Systems and methods for direct to device satellite communications

Abstract

Systems and methods for direct-to-device satellite communications in which a centralized processor coupled to a network receives data streams intended for user equipment (UE) devices located in a coverage area. The processor obtains channel state information (CSI) characterizing radio frequency (RF) channels between the UEs and antennas of a plurality of satellites orbiting the coverage area. Precoding weights are computed based on the CSI, and precoded waveforms are generated. The plurality of satellites cooperatively transmit the precoded waveforms such that they combine coherently at the location of each UE to form independent RF channels, delivering distinct data streams to the UEs. The system may exploit uplink / downlink channel reciprocity and derive full bandwidth CSI from narrowband uplink sounding signals.

Description

Atty. Docket No. 00652-0847 (P544PCT) PatentUNITED STATES PATENT APPLICATIONforSYSTEMS AND METHODS FOR DIRECT TO DEVICE SATELLITE COMMUNICATIONSInventors:Stephen G. PerlmanFadi SaibiAttorney’s Docket No. 00652-0847 (P544PCT)P544SYSTEMS AND METHODS FOR DIRECT TO DEVICE SATELLITE COMMUNICATIONS RELATED APPLICATIONS

[0001] This patent application claims the benefit and priority of the following United States Provisional Applications: U. S. Provisional Application No. 63 / 753,537, filed February 4, 2025, entitled “Systems and Methods for Direct to Device Satellite Communications”; U. S. Provisional Application No. 63 / 780,846, filed March 31, 2025, entitled “Systems and Methods for Direct to Device Satellite Communications”; U. S. Provisional Application No. 63 / 806,300, filed May 15, 2025, entitled “Systems and Methods for Direct to Device Satellite Communications”; and U. S. Provisional Application No. 63 / 882,716, filed Sep. 16, 2025, entitled “Systems and Methods for Direct to Device Satellite Communications”. The entire contents of each of the aboveidentified applications are hereby incorporated by reference in their entirety for all purposes.

[0002] This application may be related to the following issued U. S. Patents and co-pending U. S. Patent Applications:

[0003] U. S. Patent No. 12,537,580, issued Jan. 27, 2026, entitled, “System and Methods for Exploiting Inter-Cell Multiplexing Gain in Wireless Cellular Systems Via Distributed Input Distributed Output Technology”;

[0004] U. S. Patent No. 12,470,941, issued Oct. 29, 2025, entitled “System And Method For Concurrent Spectrum Usage within Actively Used Spectrum”;

[0005] U. S. Patent No. 12,355,520, issued July 8, 2025, entitled “System and Methods for Radio Frequency Calibration Exploiting Channel Reciprocity in Distributed Input Distributed Output Wireless Communications”;

[0006] U. S. Patent No. 12,355,519, issued July 8, 2025, entitled “System and Methods for Radio Frequency Calibration Exploiting Channel Reciprocity in Distributed Input Distributed Output Wireless Communications”;

[0007] U. S. Patent No. 12,341,582, issued June 24, 2025, entitled “System And Method For Mitigating Interference within Actively Used Spectrum”;

[0008] U. S. Patent No. 12,244,369, issued March 4, 2025, entitled “System and Methods for Radio Frequency Calibration Exploiting Channel Reciprocity in Distributed Input Distributed Output Wireless Communications”;

[0009] U. S. Patent No. 12,237,888, issued Feb. 25, 2025, entitled “System and Methods for Radio Frequency Calibration Exploiting Channel Reciprocity in Distributed Input Distributed Output Wireless Communications”;

[0010] U. S. Patent No. 12,224,819, issued Feb. 11, 2025, entitled “System and Methods for Radio Frequency Calibration Exploiting Channel Reciprocity in Distributed Input Distributed Output Wireless Communications”;

[0011] U. S. Patent No. 12,170,401, issued Dec. 17, 2024, entitled “System And Method For Distributing Radioheads”;

[0012] U. S. Patent No. 12,166,546, issued Dec. 10, 2024, entitled “System and Methods for Radio Frequency Calibration Exploiting Channel Reciprocity in Distributed Input Distributed Output Wireless Communications”;

[0013] U. S. Patent No. 12,166,280, issued Dec. 10, 2024, entitled “System And Method For Distributing Radioheads”;

[0014] U. S. Patent No. 11,923,931, issued March 5, 2024, entitled “System and Method For Distributed Antenna Wireless Communications”;

[0015] U. S. Patent No. 11,901,992, issued Feb. 13, 2024, entitled “Systems And Methods For Exploiting Inter-Cell Multiplexing Gain In Wireless Cellular Systems Via Distributed Input Distributed Output Technology”;

[0016] U. S. Patent No. 11,818,604, issued Nov. 14, 2023, entitled “Systems And Methods For Exploiting Inter-Cell Multiplexing Gain In Wireless Cellular Systems Via Distributed Input Distributed Output Technology”;

[0017] U. S. Patent No. 11,646,773, issued May 9, 2023, entitled “System and Method For Distributed Antenna Wireless Communications”;

[0018] U. S. Patent No. 11,581,924, issued Feb. 14, 2023, entitled “System and Methods for Radio Frequency Calibration Exploiting Channel Reciprocity in Distributed Input Distributed Output Wireless Communications”;

[0019] U. S. Patent No. 11,451,281, issued September 20, 2022, entitled “Systems And Methods For Exploiting Inter-Cell Multiplexing Gain In Wireless Cellular Systems Via Distributed Input Distributed Output Technology”;

[0020] U. S. Patent No. 11,451,275, issued September 20, 2022, entitled “System and Method For Distributed Antenna Wireless Communications”;

[0021] U. S. Patent No. 11,394,436, issued July 19, 2022, entitled “System and Method For Distributed Antenna Wireless Communications”;

[0022] U. S. Patent No. 11,309,943, issued April 19, 2022, entitled “System and Methods for Planned Evolution and Obsolescence of Multiuser Spectrum”;

[0023] U. S. Patent No. 11,290,162, issued March 29, 2022, entitled “System And Method For Mitigating Interference within Actively Used Spectrum”;

[0024] U. S. Patent No. 11,196,467, issued December 7, 2021, entitled “System and Method For Distributed Antenna Wireless Communications”;

[0025] U. S. Patent No. 11,190,947, issued Nov. 30, 2021, entitled “System And Method For Concurrent Spectrum Usage within Actively Used Spectrum”;

[0026] U. S. Patent No. 11,190,247, issued November 30, 2021, entitled “System and Method For Distributed Antenna Wireless Communications”;

[0027] U. S. Patent No. 11,190,246, issued November 30, 2021, entitled “System and Method For Distributed Antenna Wireless Communications”;

[0028] U. S. Patent No. 11,189,917, filed Nov. 30, 2021, entitled “System And Method For Distributing Radioheads”;

[0029] U. S. Patent No. 11,146,313, issued October 12, 2021, entitled “System and Methods for Radio Frequency Calibration Exploiting Channel Reciprocity in Distributed Input Distributed Output Wireless Communications”;

[0030] U. S. Patent No. 11,070,258, issued July 20, 2021, entitled “System and Methods for Planned Evolution and Obsolescence of Multiuser Spectrum”;

[0031] U. S. Patent No. 11,050,468, issued June 29, 2021, entitled “System And Method For Mitigating Interference within Actively Used Spectrum”;

[0032] U. S. Patent No. 10,985,811, issued April 20, 2021, entitled “System and Method For Distributed Antenna Wireless Communications”;

[0033] U. S. Patent No. 10,886,979, issued Jan. 4, 2021, entitled “System And Method For Link adaptation In DIDO Multicarrier Systems”;

[0034] U. S. Patent No. 10,848,225, issued Nov. 24, 2020, entitled “Systems And Methods For Exploiting Inter-Cell Multiplexing Gain In Wireless Cellular Systems Via Distributed Input Distributed Output Technology”;

[0035] U. S. Patent No. 10,749,582, issued Aug. 18, 2020, entitled “Systems and Methods to Coordinate Transmissions in Distributed Wireless Systems via User Clustering”;

[0036] U. S. Patent No. 10,727,907, issued July 28, 2020, entitled “System and Methods to Enhance Spatial Diversity in Distributed-Input Distributed-Output Wireless Systems”;

[0037] U. S. Patent No. 10,547,358, issued Jan. 28, 2020, entitled “System and Methods for Radio Frequency Calibration Exploiting Channel Reciprocity in Distributed Input Distributed Output Wireless Communications”;

[0038] U. S. Patent No. 10,425,134, issued Sep. 24, 2019, entitled “System and Methods for Planned Evolution and Obsolescence of Multiuser Spectrum”;

[0039] U. S. Patent No. 10,349,417, issued July 9, 2019, entitled “System and Methods to Compensate for Doppler Effects in Distributed-Input Distributed Output Systems”;

[0040] U. S. Patent No. 10,333,604, issued, June 25, 2019, entitled “System and Method For Distributed Antenna Wireless Communications”;

[0041] U. S. Patent No. 10,320,455, issued June 11, 2019, entitled “Systems and Methods to Coordinate Transmissions in Distributed Wireless Systems via User Clustering”;

[0042] U. S. Patent No. 10,277,290, issued April 30, 2019, entitled “Systems and Methods to Exploit Areas of Coherence in Wireless Systems”;

[0043] U. S. Patent No. 10,243,623, issued March 26, 2019, entitled “System and Methods to Enhance Spatial Diversity in Distributed-Input Distributed-Output Wireless Systems”;

[0044] U. S. Patent No. 10,200,094, issued Feb. 5, 2019, entitled “Interference Management, Handoff, Power Control And Link Adaptation In Distributed-Input Distributed-Output (DIDO) Communication Systems”;

[0045] U. S. Patent No. 10,194,346, issued Jan. 29, 2019, entitled “System and Methods for Exploiting Inter-Cell Multiplexing Gain in Wireless Cellular Systems Via Distributed Input Distributed Output Technology”;

[0046] U. S. Patent No. 10,187,133, issued Jan. 22, 2019, entitled “System And Method For Power Control And Antenna Grouping In A Distributed-Input-Distributed-Output (DIDO) Network”;

[0047] U. S. Patent No. 10,164,698, issued Dec. 25, 2018, entitled “System and Methods for Exploiting Inter-Cell Multiplexing Gain in Wireless Cellular Systems Via Distributed Input Distributed Output Technology”;

[0048] U. S. Patent No. 9,973,246, issued May 15, 2018, entitled “System and Methods for Exploiting Inter-Cell Multiplexing Gain in Wireless Cellular Systems Via Distributed Input Distributed Output Technology”;

[0049] U. S. Patent No. 9,923,657, issued March 20, 2018, entitled “System and Methods for Exploiting Inter-Cell Multiplexing Gain in Wireless Cellular Systems Via Distributed Input Distributed Output Technology”;

[0050] U. S. Patent No. 9,826,537, issued November 21, 2017, entitled “System And Method For Managing Inter-Cluster Handoff Of Clients Which Traverse Multiple DIDO Clusters”;

[0051] U. S. Patent No. 9,819,403, issued November 14, 2017, entitled “System And Method For Managing Handoff Of A Client Between Different Distributed-Input-Distributed-Output (DIDO) Networks Based On Detected Velocity Of The Client”;

[0052] U. S. Patent No. 9,685,997, issued June 20, 2017, entitled “Systems and Methods to Enhance Spatial Diversity in Distributed Input Distributed Output Wireless Systems.”;

[0053] U. S. Patent No. 9,386,465, issued, July 5, 2016, entitled “System and Method For Distributed Antenna Wireless Communications”;

[0054] U. S. Patent No. 9,369,888, issued June 14, 2016, entitled “Systems and Methods to Coordinate Transmissions in Distributed Wireless Systems via User Clustering”;

[0055] U. S. Patent No. 9,312,929, issued April 12, 2016, entitled “System and Methods to Compensate for Doppler Effects in Distributed-Input Distributed Output Systems.”;

[0056] U. S. Patent No. 8,989,155, issued March 24, 2015, entitled “System and Methods for Wireless Backhaul in Distributed-Input Distributed-Output Wireless Systems”;

[0057] U. S. Patent No. 8,971,380, issued March 3, 2015, entitled “System And Method For Adjusting DIDO Interference Cancellation Based On Signal Strength Measurements”;

[0058] U. S. Patent No. 8,654,815, issued Feb. 18, 2014, entitled “System and Method For Distributed Antenna Wireless Communications”;

[0059] U. S. Patent No. 8,571,086, issued Oct. 29, 2013, entitled “System And Method For DIDO Precoding Interpolation In Multicarrier Systems”;

[0060] U. S. Patent No. 8,542,763, issued Sep. 24, 2013, entitled “Systems And Methods To Coordinate Transmissions In Distributed Wireless Systems Via User Clustering”;

[0061] U. S. Patent No. 8,428,162, issued April 23, 2013, entitled “System and Method for Distributed Input Distributed Output Wireless Communication”;

[0062] U. S. Patent No. 8,170,081, issued May 1, 2012, entitled “System And Method For Adjusting DIDO Interference Cancellation Based On Signal Strength Measurements”;

[0063] U. S. Patent No. 8,160,121, issued Apr. 17, 2012, entitled, “System and Method For Distributed Input-Distributed Output Wireless Communications”;

[0064] U. S. Patent No. 7,885,354, issued Feb. 8, 2011, entitled “System and Method For Enhancing Near Vertical Incidence Skywave (“NVIS”) Communication Using Space-Time Coding.”;

[0065] U. S. Patent No. 7,711,030, issued May 4, 2010, entitled “System and Method For Spatial-Multiplexed Tropospheric Scatter Communications”;

[0066] U. S. Patent No. 7,636,381, issued Dec. 22, 2009, entitled “System and Method for Distributed Input Distributed Output Wireless Communication”;

[0067] U. S. Patent No. 7,633,994, issued Dec. 15, 2009, entitled “System and Method for Distributed Input Distributed Output Wireless Communication”;

[0068] U. S. Patent No. 7,599,420, issued Oct. 6, 2009, entitled “System and Method for Distributed Input Distributed Output Wireless Communication”;

[0069] U. S. Patent No. 7,418,053, issued August 26, 2008, entitled “System and Method for Distributed Input Distributed Output Wireless Communication”;

[0070] U. S. Patent Application No. 19 / 440,224 filed January 5, 2026, entitled “Systems and Methods for Exploiting Inter-cell Multiplexing Gain in Wireless Cellular Systems Via Distributed Input Distributed Output Technology”;

[0071] U. S. Patent Application No. 19 / 415,582 filed December 10, 2025, entitled “Systems and Methods for Exploiting Inter-cell Multiplexing Gain in Wireless Cellular Systems Via Distributed Input Distributed Output Technology”;

[0072] U. S. Patent Application No. 19 / 280,444 filed July 25, 2025, entitled “System And Method For Exploiting Inter-cell Multiplexing Gain in Wireless Cellular Systems Via Distributed Input Distributed Output Technology”;

[0073] U. S. Patent Application No. 19 / 214,698, filed May 21, 2025, entitled “System And Method For Mitigating Interference within Actively Used Spectrum”;

[0074] U. S. Patent Application No. 19 / 199,110, filed May 5, 2025, entitled “System and Methods for Radio Frequency Calibration Exploiting Channel Reciprocity in Distributed Input Distributed Output Wireless Communications”;

[0075] U. S. Patent Application No. 18 / 981,039, filed Oct. 12, 2024, entitled “System And Method For Distributing Radioheads”;

[0076] U. S. Patent Application No. 18 / 389,127, filed Nov. 13, 2023, entitled “System and Methods for Exploiting Inter-Cell Multiplexing Gain in Wireless Cellular Systems Via Distributed Input Distributed Output Technology”;

[0077] U. S. Patent Application No. 16 / 505,593, filed July 8, 2019, entitled “System and Methods to Compensate for Doppler Effects in Distributed-Input Distributed Output Systems”;

[0078] U. S. Patent Application No. 14 / 611,565, filed Feb. 2, 2015, entitled “System and Method For Mapping Virtual Radio Instances Into Physical Areas of Coherence in Distributed Antenna Wireless Systems”.TECHNICAL FIELD

[0079] The present disclosure generally relates to systems and methods for multiantenna multiplexing, antenna, and diversity gain in satellite wireless communications networks via spatial processing.BACKGROUND

[0080] In the last three decades, the wireless cellular market has experienced increasing number of subscribers worldwide as well as demand for better services shifting from voice to web-browsing and real-time HD video streaming. This increasing demand for services that requires higher data rate, lower latency and improved reliability has driven a radical evolution of wireless technologies through different standards. Beginning from the first generation analog AMPS and TAGS (for voice service) in the early 1980s, to 2G and 2.5G digital GSM, IS-95 and GPRS (for voice and data services) in the 1990s, to 3G with UMTS and CDMA2000 (for web-browsing) in the early 2000s, and finally LTE (for high-speed internet connectivity), refined by 5GNR, deployed in different countries worldwide.

[0081] Long-term evolution (LTE) is the standard developed by the 3rdgeneration partnership project (3GPP) for fourth generation (4G) wireless cellular systems. LTEcan achieve theoretically up to 4x improvement in downlink spectral efficiency over previous 3G and HSPA+ standards by exploiting the spatial components of wireless channels via multiple-input multiple-output (MIMO) technology. LTE-Advanced is the evolution of LTE, that theoretically was to enable up to 8x increase in spectral efficiency over 3G standard systems. 5GNR is the evolution of LTE-Advanced claiming even higher spectral efficiency than LTE.

[0082] Despite this technology evolution, it is very likely that in the next three years wireless carriers will not be able to satisfy the growing demand for data rate due to raising market penetration of smartphones and tables, offering more data-hungry applications like real-time HD video streaming, video conferencing and gaming.

[0083] As capacity gains offered by LTE / 5GNR deployment and increased spectrum availability are insufficient, the only foreseeable solution to prevent this upcoming spectrum crisis is to promote new wireless technologies [Reference 29], LTE-Advanced (the evolution of LTE standard) promised additional gains over LTE through more sophisticated MIMO techniques and by increasing the density of “small cells” [Reference 30], 5GNR and Massive MIMO promised even more spectral efficiency gains. However, there are limits to the number of cells that can fit a certain area without incurring interference issues or increasing the complexity of the backhaul to allow coordination across cells.

[0084] One promising technology that will provide orders of magnitude increase in spectral efficiency over wireless links without the limitations of conventional cellular systems is distributed-input distributed-output (DIDO) technology (see Related Patents and Applications referenced below), now branded commercially as pCell® technology and generally referred to in academia as Cell-Free Massive MIMO. The present disclosure describes DIDO / pCell technology employed in the context of cellular systems (such as LTE or LTE-Advanced), both within and without the constraints of cellular standards, to provide significant performance benefits over conventional wireless systems. We begin with an overview on MIMO and review different spatial processing techniques employed by LTE and LTE-Advanced, which are also employed by 5GNR and 5GNTN. Then we show how the present disclosure provides significant capacity gains for next generation wireless communications systems compared to prior art approaches.

[0085] MIMO employs multiple antennas at the transmitter and receiver sides of the wireless link and uses spatial processing to improve link reliability via diversitytechniques (i.e., diversity gain) or provide higher data rate via multiplexing schemes (i.e., multiplexing gain) [References 1-2]. Diversity gain is a measure of enhanced robustness to signal fading, resulting in higher signal-to-noise ratio (SNR) for fixed data rate. Multiplexing gain is obtained by exploiting additional spatial degrees of freedom of the wireless channel to increase data rate for fixed probability of error. Fundamental tradeoffs between diversity and multiplexing in MIMO systems were described in [References 3-4].

[0086] In practical MIMO systems, link adaptation techniques can be used to switch dynamically between diversity and multiplexing schemes based on propagation conditions [References 20-23], For example, link adaptation schemes described in [References 22-23] showed that beamforming or Orthogonal Space-Time Block Codes (OSTBC) are preferred schemes in low SNR regime or channels characterized by low spatial selectivity. By contrast, spatial multiplexing can provide significant gain in data rate for channels with high SNR and high spatial selectivity. For example, Figure 1 shows that cells can be divided in two regions: i) multiplexing region 101, characterized by high SNR (due to proximity to the cell tower or base station) where the spatial degrees of freedom of the channel can be exploited via spatial multiplexing to increase data rate; ii) diversity region 102 or cell-edge, where spatial multiplexing techniques are not as effective and diversity methods can be used to improve SNR and coverage (yielding only marginal increase in data rate). Note that the circle of the macrocell 103 in Figure 1 labels the shaded center of the circle as the “multiplexing region” and the unshaded outer region of the circle as the “diversity region”. This same region designation is used throughout Figures 1,3-5, where the shaded region is the “multiplexing region” and the unshaded region is the “diversity region”, even if they are not labeled. For example, the same designation is used for the small-cell 104 in Figure 1

[0087] The LTE (Release 8) and LTE-Advanced (Release 10) standards define a set of ten transmission modes (TM) including either diversity or multiplexing schemes [References 35,85-86]:• Mode 1: Single antenna port, port 0• Mode 2: Transmit diversity• Mode 3: Large-delay cyclic delay diversity (CDD), extension of open-loop spatial multiplexing for single-user MIMO (SU-MIMO)• Mode 4: Closed-loop spatial multiplexing for SU-MIMO• Mode 5: Multi-user MIMO (MU-MIMO)• Mode 6: Closed-loop spatial multiplexing, using a single transmission layer • Mode 7: Single antenna port, UE-specific RS (port 5)• Mode 8: Single or dual-layer transmission with UE-specific RS (ports 7 and / or 8)• Mode 9: Single or up to eight layers closed-loop SU-MIMO (added in Release 10)• Mode 10: Multi-layer closed-loop SU-MIMO, up to eight layers (added in Release 10)

[0088] Hereafter we describe diversity and multiplexing schemes commonly used in cellular systems as well as specific methods employed in LTE as outlined above, and compare them against techniques that are unique for DIDO communications. We first identify two types of transmission methods: i) intra-cell methods (exploiting microdiversity in cellular systems), using multiple antennas to improve link reliability or data rate within one cell; ii) inter-cell methods (exploiting macro-diversity), allowing cooperation between cells to provide additional diversity or multiplexing gains. Then we describe how the present disclosure provides significant advantages (including spectral capacity gain) over prior art.i. Intra-cell Diversity Methods

[0089] Intra-cell diversity methods operate within one cell and are designed to increase SNR in scenarios with poor link quality (e.g., users at the cell-edge subject to high pathloss from the central tower or base station). Typical diversity schemes employed in MIMO communications are beamforming [References 5-11] and orthogonal space-time block codes (OSTBC) [References 12-15],

[0090] Diversity techniques supported by the LTE standard are transmit diversity, closed-loop rank-1 precoding and dedicated beamforming [References 31-35], Transmit diversity scheme supports two or four transmit antennas over the downlink (DL) and only two antennas for the uplink (UL). In the DL channel, it is implemented via space-frequency block codes (SFBC) combined with frequency-switched transmit diversity (FSTD) to exploit space as well as frequency selectivity [Reference 31], Rank-1 precoding creates a dedicated beam to one user based on quantized weightsselected from a codebook (pre-designed using limited feedback techniques [References 36-42]) to reduce the feedback overhead from the user equipment (UE) to the base transceiver station (BTS 105 in Figure 1, or eNodeB using LTE terminology). Alternatively, dedicated beamforming weights can be computed based on UE-specific reference signal.ii. Intra-cell Multiplexing Methods

[0091] MIMO multiplexing schemes [References 1,19] provide gain in data rate in high SNR regime and in scenarios with enough spatial degrees of freedom in the channel (e.g., rich multipath environments with high spatial selectivity [References 16-18]) to support multiple parallel data streams over wireless links.

[0092] The LTE standard supports different multiplexing techniques for single-user MIMO (SU-MIMO) and multi-user MIMO (MU-MIMO) [Reference 31], SU-MIMO schemes have two modes of operation: i) closed-loop, exploiting feedback information from the UE to select the DL precoding weights; ii) open-loop, used when feedback from the UE is unavailable or the UE is moving too fast to support closed-loop schemes. Closed-loop schemes use a set of pre-computed weights selected from a codebook. These weights can support two or four transmit antennas as well as one to four parallel data streams (identified by number of layers of the precoding matrix), depending on the UE request and decision of the scheduler at the BTS. LTE-Advanced will include new transmission modes up to MIMO 8x8 to provide up to 8x increase in spectral efficiency via spatial processing [Reference 62],

[0093] MU-MIMO schemes are defined for both UL and DL channels [References 31,50], In the UL, every UE sends a reference signal to the BTS (made up of cyclically shifted version of the Zadoff-Chu sequence [Reference 33]). Those reference signals are orthogonal, such that the BTS can estimate the channel from all UEs and demodulate data streams from multiple UEs simultaneously via spatial processing. In the DL, precoding weights for different UEs are selected from codebooks based on the feedback from the UEs and the scheduler (similarly to closed-loop SU-MIMO schemes) and only rank-1 precoding is allowed for every UE (e.g., each UE receives only one data stream).

[0094] Intra-cell multiplexing techniques employing spatial processing provide satisfactory performance only in propagation scenarios characterized by high SNR (orSINR) and high spatial selectivity (multipath-rich environments). For conventional macrocells, these conditions may be harder to achieve as BTSs are typically far from the UEs and the distribution of the SINR is typically centered at low values [Reference 43], In these scenarios, MU-MIMO schemes or diversity techniques may be better choices than SU-MIMO with spatial multiplexing.

[0095] Other techniques and network solutions contemplated by LTE-Advanced to achieve additional multiplexing gain (without requiring spatial processing through MIMO) are: carrier aggregation (CA) and small cells. CA [References 30,44-47] combines different portions of the RF spectrum to increase signal bandwidth up to 100MHz [Reference 85], thereby yielding higher data rates. Intra-band CA combines different bands within the same portion of the spectrum. As such it can use the same RF chain for multiple channels, and multiple data streams are recombined in software. Inter-band CA requires different RF chains to operate at different portions of the spectrum as well as signal processing to recombine multiple data streams from different bands.

[0096] The key idea of small cells [References 30,47] is to reduce the size of conventional macro-cells, thereby allowing higher cell density and larger throughput per area of coverage. Small-cells are typically deployed through inexpensive access points 106 with low power transmission (as depicted in Figure 1) as opposed to tall and expensive cell towers used for macro-cells. Two types of small cells are defined in LTE-Advanced: i) metrocells, for outdoor installation in urban areas, supporting up 32 to 64 simultaneous users; and ii) femtocells, for indoor use, can serve at most 4 active users. One advantage of small cells is that the density of UEs close to the BTS is statistically higher, yielding better SNR that can be exploited via spatial multiplexing to increase data rate. There are, however, still many concerns about practical deployment of small cells, particularly related to the backhaul. In fact, it may be challenging to reach BTSs of every small cell via high-speed wireline connections, especially considering the high density of metrocells and femtocells in a given coverage area. While using Line-Of-Sight (LOS) backhaul to small cells can often be implemented inexpensively, compared to wireline backhaul, there often are no practical LOS backhaul paths available for preferred small cell BTS placements, and there is no general solution for Non-Line-Of-Sight (NLOS) wireless backhaul to small cell BTSs. Moreover, small cells require complex real-time coordination across BTSs to avoid interference as in self-organized networks (SON) [References 30,51-52] andsophisticated cell-planning tools (even more complex than conventional cellular systems, due to higher density of small cells) to plan their optimal location [References 48,49], Finally, handoff is a limiting factor for small cells deployment, particularly in scenarios where groups of subscribers switch cells at the same time, causing large amount of handoff overhead over the backhaul, resulting in high latency and unavoidable dropped calls.

[0097] It can be trivially shown there is no practical general solution that enables small cells to co-exist with macrocells and achieve optimal, or necessarily even improved, throughput. Among the myriad of such unsolvable situations is when a small cell is located such that its UEs unavoidably overlap with a macrocell transmission and the small cell and the macrocell use the same frequencies to reach their respective UEs. Clearly in this situation, the macrocell transmission will interfere with the small cell transmission. While there may be some approach that mitigates such interference for particular circumstances of a particular macrocell, a particular small cell, the particular macrocell and small cell UEs involved, the throughput requirements of those UEs, and environmental circumstances, etc., any such approach would be highly specific, not only to the static plan of the macrocell and small cell, but to the dynamic circumstances of a particular time interval. Typically, the full throughput of the channel to each UE cannot be achieved.iii. Inter-cell Diversity Methods

[0098] In a heterogeneous network (HetNet) [Reference 90] where macro-cells coexist with small-cells (e.g., metro-cells, pico-cells and femto-cells) it is necessary to employ different techniques to eliminate inter-cell interference. While HetNets provide better coverage through small-cells, the gains in data rate are only marginal since they require sharing the spectrum through different forms of frequency reuse patterns or using spatial processing to remove interference rather than achieve multiplexing gain. The LTE standards employ inter-cell interference coordination (ICIC) schemes to remove interference particularly at the cell-edge. There are two types of ICIC methods: cell-autonomous and coordinated between BTSs.

[0099] Cell-autonomous ICIC schemes avoid inter-cell interference via different frequency reuse patterns depicted in Figure 2, where the hexagons represent the cells and the colors refer to different carrier frequencies. Three types of schemes are considered in LTE: i) full frequency reuse (or reuse 1), where the cells utilize all theavailable bandwidth as in Figure 2A, thereby producing high interference at the celledge; ii) hard frequency reuse (HFR), where every cell is assigned with a different frequency band as in Figure 2B (with typical reuse factor of 3) to avoid interference across adjacent cells; iii) fractional frequency reuse (FFR), where the center of the cell is assigned with the whole available bandwidth as in frequency reuse 1, whereas the cell-edge operates in HFR mode to mitigate inter-cell interference as in Figure 2C.

[0100] Coordinated ICIC methods enable cooperation across BTSs to improve performance of wireless networks. These techniques are a special case of methods taught in Related Patents and Applications below to enable cooperation across wireless transceivers in the general case of distributed antenna networks for multiple UEs all using the same frequency simultaneously. Cooperation across BTSs to remove inter-cell interference for the particular case of cellular systems for a single UE at a given time at a given frequency was described in [Reference 53], The system in [Reference 53] divides every macrocell into multiple subcells and enables soft-handoff across subcells by employing dedicated beamforming from coordinated BTSs to improve link robustness at a single UE at a single frequency, as it moves along the subcell boundaries.

[0101] More recently, this class of cooperative wireless cellular networks has been defined in the MIMO literature as “network MIMO” or “coordinated multi-point” (CoMP) systems. Theoretical analysis and simulated results on the benefits obtained in network MIMO by eliminating inter-cell interference are presented in [References 54-61], The key advantage of network MIMO and CoMP is to remove inter-cell interference in the overlapping regions of the cells denoted as “interference region” 301 in Figure 3 for the case of macro-cells 302.

[0102] CoMP networks are actively becoming part of LTE-Advanced standard as a solution to mitigate inter-cell interference in next generation cellular networks [References 62-64], Three CoMP solutions have been proposed so far in the standard to remove inter-cell interference: i) coordinated scheduling / beamforming (CS / CB), where the UE receives its data stream from only one BTS via beamfoming and coordination across BTSs is enabled to remove interference via beamforming or scheduling techniques; ii) dynamic cell selection (DCS) that chooses dynamically the cell for every UE on a per-subframe basis, transparently to the UE; iii) joint transmission (JT), where data for given UE is jointly transmitted from multiple BTSs to improve received signal quality and eliminate inter-cell interference. CoMP-JT yieldslarger gains than CoMP-CS / CB at the expenses of higher overhead in the backhaul to enable coordination across BTSs.iv. Inter-cell Multiplexing Methods

[0103] Prior art multi-user wireless systems add complexity and introduce limitations to wireless networks which result in a situation where a given user’s experience (e.g. available throughput, latency, predictability, reliability) is impacted by the utilization of the spectrum by other users in the area. Given the increasing demands for aggregate throughput within wireless spectrum shared by multiple users, and the increasing growth of applications that can rely upon multi-user wireless network reliability, predictability and low latency for a given user, it is apparent that prior art multi-user wireless technology suffers from many limitations. Indeed, with the limited availability of spectrum suitable for particular types of wireless communications (e.g. at wavelengths that are efficient in penetrating building walls), prior art wireless techniques will be insufficient to meet the increasing demands for bandwidth that is reliable, predictable and low-latency.

[0104] Prior art intra-cell diversity and multiplexing methods can only provide up to a theoretical 4x increase in throughput over current cellular networks for LTE (through MIMO 4x4) or at most a theoretical 8x for LTE-Advanced (through MIMO 8x8), although higher orders of MIMO achieve diminishing improvements in increasing throughput in a given multipath environment, particularly as UEs (such as smartphones) get smaller and more constrained in terms of antenna placement. Other marginal throughput gains in next generation cellular systems may be obtained from additional spectrum allocation (e.g., FCC national broadband plan), exploited via carrier aggregation techniques, and more dense distribution of BTSs via small cell networks and SON [References 30,46], All the above techniques, however, still rely heavily on spectrum or time sharing techniques to enable multi-user transmissions, since the spectral efficiency gains obtained by spatial processing is limited.

[0105] While prior art inter-cell methods (e.g., network MIMO and CoMP systems [References 53-64]) can improve reliability of cellular networks by eliminating inter-cell interference, their capacity gains are only marginal. In fact, those systems constrain power transmitted from every BTS to be contained within the cell boundaries and are only effective to eliminate inter-cell interference due to power leakage across cells.Figure 3 shows one example of cellular networks with three BTSs, each one characterized by its own coverage area or cell. The power transmitted from each BTS is constrained to limit the amount of interference across cells, depicted in Figure 3 by the areas where the cells overlap. As these systems operate in the low SINR regime at the interference region, their gains in spectral efficiency is only marginal, similarly to intra-cell schemes for SU-MIMO. To truly obtain significant capacity gains in intercell cooperative networks, power constraints limited to cell-boundaries must be relaxed and spatial multiplexing techniques should be enabled throughout the cells where the SINR is high (not just at the cell-edge with poor SINR performance as in prior art approaches).

[0106] Figure 4 shows the case where the power transmitted from the three BTSs 401 all transmitting simultaneously at the same frequency is increased, thereby allowing a higher level of interference throughout the cell 402. In prior art systems, such interference would result in incoherent interference (disrupting UE signal reception) throughout the interfering areas of the BTSs, but this interference is actually exploited in the present disclosure through novel inter-cell multiplexing methods using spatial processing to create areas of coherent interference (enhancing UE signal reception) around every UE, thereby providing simultaneous non-interfering data streams to every UE and increasing their SINR throughout the cell.

[0107] The scenario depicted in Figure 4 is described in [Reference 89] for the particular case of cellular systems. The system in [Reference 89] is made up of several BTSs identifying different cells that are grouped into clusters. Cooperation is allowed only across BTSs from adjacent cells within the same clusters. In this case it was shown that, as the power transmitted from the BTSs increases, there is a limit to the capacity (or spectral efficiency) achievable through inter-cell multiplexing methods. In fact, as the transmit power increases, the out-of-cluster interference increases proportionally, producing a saturation regime for the SINR and consequently for the capacity. As a consequence of this effect, the system in [Reference 89] can theoretically achieve at most 3x gain in capacity (i.e., at most three cells within the cluster) and any additional cell included in the cluster would reduce capacity due to increased out-of-cluster interference (e.g., the case of 21 cells per cluster yields lower capacity than the case of 3 cells per cluster). We observe that the fundamental capacity limit in [Reference 89] holds because the BTSs are constrained to predefined locations, as in cellular systems, and multiplexing gain is achieved by increasingtransmit power from the BTSs. To obtain theoretically unlimited capacity gain via intercell multiplexing methods, the constraint on the BTS placement must be removed, allowing the BTSs to be placed anywhere is convenient.

[0108] It would thus be desirable to provide a system that achieves orders of magnitudes increase in spectral efficiency exploiting inter-cell multiplexing gain via spatial processing by removing any constraint on the power transmitted from distributed BTSs 501 as well as on their placement. Figure 5 shows one example where many additional access points 502 are added to deliberately increase the level of incoherent interference throughout the cell 503, that is exploited in the present disclosure to generate areas of coherent interference around UEs, thereby yielding theoretically unlimited inter-cell multiplexing gain. The additional access points are placed serendipitously wherever it is convenient and are not constrained to any specific cell planning, as in cellular systems described in prior art. In an exemplary embodiment of the disclosure, the serendipitous access points are distributed-input distributed-output (DIDO / pCell) access points and the inter-cell multiplexing gain is achieved through DIDO / pCell methods described in Related Patents and Applications listed below and [References 77-78], In another embodiment, the serendipitous access points are low power transceivers, similar to inexpensive Wi-Fi access points or small-cells [References 30,47], thereby providing smaller areas of coverage overlapping throughout the macro-cell as shown in Figure 5.

[0109] We observe that prior art inter-cell methods [References 53-64] avoid incoherent interference by intentionally limiting the transmit power from every BTS as in Figure 3 and eliminate residual inter-cell interference (on the overlapping areas between cells) via spatial processing, thereby providing improved SINR and inter-cell diversity gain. We further observe that [Reference 89] constrains BTS placement to cell planning while increasing transmit power, thereby limiting the achievable capacity due to out-of-cl uster interference, and as such it is still limited by interference. By contrast, the present disclosure exploits incoherent interference to create coherent interference around the UEs, by transmitting higher power from every BTS serendipitously placed, thereby improving signal quality at the UE that is necessary condition to obtain inter-cell multiplexing gain throughout the cell via spatial processing. As such, the systems described in prior art cannot be used to achieve unlimited inter-cell multiplexing gain via spatial processing, since there is not sufficient SINR throughout the cell (due to the limited transmit power from the BTSs or the out-of-cluster interference when transmit power is increased) to enable inter-cell multiplexing methods as in the present disclosure. Moreover, the systems described in prior art would be inoperable to achieve the multiplexing gain achieved in the present disclosure depicted in Figures 4-5, given that prior art systems were designed to avoid inter-cell interference within the diversity regions shown in the shaded area of Figure 1 and Figures 3-5 rather than exploit inter-cell interference in the multiplexing regions to obtain inter-cell multiplexing gain as achieved in the present disclosure.

[0110] In cellular systems, user mobility across adjacent cells is typically handled via handoff. During handoff, the information of the user is passed from the base station of the current cell to the base station of the adjacent cell. This procedure results in significant overhead over wireless links and backhaul (due to control information), latency, and potential call drops (e.g., when the cell handling handoff is overloaded). These problems are particularly exacerbated in wireless systems employing smallcells as in long term evolution (LTE) networks. In fact, the coverage area of small-cells is only a fraction of conventional macro-cell deployments, thereby increasing the probability of users moving across cells and the chances to trigger handoff procedures.

[0111] Another limit of prior art cellular systems is the rigid design of the base station architectures, which are not amenable for parallelization, particularly as the numberof subscribers joining the network increases. For example, every LTE eNodeB can support only a limited number of concurrent subscribers ranging from about 20 users for pico-cells, 60-100 users for small-cells, and up to 100-200 users for macrocells. These concurrent subscribers are typically served through complex scheduling techniques or via multiple access techniques such as orthogonal frequency division multiple access (OFDMA) or time division multiple access (TDMA).

[0112] Given the growing demand for throughput over wireless networks, in some cases at the rate of over 2x per year, and the ever increasing number of wireless subscribers using smart phones, tablets and data-hungry applications, it is desirable to design systems that can provide multiple fold increases in capacity and with scalable architectures that can support large numbers of subscribers. One promising solution is distributed-input distributed-output (DI DO / pCell) technology disclosed in the Related Patents and Applications listed below. The present embodiments of the disclosure include a novel system architecture for DIDO / pCell systems that allows for scalability and efficient use of the spectrum, even in the presence of user mobility.

[0113] One embodiment of the present disclosure includes a virtual radio instance (VRI) comprising a protocol stack that maps data streams coming from a network into physical layer I / Q samples fed to the DIDO / pCell precoder. In one embodiment each VRI is bound to one user device and the volume of coherence, as described herein, created by the DIDO / pCell precoder around that user device. As such, the VRI follows the user device as it moves around the coverage area, thereby keeping its context active and eliminating the need for handoff.

[0114] For example, “VRI teleportation” is described below as the process by which the VRI is ported from one physical radio access network (RAN) to another while maintaining the context in an active state and without disrupting the connection. Unlike handoff in conventional cellular systems, VRI teleportation seamlessly hands one VRI from one RAN to the adjacent one, without incurring any additional overhead. Moreover, because of the flexible design of VRIs and given that in one embodiment they are bound to only one user device, the architecture disclosed in the present application is very parallelizable and ideal for systems that scale up to a large number of concurrent subscribers.

[0115] Both Frequency Division Duplex (“FDD”) and Time Division Duplex (“TDD”) modes are commonly used in wireless communications systems. For example, the LTE standard supports both FDD and TDD modes, as another example 802.11 versions (e.g. Wi-Fi) support TDD mode of operation.

[0116] In the case of LTE, various numbered bands are defined within what is called “Evolved UMTS Terrestrial Radio Access” (E-UTRA) air interface. Each E-UTRA band not only specifies a particular band number, but it defines whether the band is FDD or TDD, and what bandwidths are supported within the band (e.g. see http: / / en.wikipedia.org / wiki / LTE_frequency_bands#Frequency_bands_and_channel_bandwidths for a list of E-UTRA bands and their specifications). For example, Band 7 is an FDD band defined as using the frequency ranges of 2,500-2,570 MHz for Uplink (“UL”), 2,620 - 2,690 for downlink (“DL”), it supports 5, 10, 15, 20 and MHz signal bandwidths within each of the UL and DL bands.

[0117] In many cases E-UTRA bands overlap. For example, different bands may be common spectrum that has been allocated in different markets or regions. For example, Band 41 is a TDD band using the frequency ranges of 2,496 - 2,690 MHz for both UL and DL, which overlaps with both UL and DL ranges in FDD Band 7 (e.g. see Figures 51 A and 51 B). Currently, Band 41 is used in the U. S. by Sprint, whileBand 7 is used by Rogers Wireless in the bordering country of Canada. Thus, in the U. S., 2,500-2,570 MHz is TDD spectrum, while in Canada that same frequency range is UL for FDD spectrum.

[0118] Typically, a mobile device, upon attaching to a wireless network, will scan through the band searching for transmissions from one or more base stations, and typically during the attach procedure, the base station will transmit the characteristics of the network, such as the bandwidth used by the network, and details of the protocol in use. For example, if an LTE device scans through 2,620-2,690 MHz in the U. S., it might receive an LTE DL frame transmitted by an eNodeB that identifies the spectrum as Band 41, and if the LTE device supports Band 41 and TDD, it may attempt to connect to the eNodeB in TDD mode in that band. Similarly, if an LTE device scans through 2,620-2,690 MHz in Canada, it might receive an LTE DL frame transmitted by an eNodeB that identifies the spectrum as Band 7, and if the LTE device supports Band 7 and FDD, it may attempt to connect to the eNodeB in FDD mode in Band 7.

[0119] Most early LTE networks deployed worldwide used FDD mode (e.g., Verizon, AT& T), but increasingly TDD mode is being used, both in markets with extensive FDD coverage, such as the U. S. (where Sprint is deploying TDD) and in markets that do not yet have extensive LTE coverage, such as China (where China Mobile is deploying TDD). In many cases, a single operator is deploying both FDD and TDD at different frequencies (e.g. Sprint operates both FDD LTE and TDD LTE in different frequencies in the U. S.), and may offer LTE devices which can operate in both modes, depending on which band is used.

[0120] Note that the E-UTRA list of LTE bands is by no means a final list, but rather evolves as new spectrum is allocated to mobile operators and devices to use that spectrum are specified. New bands are specified both in spectrum with no current band that overlaps its frequencies, and in spectrum in bands overlapping frequencies of previous band allocations. For example, Band 44, a TDD band spanning 703-803 MHz, was added as an E-UTRA band several years after older 700 MHz FDD bands were specified, such as Bands 12, 13, 14 and 17.

[0121] As can be seen in Figure 41, the bulk of mobile data used to be voice data (e.g. Q1 2007), which is highly symmetric. But, with the introduction of the iPhone in 2007, and the rapid adoption of Android and then introduction of the iPad in 2009, nonvoice mobile data rapidly outpaced the growth of voice data, to the point where, by themiddle of 2013, voice data was a small fraction of mobile data traffic. Non-voice data is projected to continue to grow exponentially, increasingly dwarfing voice data.

[0122] As can been seen in Figure 42, non-voice mobile data is largely dominated by media, such as streaming video, audio and Web browsing (much of which includes streaming video). Although some streaming media is UL data (e.g. during a videoconference), the vast majority is DL data, resulting is highly asymmetric DL vs. UL data usage. For example, in the Financial Times May 28, 2013 article, “Asymmetry and the impending (US) spectrum crisis”, it states that “...industry estimates of the ratio of data traffic downlink to data traffic in the uplink ranges from a ratio of about eight to one (8:1)—to considerably more.” The article then points out that the largely FDD deployments in the U. S. are very inefficient in handling such asymmetry since FDD mode allocates the same amount of spectrum to each DL and UL. As another example, Qualcomm estimated DL / UL traffic asymmetry as high as 9:1 for one of the U. S. operators, based on 2009 measurements in live networks (cfr., Qualcomm, “1000x: more spectrum - especially for small cells”, Nov. 2013, http: / / www.qualcomm.com / media / documents / files / 1000x-more-spectrum-especially-for-small-cells.pdf). Thus, even when FDD DL spectrum is heavily utilized (potentially to the point of being overloaded), the UL spectrum may be largely unused.

[0123] The Financial Times article points out that TDD is far better suited to such asymmetry since it can be configured to allocate far more timeslots to the DL data than the UL data. For example, in the case when 20 MHz is allocated to FDD (as 10+10 MHz), DL data throughput is limited to a maximum of full-time use of 10 MHz (even when the UL data needs far less than the 10 MHz it has been allocated), whereas when 20 MHz allocated to TDD, DL data throughput can use all 20 MHz the vast majority of the time, allocating the 20MHz to UL data a small percentage of the time, far better matching the characteristics of data usage today. The article acknowledges that, unfortunately, most existing U. S. mobile spectrum is already committed to FDD mode, but urges the FCC to encourage the use of TDD as it allocates new spectrum.

[0124] Although TDD would certainly allow for more efficient use of new spectrum allocations given the increasingly asymmetric nature of mobile data, unfortunately existing FDD networks deployments cannot change operating mode to TDD since the vast majority of users of such LTE FDD networks have devices that only support FDD mode and their devices would cease to be able to connect if the network were switched to TDD mode. Consequently, as LTE data usage becomes increasingly asymmetric,existing LTE FDD networks will see increasing DL congestion, while UL spectrum will be increasingly underutilized (at 8:1 DL:UL ratio, the lower estimate of the May 28, 2013 Financial Times article, that would imply that if the DL channel is fully utilized, only 1 / 8th, equivalent to 1.25MHz of 10Mhz, would be used of the UL channel). This is extremely wasteful and inefficient, particularly given the limited physical existence of practical mobile spectrum (e.g. frequencies that can penetrate walls and propagate well non-line-of-sight, such as ~450-2600 MHz) and the exponential growth of (increasingly asymmetric) mobile data (e.g. such as streaming video and other highly asymmetric data).

[0125] 5G New Radio (5GNR) was introduced in 3GPP Release 15, with enhancements through Release 18 released to equipment vendors and Releases 19 and beyond in development. Notably, 5G Releases 17 and 18 focus on non-terrestrial networks (“NTN”), with the standard sometimes called 5GNTN. Despite this technology evolution, non-terrestrial networks, as they are currently conceived within these standards, provide very low per-UE data rates in practical systems.

[0126] Examples of non-terrestrial network technology (whether using UEs capable of 3GPP Releases that are earlier or later than Release 17) are low Earth orbital (“LEO”) satellite “Direct-to-Device” (“D2D”) services such as an emergency D2D “SOS” service added to iPhones since 2022 as well as announced LTE and 5G services for unmodified mobile phones.

[0127] All D2D service offerings use cell-centric beamforming from a LEO satellite which inherently limits D2D service offerings to low data rates in very remote areas, which in turn, limits the potential size of the D2D market. This limitation arises from the fact that, at mobile frequencies and LEO altitudes, even with enormous satellites, such as the AST BlueBird satellites at roughly 64 m2in size, the smallest spot (i.e., cell) that can be created on the ground is quite large. For example, in AST SpaceMobile’s June 12, 2023 Reply Comments filing with the FCC (https: / / www.fcc.goV / ecfs / document / 1061338570221 / 1) the company states the “First generation AST BlueBird commercial spacecraft are expected to employ beams with a 48 km diameter on the ground.”

[0128] For example, if we estimate that in 20 MHz, a 5G line-of-sight (LoS) channel from a LEO would deliver at peak about 75 Mbps downlink (DL). 75 Mbps is an adequate DL data rate for a very small cell to support a reasonable density of users who are using popular streaming video services such as TikTok, X, Instagram,YouTube, Netflix, and Zoom, let alone future mobile services that will likely need higher data rates.

[0129] But, 48 km is an enormously large cell, that can easily encompass millions of users in suburban areas (e.g., the San Francisco Bay Area peninsula) let alone urban areas (e.g., New York City). But even in rural areas, there are still thousands of users in a 48 km diameter cell. A 48 km circle is about 700 sq. mi. The U. S. government defines “Rural” as “population density of 35 or less per sq. mile” and has reported that 19.3% of the U. S. population is rural (e.g., see “How We Define Rural”, U. S. Health Resources and Services Administration, April 16, 2024: https: / / web.archive. Org / web / 20240416180605 / https: / / www. hrsa.gov / rural-health / about-us / what-is-rural). By this rural definition, 35* 700 sq. mi. = 24,500 people in a rural area that would be in a 48 km cell. Even if only 10% of people are mobile users, that is 2,450 users. Even larger satellites that have double the antenna size in each dimension would only halve the spot cell size to 24 km in diameter, or about 175 sq. mi. That is still 35 * 175 sq. mi. = 6,125 people, and at 10% mobile users, that is about 613 mobile users. When 75 Mbps capacity is shared equally among 613 active users, each user at cell-center gets 74 Mbps ÷ 613 = 122 kbps, and most users (at cell-middle or cell-edge) will be getting less than half that data rate, or less than 61 kbps. This is effectively no better than 1990s “dial-up” data rates (i.e., dial-up was 56 kbps or less), sufficient only for texting and voice. And, dial-up was adequate for early web sites in the 1990s, it is inadequate for modern websites that routinely include video streaming and high-resolution images. Even if we make even larger satellites, with each doubling their antennas in both dimensions again, we only double this extremely low data rate per user in rural areas. We are nowhere close to having useful data rates for user densities in suburban or urban areas, which are where more than 80% of the U. S. population resides.

[0130] Adding more LEO D2D beamforming satellites will increase the coverage areas served on the Earth’s surface but will not increase UE densification or data rate per user because per user data rate ultimately is limited by the enormous cell size dictated by physics limits of beamforming technology. Once the entire surface planet Earth is served, there will be no benefit in adding more satellites, and the final result will be dial-up speeds available in rural and remote areas, useful only for emergency services, texting, voice, but for little else that a mobile device user would want, and notuseful for many current popular internet services, let alone for internet services in the future.

[0131] This is why D2D services are only being offered in very, very remote areas. Elon Musk, CEO of SpaceX, owner of Starlink, recently acknowledged this is an inescapable “physics” limitation of D2D in a November 2025 interview. When asked about whether Starlink could one day work in densely populated areas, Musk said that “physics won't allow for that”... “Because you've got a satellite beam, which is a pretty big beam and you have a fixed number of users per beam.”... “Think of it as a flashlight, the cone is coming down to 550 km but not 1 km away. It's not physically possible for us to have Starlink to serve dense cities. It can serve 1 % or 2% of a densely populated city.” (Jayaraj, Prajwal, “Physics Won’t Allow: Elon Musk on Starlink for Densely Populated Areas”, NDTV, 30 November 2025, https: / / www.ndtvprofit.com / technology / physics-wont-allow-elon-musk-on-starlink-for-densely-populated-areas)

[0132] It’s important to note the Mr. Musk did not say it was a difficult, or even an infeasible, engineering challenge to achieve high enough data rates to offer LEO D2D services (or even Starlink direct-to-home data services) in non-rural areas: Mr. Musk stated, “physics won’t allow for that” and it is “not physically possible”, which means that in his assessment, it is not possible through any means because of an absolute physics limitation. Starlink currently has thousands of LEO satellites in orbit (far more satellites than any other company or country) providing LEO data services for both D2D and direct-to-home and Mr. Musk is a deeply technical CEO. Further, Mr. Musk is famously known for having virtually unlimited financial, business, and personnel resources to apply to difficult and large-scale engineering problems which he does not shirk away from if he believes them at all possible. And, finally, Mr. Musk would be highly motivated to find a solution that would overcome such severe LEO D2D data rate limitations given the advantages this would provide to Starlink and its parent company SpaceX. As such, Mr. Musk is arguably one of the most skilled people, if not the most skilled person, on Earth to make this assessment. In short, Mr. Musk’s remarks confirm that it is far from obvious that it is possible to dramatically increase the capacity and density of D2D satellites beyond the current cell-centric beamforming technology in use today by Starlink, AST SpaceMobile and others.

[0133] LEO D2D beamforming technology suffers from other significant limitations. Since there can only be one LEO transmitting to one cell on the ground atonce, that means that each UE is only served by a single satellite. If there are any overhead obstacles, such as trees, buildings, hills, or mountains blocking a view to that single satellite, then the UE will likely lose its link to the satellite. In fact, since LEO satellites are constantly moving across the sky as they orbit, a stationary UE may have a link with a satellite that it loses when the satellite’s orbit moves it behind an obstacle. This results in very inconsistent service.

[0134] Mobile spectrum is very limited, and it is highly desirable (and sometimes essential) for terrestrial spectrum owners such as mobile network operators (“MNOs”) to be able to use the same spectrum for D2D service. D2D cell-centric beamforming transmissions would interfere with terrestrial spectrum use, so to avoid such interference, D2D cell-centric beamforming transmissions must be geofenced so they do not transmit anywhere that terrestrial spectrum is used. D2D cell-centric beamforming can only “turn off” beams for geofencing at the resolution of the narrowest beam that can be formed, which as noted above, are typically on the order of 10s of km. This effectively means that cell-centric D2D service is limited to areas that are at least 10s of km away from the closest terrestrial mobile network using the same spectrum. This is a very significant limitation because even very remote areas often have small regions of terrestrial mobile service (e.g., highways going through them with mobile service, or ski resorts with mobile service on the ski slopes) and D2D geofencing will limit satellite service to be 10s of km away from any small patch of mobile service. It would be far more useful for mobile users to have D2D service immediately be available when small regions of terrestrial service fall out of range (e.g., when a user exits off a rural highway or leaves a ski resort), but the giant D2D beamforming spots make this impractical or impossible.

[0135] Clearly, there is a long-felt but unmet need for D2D technology that provides service in rural, suburban, urban regions with sufficient per-user data rates to support today’s popular internet services and websites, that is scalable to support future higher data rate services, that is able to operate consistently despite overhead obstacles partially obscuring the sky, and that is able to use terrestrial spectrum in regions where the spectrum is also used to provide terrestrial service without disrupting the use of that terrestrial service.SUMMARY OF THE INVENTION

[0136] The present disclosure relates generally to wireless communications, and more particularly to systems and methods for direct-to-device satellite communications using distributed spatial processing.

[0137] According to an exemplary embodiment of the present invention, a system for direct-to-device satellite communications comprises: a centralized processor coupled to a network and configured to receive a plurality of data streams intended for a plurality of user equipment (UE) devices located in a coverage area on a surface of a celestial body. The system further comprises a plurality of satellites in orbit above the coverage area, each satellite comprising at least one antenna and coupled to the centralized processor. The centralized processor is configured to obtain channel state information (CSI) characterizing a radio frequency (RF) channel between each of the plurality of UE devices and the at least one antenna of the plurality of satellites; compute precoding weights based on the obtained CSI for the plurality of UE devices; and generate a plurality of precoded waveforms by applying the computed precoding weights to the plurality of data streams. The plurality of satellites are configured to cooperatively transmit the plurality of precoded waveforms such that the precoded waveforms combine coherently at the location of each of the plurality of UE devices to form a plurality of independent RF channels, wherein each independent RF channel delivers a distinct data stream to a corresponding UE device.

[0138] In some embodiments, the RF channel operates in a Frequency Division Duplex (FDD) mode. In other embodiments, the RF channel operates in a Time Division Duplex (TDD) mode.

[0139] In certain embodiments, the centralized processor is configured to obtain the CSI by exploiting uplink / downlink channel reciprocity. In particular embodiments, obtaining the CSI comprises receiving an uplink (UL) sounding signal from each of the plurality of UE devices. Notably, in some configurations, the UL sounding signal occupies a bandwidth that is either a full bandwidth of the RF channel or a subband bandwidth that is narrower than the full bandwidth, and the centralized processor is configured to derive the CSI for the full bandwidth of the RF channel based on the UL sounding signal. The UL sounding signal may be a 3rd Generation Partnership Project (3GPP) Sounding Reference Signal (SRS).

[0140] According to an exemplary embodiment of the present invention, a method for providing direct-to-device satellite communications comprises: receiving, at a centralized processor coupled to a network, a plurality of data streams intended for aplurality of user equipment (UE) devices located in a coverage area on a surface of a celestial body. The method further comprises obtaining, by the centralized processor, channel state information (CSI) characterizing a radio frequency (RF) channel between each of the plurality of UE devices and at least one antenna of each of a plurality of satellites orbiting above the coverage area. The method includes computing, by the centralized processor, precoding weights based on the obtained CSI for the plurality of UE devices; and generating, by the centralized processor, a plurality of precoded waveforms by applying the computed precoding weights to the plurality of data streams. The method further comprises cooperatively transmitting, by the plurality of satellites, the plurality of precoded waveforms such that the precoded waveforms combine coherently at the location of each of the plurality of UE devices to form a plurality of independent RF channels, wherein each independent RF channel delivers a distinct data stream to a corresponding UE device.

[0141] In some embodiments of the method, the RF channel operates in a Frequency Division Duplex (FDD) mode, while in others it operates in a Time Division Duplex (TDD) mode. The step of obtaining the CSI may comprise exploiting uplink / downlink channel reciprocity. Furthermore, obtaining the CSI may comprise receiving an uplink sounding signal from each of the plurality of UE devices. In specific embodiments, this involves receiving an uplink (UL) sounding signal that occupies a subband bandwidth narrower than the full bandwidth of the RF channel and deriving the CSI for the full bandwidth of the RF channel based on that UL sounding signal.

[0142] According to an exemplary embodiment of the present invention, a non-transitory computer-readable medium is provided. The medium stores instructions that, when executed by one or more processors of a centralized processor coupled to a network, cause the centralized processor to perform operations comprising: receiving a plurality of data streams intended for a plurality of user equipment (UE) devices located in a coverage area on a surface of a celestial body; obtaining channel state information (CSI) characterizing a radio frequency (RF) channel between each of the plurality of UE devices and at least one antenna of each of a plurality of satellites orbiting above the coverage area; computing precoding weights based on the obtained CSI for the plurality of UE devices; and generating a plurality of precoded waveforms by applying the computed precoding weights to the plurality of data streams. The precoded waveforms are configured to be cooperatively transmitted by the plurality of satellites such that they combine coherently at the location of each of the plurality ofUE devices to form a plurality of independent RF channels, wherein each independent RF channel delivers a distinct data stream to a corresponding UE device.BRIEF DESCRIPTION OF THE DRAWINGS

[0143] A better understanding of the present disclosure can be obtained from the following detailed description in conjunction with the drawings, in which:

[0144] FIG. 1 illustrates multiplexing and diversity regions for a macro-cell and a small-cell.

[0145] FIG. 2A illustrates full frequency reuse pattern in conventional cellular systems.

[0146] FIG. 2B illustrates hard frequency reuse (HFR) pattern in conventional cellular systems.

[0147] FIG. 2C illustrates fractional frequency reuse (FFR) pattern in conventional cellular systems.

[0148] FIG. 3 illustrates the interference region between adjacent macro-cells.

[0149] FIG. 4 illustrates multiple BTSs transmitting at higher power to increase the level of interference between cells.

[0150] FIG. 5 illustrates one example where many access points are added to deliberately increase the level of incoherent interference throughout the cell.

[0151] FIG. 6 illustrates the network elements in LTE networks.

[0152] FIG. 7A illustrates the LTE frame structure for FDD operation.

[0153] FIG. 7B illustrates the LTE frame structure for TDD operation.

[0154] FIG. 8A illustrates the LTE “resource elements” and “resource blocks” in the OFDM DL channel.

[0155] FIG. 8B illustrates the LTE “resource elements” and “resource blocks” in the SC-FDMA UL channel.

[0156] FIG. 9 illustrates one embodiment of a multi-user (MU) multiple antenna system (MAS), or MU-MAS, made up of antenna-clusters and user-clusters.

[0157] FIG. 10 illustrates one embodiment of a MU-MAS wherein a different cell ID is associated to every antenna-subcluster.

[0158] FIG. 11 illustrates one embodiment of a MU-MAS wherein the same set of cell IDs are assigned to the antenna-subclusters with given repetition pattern.

[0159] FIG. 12 illustrates the SNR distribution for practical deployment of MU-MAS systems in downtown San Francisco, CA, with sparsely and densely populated areas.

[0160] FIG. 13 illustrates one embodiment of a MU-MAS made up of CP, distributed BTSs and multiple UEs.

[0161] FIG. 14 illustrates one embodiment of a MU-MAS made up of CP, distributed BTSs, multiple devices and one UE connected to the devices as well as the BTSs via network interfaces.

[0162] FIG. 15 illustrates one embodiment of a MU-MAS wherein the UE is in a case that physically attaches to the user device.

[0163] FIG. 16 illustrates one embodiment of a MU-MAS wherein the distributed antennas communicate to the UEs via the UL and DL channels.

[0164] FIG. 17 illustrates one embodiment of a MU-MAS wherein the distributed antennas communicate to the beacon via the UL and DL channels.

[0165] FIG. 18 illustrates the symbol error rate (SER) performance of the MU-MAS with linear precoding with / without RF mismatch and with / without RF calibration.

[0166] FIG. 19 illustrates the symbol error rate (SER) performance of the MU-MAS with linear and non-linear precoding with / without RF mismatch and with / without RF calibration.

[0167] FIGS. 20A-20B illustrates the 4-QAM constellations at the UEs (before modulo operation) when applying THP non-linear precoding.

[0168] FIG. 21 illustrates the general framework of the Radio Access Network (RAN);

[0169] FIGS. 22A-22B illustrate the protocol stack of the Virtual Radio Instance (VRI) consistent to the OSI model and LTE standard;

[0170] FIG. 23 illustrates adjacent RANs to extend coverage in DIDO wireless networks;

[0171] FIG. 24 illustrates handoff between RAN and adjacent wireless networks;

[0172] FIG. 25 illustrates handoff between RAN and LTE cellular networks;

[0173] FIG. 26 illustrates one embodiment of DIDO-OFDM systems with I / Q compensation;

[0174] FIG. 27 illustrates an embodiment of the DIDO transmitter with I / Q compensation functional units;

[0175] FIG. 28 a DIDO receiver with I / Q compensation functional units;

[0176] FIG. 29 illustrates one embodiment of DIDO 2 x 2 performance with and without I / Q compensation;

[0177] FIG. 30 illustrates one embodiment of DIDO 2 x 2 performance with and without l / Q compensation; and

[0178] FIG. 31 illustrates one embodiment of the SER (Symbol Error Rate) with and without l / Q compensation for different QAM constellations;

[0179] FIG. 32 illustrates one embodiment of DIDO 2 x 2 performances with and without compensation in different user device locations;

[0180] FIG. 33 illustrates one embodiment of the SER with and without l / Q compensation in ideal (i.i.d. (independent and identically-distributed)) channels;

[0181] FIG. 34 illustrates one embodiment of a method of adaptive DIDO-OFDM;

[0182] FIG. 35 illustrates the performance of different order DIDO systems;

[0183] FIG. 36 illustrates one embodiment of the DIDO 2 x 2 performance with 4- QAM and FEC rate 1 / 2 as function of the user device location;

[0184] FIG. 37 illustrates one embodiment of a transmitter framework of adaptive DIDO systems;

[0185] FIG. 38 illustrates one embodiment of the SER with and without l / Q compensation in ideal (i.i.d. (independent and identically-distributed)) channels;

[0186] FIG. 39 illustrates one embodiment of the antenna layout for DIDO measurements; and

[0187] FIG. 40 illustrates one embodiment of a receiver framework of adaptive DIDO systems.

[0188] FIG. 41 is prior art showing voice and non-voice data utilization of mobile spectrum from 2007-2013.

[0189] FIG. 42 is prior art showing mobile data traffic share by application type in 2012.

[0190] FIG. 43 is a prior art comparison of FDD LTE and TDD LTE modes of operations

[0191] FIG.44 illustrates a new TDD network concurrently using UL spectrum with an existing FDD network

[0192] FIG. 45 is a prior art chart of TDD LTE duplex configurations

[0193] FIG.46 illustrates a new TDD network concurrently using DL spectrum with an existing FDD network

[0194] FIG. 47 illustrates two new TDD networks concurrently using UL and DL spectrum with an existing FDD network

[0195] FIG. 48 illustrates a new FDD network concurrently using UL and DL spectrum with an existing FDD network

[0196] FIG.49 illustrates a RAN that synthesizes null pCells at the location of base station antennas.

[0197] FIGS. 50A, 50B, 50C, and 50D illustrate various propagation scenarios between base station antennas.

[0198] FIGS. 51 A and 51 B are prior art diagrams of allocations of the 2500-2690 MHz band in different regions as either FDD and TDD or only as TDD.

[0199] FIGS. 52A, 52B, and 52C illustrate various configurations of the pCell vRAN system coupled to low earth orbital satellites and terrestrial base stations and providing direct-to-device mobile wireless service to mobile devices.

[0200] FIGS. 53A and 53B compare direct-to-device satellite cellular with direct-to-device pCell capacity and user throughput.

[0201] FIGS. 54A and 54B compare direct-to-device satellite cellular with direct-to-device pCell uplink antenna gain.

[0202] FIGS. 55A and 55B compare direct-to-device satellite cellular with direct-to-device pCell antenna diversity gain.

[0203] FIG. 56 illustrates how direct-to-device satellite pCell supports interference mitigation.

[0204] FIG. 57 illustrates how pCell supports TDD and FDD bands, and provides a carrier aggregation example.

[0205] FIG. 58A illustrates a direct-to-device satellite communication system with two satellites whose beams overlap the same coverage area on the ground.

[0206] FIG. 58B illustrates in accordance with embodiments of the present invention pCell supporting direct-to-device satellite communication with two satellites whose beams overlap the same coverage area on the ground.

[0207] FIG.59 illustrates in accordance with embodiments of the present invention uplink signals received through different satellite beams incurring different satellitebeam dependent delays relative to the coverage area center.

[0208] FIG.60 illustrates in accordance with embodiments of the present invention the PRACH Detection and Delay Estimation unit.

[0209] FIG.61 illustrates in accordance with embodiments of the present invention how the PRACH Detection and Delay Estimation unit performs the detection task.

[0210] FIG.62 illustrates in accordance with embodiments of the present invention SRS Detection, CSI and Delay Estimation unit.

[0211] FIG.63 illustrates in accordance with embodiments of the present invention pCell processing that makes use of linear DL precoding showing how one-way delay compensation operations are required in each UE-satellite beam branch.

[0212] FIG.64 illustrates in accordance with embodiments of the present invention pCell processing that makes use of linear DL precoding assuming that channel coherence bandwidth exceeds the system bandwidth and thus one delay-free DL weight matrix applies to the entire system bandwidth.

[0213] FIG.65 illustrates in accordance with embodiments of the present invention pCell processing that makes use of linear DL precoding and application in the time domain of DL precoding weight coefficients that are not constant over the entire system bandwidth.

[0214] FIG.66 illustrates in accordance with embodiments of the present invention pCell processing that assumes that the channel coherence bandwidth is larger than the system bandwidth and that makes use of linear UL precoding showing specifically how round-trip compensation operations are required in each satellite beam-UE branch.

[0215] FIG. 67 illustrates the structure of each TEQ instance, where the inputted unequalized time domain signal first passes through an all-pass Feedforward Equalizer that turns the overall system response into a minimum phase response and subsequently through a Feedback Equalizer that cancels post-cursor replicas.

[0216] FIG.68 illustrates in accordance with embodiments of the present invention the Time Domain Equalizer structure in the case where the magnitude of g1is larger than the magnitude of g2and ZIT is positive.

[0217] FIG.69 illustrates in accordance with embodiments of the present invention the pCell processing that makes use of transmit pre-emphasis (TPE) units, linear DL precoding, and application in the time domain of DL precoding weights that are constant over the system bandwidth.

[0218] FIG. 70 illustrates the structure of each transmit pre-emphasis (TPE) instance where a UE time-domain input signal is passed through a feed-forward emphasis unit and then a feedback emphasis unit to output the pre-emphasized UE signal.

[0219] FIG.71 illustrates in accordance with embodiments of the present invention the pCell processing that makes use of transmit pre-emphasis (TPE) units, linear DL precoding, and application in the time domain of DL precoding weights that are not constant over the system bandwidth.

[0220] FIG. 72 illustrates the change of distance between a UE and a satellite in a UE-satellite pair for a satellite having speed v in an inertial reference frame where the UE is at rest at the beginning of the period of time of length AT.

[0221] FIG.73 illustrates in accordance with embodiments of the present invention the DL pCell processing showing routing and delay units for the control and alignment of DL broadcast waveform with UE-specific DL waveforms.

[0222] FIG. 74 illustrates the variations over time of the select signal controlling DL broadcast waveform routing and of the signals controlling UE-specific delay elements to implement a seamless and continuous “anchor” satellite switching procedure.

[0223] FIG. 75 illustrates the evolution over time of the sets Sat(FoV 0)), ActiveSat(FoVi(0)), AnchorSat(Fo\Ai(0)) for Coverage Area A and the select signal controlling DL broadcast waveform routing.

[0224] FIG.76 illustrates in accordance with embodiments of the present invention where a geostationary satellite serves as “anchor” satellite and transmits broadcast signals to UE devices on the Earth’s surface while lower-orbit satellites serve to relay data to and from a joint coverage volume.

[0225] FIG. 77A illustrates in accordance with embodiments of the present invention a pCell satellite direct-to-device communication system that permits coexistence and joint operation with a terrestrial system where the same frequency band is partially or entirely shared between the pCell system UL transmissions and the terrestrial system DL transmissions.

[0226] FIG. 77B illustrates in accordance with embodiments of the present invention a pCell satellite direct-to-device communication system that permits coexistence and joint operation with a terrestrial system where the same frequency band is partially or entirely shared between the pCell system DL transmissions and the terrestrial system UL transmissions.

[0227] FIG. 78 illustrates certain elements of an orbital communications satellite.

[0228] FIG. 79A illustrates a direct-to-device satellite communication system with one satellite creating beam spots on the ground.

[0229] FIG. 79B illustrates a direct-to-device satellite communication system with two satellites creating beam spots on the ground.

[0230] FIG. 79C illustrates a direct-to-device satellite communication system with a satellite using beamforming to create spot beam cell shapes that vary at different elevations on the surface of the Earth.

[0231] FIG. 79D illustrates in accordance with embodiments of the present invention a direct-to-device satellite communication system with a satellite using precoding to create user-centric CINR regions of independent channels per UE with arbitrary shapes on the surface of the Earth.

[0232] FIG. 80 illustrates an idealized fixed hexagonal cellular pattern on the ground in a coverage area with UEs.

[0233] FIG. 81 illustrates an idealized fixed hexagonal cellular pattern overlaid with a circular beam spot pattern on the ground in a coverage area with UEs.

[0234] FIG. 82 illustrates a fixed circular beam spot pattern on the ground in a coverage area with UEs.

[0235] FIG. 83 illustrates a fixed circular and elliptical beam spot pattern on the ground in a coverage area with UEs.

[0236] FIG. 84 illustrates a dynamic circular and elliptical beam spot pattern on the ground in a coverage area with UEs.

[0237] FIG. 85 illustrates a precoded channel pattern on the ground in a coverage area with UEs.

[0238] FIG. 86 illustrates a fixed circular beam spot pattern on the ground in a coverage area with two cohorts of UEs.

[0239] FIG. 87 illustrates a fixed circular and elliptical beam spot pattern on the ground in a coverage area with two cohorts of UEs.

[0240] FIG. 88A illustrates a dynamic circular and elliptical beam spot pattern on the ground in a coverage area with two cohorts of UEs.

[0241] FIG. 88B illustrates a dynamic circular and elliptical beam spot pattern on the ground in a coverage area with the first of two cohorts of UEs.

[0242] FIG. 88C illustrates a dynamic circular and elliptical beam spot pattern on the ground in a coverage area with the second of two cohorts of UEs.

[0243] FIG. 89A illustrates a precoded channel pattern on the ground in a coverage area with three cohorts of UEs.

[0244] FIG. 89B illustrates a precoded channel pattern on the ground in a coverage area with a first pair of three cohorts of UEs.

[0245] FIG. 89C illustrates a precoded channel pattern on the ground in a coverage area with a second pair of three cohorts of UEs.

[0246] FIG. 90 illustrates a map of the United States showing how most of the surface area has low population density.

[0247] FIG. 91 illustrates an arrangement of UEs in a coverage area in one trial among many trials of a Monte Carlo simulation of a satellite antenna array.

[0248] FIG. 92 illustrates, for a given arrangement of UEs, that the numerical rank of the CSI matrix is determined by computing the CSI matrix singular values and then counting the number of such singular values greater than a threshold.

[0249] FIG. 93A shows two histograms of Monte Carlo trials of the arrangement of UEs in a coverage area showing the number of simultaneously active beam cell channels and the number of simultaneously active precoded channels.

[0250] FIG. 93B shows for a Monte Carlo simulation the histogram of the ratio of the number of simultaneously active precoded channels to the number of simultaneously active beam cell channels for each arrangement of UEs in a coverage area.

[0251] FIG. 94 show prior art direct-to-device satellite parameters from a public FCC filing.

[0252] FIG. 95 is a chart comparing satellite capacity results from simulating single-satellite prior art cell-centric beamforming and embodiments of the present invention of user-centric precoding at a minimum 35° elevation angle.

[0253] FIG. 96 is a chart comparing per-user capacity results from simulating single-satellite prior art cell-centric beamforming and embodiments of the present invention of user-centric precoding at a minimum 35° elevation angle.

[0254] FIG. 97 is a chart comparing satellite capacity results from simulating single-satellite prior art cell-centric beamforming and embodiments of the present invention of user-centric precoding at a minimum 20° elevation angle.

[0255] FIG. 98 is a chart comparing satellite capacity per-user results from simulating single-satellite prior art cell-centric beamforming and embodiments of the present invention of user-centric precoding at a minimum 20° elevation angle.

[0256] FIG. 99 shows prior art direct-to-device satellite parameters from a public FCC filing used for 35° elevation simulations.

[0257] FIG. 100 shows prior art ideal satellite beam cell layouts showing 460 cells and 460 UE locations from a Monte Carlo trial used for 35° elevation simulations.

[0258] FIG. 101 shows receive power heat maps for a Monte Carlo trial of 35° elevation minimum elevation satellite transmission simulations comparing (a) prior art cell-centric beamforming with 460 UEs in 460 prior art cells with beam hopping, and (b) an embodiment of user-centric precoding of a cohort of 415 UEs out of 460 UEs.

[0259] FIG. 102 shows Cl NR heat maps for a Monte Carlo trial of 35° elevation minimum elevation satellite transmission simulations comparing (a) prior art cellcentric beamforming with 460 UEs in 460 prior art cells with beam hopping, and (b) an embodiment of user-centric precoding of a cohort of 415 UEs out of 460 UEs.

[0260] FIG. 103 shows prior art ideal satellite beam cell layouts showing 460 cells and 3,680 UE locations from a Monte Carlo trial used for 35° elevation simulations.

[0261] FIGS. 104A and 104B show receive power heat maps for a Monte Carlo trial of 35° elevation minimum elevation satellite transmission simulations comparing (a) prior art cell-centric beamforming with 3,680 UEs in 460 prior art cells, and (b) an embodiment of user-centric precoding of a cohort of 1,985 UEs out of 3,680 UEs. FIG.104A shows UE locations and FIG. 104B does not.

[0262] FIGS. 105A and 105B shows CINR heat maps for a Monte Carlo trial of 35° elevation minimum elevation satellite transmission simulations comparing (a) prior art cell-centric beamforming with 3,680 UEs in 460 prior art cells, and (b) an embodiment of user-centric precoding of a cohort of 1,985 UEs out of 3,680 UEs. FIG.105A shows UE locations and FIG. 105B does not.

[0263] FIGS. 105C and 105D show 3D CINR charts of low and high elevation regions, respectively, of the prior art cell-centric beamforming heat map of FIG. 105A.

[0264] FIGS. 105E and 105F show 3D CINR charts of low and high elevation regions, respectively, of an embodiment of the user-centric precoding heat map of FIG. 105A.

[0265] FIG. 106 shows receive power heat maps for a Monte Carlo trial of 35° elevation minimum elevation satellite transmission simulations with geofencing comparing (a) prior art cell-centric beamforming with 3,494 UEs in 460 prior art cells, and (b) an embodiment of user-centric precoding of a cohort of 1,870 UEs out of 3,494 UEs.

[0266] FIG. 107 shows prior art ideal satellite beam cell layouts showing 460 cells and 14,720 UE locations from a Monte Carlo trial used for 35° elevation simulations.

[0267] FIGS. 108A and 108B show receive power heat maps for a Monte Carlo trial of 35° elevation minimum elevation satellite transmission simulations comparing (a) prior art cell-centric beamforming with 14,720 UEs in 460 prior art cells, and (b) an embodiment of user-centric precoding of a cohort of 3,585 UEs out of 14,720 UEs.FIG. 108A shows UE locations and FIG. 108B does not.

[0268] FIGS. 109A and 109B shows CINR heat maps for a Monte Carlo trial of 35° elevation minimum elevation satellite transmission simulations comparing (a) prior art cell-centric beamforming with 14,720 UEs in 460 prior art cells, and (b) an embodiment of user-centric precoding of a cohort of 3,585 UEs out of 14,720 UEs.FIG. 109A shows UE locations and FIG. 109B does not.

[0269] FIG. 110 shows a receive power heat map for a Monte Carlo trial of 35° elevation minimum elevation satellite transmission simulations with geofencing of an embodiment of user-centric precoding of a cohort of 3,388 UEs out of 13,951 UEs.

[0270] FIG. 111 shows prior art direct-to-device satellite parameters from a public FCC filing used for 20° elevation simulations.

[0271] FIG. 112 shows prior art ideal satellite beam cell layouts showing 1,755 cells and 1,755 UE locations from a Monte Carlo trial used for 20° elevation simulations.

[0272] FIG. 113 shows receive power heat maps for a Monte Carlo trial of 20° elevation minimum elevation satellite transmission simulations comparing (a) prior art cell-centric beamforming with 1,755 UEs in 1,755 prior art cells with beam hopping, and (b) an embodiment of user-centric precoding of a cohort of 1, 194 UEs out of 1,755 UEs.

[0273] FIG. 114 shows CINR heat maps for a Monte Carlo trial of 20° elevation minimum elevation satellite transmission simulations comparing (a) prior art cellcentric beamforming with 1,755 UEs in 1,755 prior art cells with beam hopping, and (b) an embodiment of user-centric precoding of a cohort of 1,194 UEs out of 1,755 UEs.

[0274] FIG. 115 shows a receive power heat map for a Monte Carlo trial of 20° elevation minimum elevation satellite transmission simulations with geofencing of an embodiment of user-centric precoding of a cohort of 1,129 UEs out of 1,668 UEs.

[0275] FIG. 116 shows prior art ideal satellite beam cell layouts showing 1,755 cells and 14,040 UE locations from a Monte Carlo trial used for 20° elevation simulations.

[0276] FIG. 117 shows receive power heat maps for a Monte Carlo trial of 20° elevation minimum elevation satellite transmission simulations comparing (a) prior art cell-centric beamforming with 14,040 UEs in 1,755 prior art cells, and (b) an embodiment of user-centric precoding of a cohort of 3,899 UEs out of 14,040 UEs.

[0277] FIG. 118 shows CINR heat maps for a Monte Carlo trial of 20° elevation minimum elevation satellite transmission simulations comparing (a) prior art cellcentric beamforming with 14,040 UEs in 1,755 prior art cells, and (b) an embodiment of user-centric precoding of a cohort of 3,899 UEs out of 14,040 UEs.

[0278] FIG. 119 shows a receive power heat map for a Monte Carlo trial of 20° elevation minimum elevation satellite transmission simulations with geofencing of an embodiment of user-centric precoding of a cohort of 3,642 UEs out of 13,146 UEs.

[0279] FIG. 120 shows prior art ideal satellite beam cell layouts showing 1,755 cells and 28,080 UE locations from a Monte Carlo trial used for 20° elevation simulations.

[0280] FIG. 121 shows receive power heat maps for a Monte Carlo trial of 20° elevation minimum elevation satellite transmission simulations comparing (a) prior art cell-centric beamforming with 28,080 UEs in 1,755 prior art cells, and (b) an embodiment of user-centric precoding of a cohort of 5,005 UEs out of 28,080 UEs.

[0281] FIG. 122 shows CINR heat maps for a Monte Carlo trial of 20° elevation minimum elevation satellite transmission simulations comparing (a) prior art cellcentric beamforming with 28,080 UEs in 1,755 prior art cells, and (b) an embodiment of user-centric precoding of a cohort of 5,005 UEs out of 28,080 UEs.

[0282] FIG. 123 shows enlarged CINR heat maps from FIGS. 105A and 105E.

[0283] FIG. 124 illustrates in accordance with embodiments of the present invention an elevation view of beam-partitioned satellite broadcasts.

[0284] FIG. 125 illustrates in accordance with embodiments of the present invention an elevation view and a plan view of satellite coverage area beam partitioning.

[0285] FIG. 126 shows in accordance with embodiments of the present invention downlink propagation delay and round-trip time.

[0286] FIG. 127 shows in accordance with embodiments of the present invention inter- and intra-beam round-trip time variations.

[0287] FIG. 128 shows a graph of the round-trip-delay variations when, for each beam spots, one point on its boundary is time-aligned with the edge of a beam spot closest to the center of coverage area.

[0288] FIG. 129 illustrates examples of how RTT delays impact the alignment of DL and UL subframes in a TDD band.

[0289] FIGS.130A-130C illustrate in accordance with embodiments of the present invention overlapping UL and DL signals in a TDD band.

[0290] FIGS.131 A-131 C illustrate in accordance with embodiments of the present invention the impact of RTT delays on the alignment of DL and UL data and SRS in a TDD band.Detailed Description

[0291] One solution to overcome many of the above prior art limitations are embodiments of Distributed-Input Distributed-Output (DIDO) technology, currently marketed as Artemis pCell® wireless technology. DIDO / pCell technology is described in the following patents and patent applications, all of which are assigned to the assignee of the present patent and the contents of which are incorporated herein by reference in their entirety for all purposes. These patents and applications are sometimes referred to collectively herein as the “Related Patents and Applications”:

[0292] U. S. Provisional Application No. 63 / 753,537, filed February 4, 2025, entitled “Systems and Methods for Direct to Device Satellite Communications”

[0293] U. S. Provisional Application No. 63 / 780,846, filed March 31, 2025, entitled “Systems and Methods for Direct to Device Satellite Communications”

[0294] U. S. Provisional Application No. 63 / 806,300, filed May 15, 2025, entitled “Systems and Methods for Direct to Device Satellite Communications”

[0295] U. S. Provisional Application No. 63 / 882,716, filed Sep. 16, 2025, entitled “Systems and Methods for Direct to Device Satellite Communications”

[0296] U. S. Patent No. 12,537,580, issued Jan. 27, 2026, entitled, “System and Methods for Exploiting Inter-Cell Multiplexing Gain in Wireless Cellular Systems Via Distributed Input Distributed Output Technology”;

[0297] U. S. Patent No. 12,470,941, issued Oct. 29, 2025, entitled “System And Method For Concurrent Spectrum Usage within Actively Used Spectrum”;

[0298] U. S. Patent No. 12,355,520, issued July 8, 2025, entitled “System and Methods for Radio Frequency Calibration Exploiting Channel Reciprocity in Distributed Input Distributed Output Wireless Communications”;

[0299] U. S. Patent No. 12,355,519, issued July 8, 2025, entitled “System and Methods for Radio Frequency Calibration Exploiting Channel Reciprocity in Distributed Input Distributed Output Wireless Communications”;

[0300] U. S. Patent No. 12,341,582, issued June 24, 2025, entitled “System And Method For Mitigating Interference within Actively Used Spectrum”;

[0301] U. S. Patent No. 12,244,369, issued March 4, 2025, entitled “System and Methods for Radio Frequency Calibration Exploiting Channel Reciprocity in Distributed Input Distributed Output Wireless Communications”;

[0302] U. S. Patent No. 12,237,888, issued Feb. 25, 2025, entitled “System and Methods for Radio Frequency Calibration Exploiting Channel Reciprocity in Distributed Input Distributed Output Wireless Communications”;

[0303] U. S. Patent No. 12,224,819, issued Feb. 11, 2025, entitled “System and Methods for Radio Frequency Calibration Exploiting Channel Reciprocity in Distributed Input Distributed Output Wireless Communications”;

[0304] U. S. Patent No. 12,170,401, issued Dec. 17, 2024, entitled “System And Method For Distributing Radioheads”;

[0305] U. S. Patent No. 12,166,546, issued Dec. 10, 2024, entitled “System and Methods for Radio Frequency Calibration Exploiting Channel Reciprocity in Distributed Input Distributed Output Wireless Communications”;

[0306] U. S. Patent No. 12,166,280, issued Dec. 10, 2024, entitled “System And Method For Distributing Radioheads”;

[0307] U. S. Patent No. 11,923,931, issued March 5, 2024, entitled “System and Method For Distributed Antenna Wireless Communications”;

[0308] U. S. Patent No. 11,901,992, issued Feb. 13, 2024, entitled “Systems And Methods For Exploiting Inter-Cell Multiplexing Gain In Wireless Cellular Systems Via Distributed Input Distributed Output Technology”;

[0309] U. S. Patent No. 11,818,604, issued Nov. 14, 2023, entitled “Systems And Methods For Exploiting Inter-Cell Multiplexing Gain In Wireless Cellular Systems Via Distributed Input Distributed Output Technology”;

[0310] U. S. Patent No. 11,646,773, issued May 9, 2023, entitled “System and Method For Distributed Antenna Wireless Communications”;

[0311] U. S. Patent No. 11,581,924, issued Feb. 14, 2023, entitled “System and Methods for Radio Frequency Calibration Exploiting Channel Reciprocity in Distributed Input Distributed Output Wireless Communications”;

[0312] U. S. Patent No. 11,451,281, issued September 20, 2022, entitled “Systems And Methods For Exploiting Inter-Cell Multiplexing Gain In Wireless Cellular Systems Via Distributed Input Distributed Output Technology”;

[0313] U. S. Patent No. 11,451,275, issued September 20, 2022, entitled “System and Method For Distributed Antenna Wireless Communications”;

[0314] U. S. Patent No. 11,394,436, issued July 19, 2022, entitled “System and Method For Distributed Antenna Wireless Communications”;

[0315] U. S. Patent No. 11,309,943, issued April 19, 2022, entitled “System and Methods for Planned Evolution and Obsolescence of Multiuser Spectrum”;

[0316] U. S. Patent No. 11,290,162, issued March 29, 2022, entitled “System And Method For Mitigating Interference within Actively Used Spectrum”;

[0317] U. S. Patent No. 11,196,467, issued December 7, 2021, entitled “System and Method For Distributed Antenna Wireless Communications”;

[0318] U. S. Patent No. 11,190,947, issued Nov. 30, 2021, entitled “System And Method For Concurrent Spectrum Usage within Actively Used Spectrum”;

[0319] U. S. Patent No. 11,190,247, issued November 30, 2021, entitled “System and Method For Distributed Antenna Wireless Communications”;

[0320] U. S. Patent No. 11,190,246, issued November 30, 2021, entitled “System and Method For Distributed Antenna Wireless Communications”;

[0321] U. S. Patent No. 11,189,917, filed Nov. 30, 2021, entitled “System And Method For Distributing Radioheads”;

[0322] U. S. Patent No. 11,146,313, issued October 12, 2021, entitled “System and Methods for Radio Frequency Calibration Exploiting Channel Reciprocity in Distributed Input Distributed Output Wireless Communications”;

[0323] U. S. Patent No. 11,070,258, issued July 20, 2021, entitled “System and Methods for Planned Evolution and Obsolescence of Multiuser Spectrum”;

[0324] U. S. Patent No. 11,050,468, issued June 29, 2021, entitled “System And Method For Mitigating Interference within Actively Used Spectrum”;

[0325] U. S. Patent No. 10,985,811, issued April 20, 2021, entitled “System and Method For Distributed Antenna Wireless Communications”;

[0326] U. S. Patent No. 10,886,979, issued Jan. 4, 2021, entitled “System And Method For Link adaptation In DIDO Multicarrier Systems”;

[0327] U. S. Patent No. 10,848,225, issued Nov. 24, 2020, entitled “Systems And Methods For Exploiting Inter-Cell Multiplexing Gain In Wireless Cellular Systems Via Distributed Input Distributed Output Technology”;

[0328] U. S. Patent No. 10,749,582, issued Aug. 18, 2020, entitled “Systems and Methods to Coordinate Transmissions in Distributed Wireless Systems via User Clustering”;

[0329] U. S. Patent No. 10,727,907, issued July 28, 2020, entitled “System and Methods to Enhance Spatial Diversity in Distributed-Input Distributed-Output Wireless Systems”;

[0330] U. S. Patent No. 10,547,358, issued Jan. 28, 2020, entitled “System and Methods for Radio Frequency Calibration Exploiting Channel Reciprocity in Distributed Input Distributed Output Wireless Communications”;

[0331] U. S. Patent No. 10,425,134, issued Sep. 24, 2019, entitled “System and Methods for Planned Evolution and Obsolescence of Multiuser Spectrum”;

[0332] U. S. Patent No. 10,349,417, issued July 9, 2019, entitled “System and Methods to Compensate for Doppler Effects in Distributed-Input Distributed Output Systems”;

[0333] U. S. Patent No. 10,333,604, issued, June 25, 2019, entitled “System and Method For Distributed Antenna Wireless Communications”;

[0334] U. S. Patent No. 10,320,455, issued June 11, 2019, entitled “Systems and Methods to Coordinate Transmissions in Distributed Wireless Systems via User Clustering”;

[0335] U. S. Patent No. 10,277,290, issued April 30, 2019, entitled “Systems and Methods to Exploit Areas of Coherence in Wireless Systems”;

[0336] U. S. Patent No. 10,243,623, issued March 26, 2019, entitled “System and Methods to Enhance Spatial Diversity in Distributed-Input Distributed-Output Wireless Systems”;

[0337] U. S. Patent No. 10,200,094, issued Feb. 5, 2019, entitled “Interference Management, Handoff, Power Control And Link Adaptation In Distributed-Input Distributed-Output (DIDO) Communication Systems”;

[0338] U. S. Patent No. 10,194,346, issued Jan. 29, 2019, entitled “System and Methods for Exploiting Inter-Cell Multiplexing Gain in Wireless Cellular Systems Via Distributed Input Distributed Output Technology”;

[0339] U. S. Patent No. 10,187,133, issued Jan. 22, 2019, entitled “System And Method For Power Control And Antenna Grouping In A Distributed-Input-Distributed-Output (DIDO) Network”;

[0340] U. S. Patent No. 10,164,698, issued Dec. 25, 2018, entitled “System and Methods for Exploiting Inter-Cell Multiplexing Gain in Wireless Cellular Systems Via Distributed Input Distributed Output Technology”;

[0341] U. S. Patent No. 9,973,246, issued May 15, 2018, entitled “System and Methods for Exploiting Inter-Cell Multiplexing Gain in Wireless Cellular Systems Via Distributed Input Distributed Output Technology”;

[0342] U. S. Patent No. 9,923,657, issued March 20, 2018, entitled “System and Methods for Exploiting Inter-Cell Multiplexing Gain in Wireless Cellular Systems Via Distributed Input Distributed Output Technology”;

[0343] U. S. Patent No. 9,826,537, issued November 21, 2017, entitled “System And Method For Managing Inter-Cluster Handoff Of Clients Which Traverse Multiple DIDO Clusters”;

[0344] U. S. Patent No. 9,819,403, issued November 14, 2017, entitled “System And Method For Managing Handoff Of A Client Between Different Distributed-Input-Distributed-Output (DIDO) Networks Based On Detected Velocity Of The Client”;

[0345] U. S. Patent No. 9,685,997, issued June 20, 2017, entitled “Systems and Methods to Enhance Spatial Diversity in Distributed Input Distributed Output Wireless Systems.”;

[0346] U. S. Patent No. 9,386,465, issued, July 5, 2016, entitled “System and Method For Distributed Antenna Wireless Communications”;

[0347] U. S. Patent No. 9,369,888, issued June 14, 2016, entitled “Systems and Methods to Coordinate Transmissions in Distributed Wireless Systems via User Clustering”;

[0348] U. S. Patent No. 9,312,929, issued April 12, 2016, entitled “System and Methods to Compensate for Doppler Effects in Distributed-Input Distributed Output Systems.”;

[0349] U. S. Patent No. 8,989,155, issued March 24, 2015, entitled “System and Methods for Wireless Backhaul in Distributed-Input Distributed-Output Wireless Systems”;

[0350] U. S. Patent No. 8,971,380, issued March 3, 2015, entitled “System And Method For Adjusting DIDO Interference Cancellation Based On Signal Strength Measurements”;

[0351] U. S. Patent No. 8,654,815, issued Feb. 18, 2014, entitled “System and Method For Distributed Antenna Wireless Communications”;

[0352] U. S. Patent No. 8,571,086, issued Oct. 29, 2013, entitled “System And Method For DIDO Precoding Interpolation In Multicarrier Systems”;

[0353] U. S. Patent No. 8,542,763, issued Sep. 24, 2013, entitled “Systems And Methods To Coordinate Transmissions In Distributed Wireless Systems Via User Clustering”;

[0354] U. S. Patent No. 8,428,162, issued April 23, 2013, entitled “System and Method for Distributed Input Distributed Output Wireless Communication”;

[0355] U. S. Patent No. 8,170,081, issued May 1, 2012, entitled “System And Method For Adjusting DIDO Interference Cancellation Based On Signal Strength Measurements”;

[0356] U. S. Patent No. 8,160,121, issued Apr. 17, 2012, entitled, “System and Method For Distributed Input-Distributed Output Wireless Communications”;

[0357] U. S. Patent No. 7,885,354, issued Feb. 8, 2011, entitled “System and Method For Enhancing Near Vertical Incidence Skywave (“NVIS”) Communication Using Space-Time Coding.”;

[0358] U. S. Patent No. 7,711,030, issued May 4, 2010, entitled “System and Method For Spatial-Multiplexed Tropospheric Scatter Communications”;

[0359] U. S. Patent No. 7,636,381, issued Dec. 22, 2009, entitled “System and Method for Distributed Input Distributed Output Wireless Communication”;

[0360] U. S. Patent No. 7,633,994, issued Dec. 15, 2009, entitled “System and Method for Distributed Input Distributed Output Wireless Communication”;

[0361] U. S. Patent No. 7,599,420, issued Oct. 6, 2009, entitled “System and Method for Distributed Input Distributed Output Wireless Communication”;

[0362] U. S. Patent No. 7,418,053, issued August 26, 2008, entitled “System and Method for Distributed Input Distributed Output Wireless Communication”;

[0363] U. S. Patent Application No. 19 / 440,224 filed January 5, 2026, entitled “Systems and Methods for Exploiting Inter-cell Multiplexing Gain in Wireless Cellular Systems Via Distributed Input Distributed Output Technology”;

[0364] U. S. Patent Application No. 19 / 415,582 filed December 10, 2025, entitled “Systems and Methods for Exploiting Inter-cell Multiplexing Gain in Wireless Cellular Systems Via Distributed Input Distributed Output Technology”;

[0365] U. S. Patent Application No. 19 / 280,444 filed July 25, 2025, entitled “System And Method For Exploiting Inter-cell Multiplexing Gain in Wireless Cellular Systems Via Distributed Input Distributed Output Technology”;

[0366] U. S. Patent Application No. 19 / 214,698, filed May 21, 2025, entitled “System And Method For Mitigating Interference within Actively Used Spectrum”;

[0367] U. S. Patent Application No. 19 / 199,110, filed May 5, 2025, entitled “System and Methods for Radio Frequency Calibration Exploiting Channel Reciprocity in Distributed Input Distributed Output Wireless Communications”;

[0368] U. S. Patent Application No. 18 / 981,039, filed Oct. 12, 2024, entitled “System And Method For Distributing Radioheads”;

[0369] U. S. Patent Application No. 18 / 389,127, filed Nov. 13, 2023, entitled “System and Methods for Exploiting Inter-Cell Multiplexing Gain in Wireless Cellular Systems Via Distributed Input Distributed Output Technology”;

[0370] U. S. Patent Application No. 16 / 505,593, filed July 8, 2019, entitled “System and Methods to Compensate for Doppler Effects in Distributed-Input Distributed Output Systems”;

[0371] U. S. Patent Application No. 14 / 611,565, filed Feb. 2, 2015 entitled “System and Method For Mapping Virtual Radio Instances Into Physical Areas of Coherence in Distributed Antenna Wireless Systems”.

[0372] To reduce the size and complexity of the present patent application, the disclosure of some of the Related Patents and Applications is not explicitly set forth below. Please see the Related Patents and Applications for a full description of the disclosure.

[0373] The present disclosure describes system and methods to exploit inter-cell multiplexing gain in wireless communications networks via spatial processing, employing a multiple antenna system (MAS) with multi-user (MU) transmissions (a Multi-User Multiple Antenna System, or “MU-MAS”), where the multiple antennas are placed serendipitously. In one embodiment of the disclosure, the power transmitted from the multiple antennas is constrained to minimize interference at cell boundaries (as in conventional cellular systems) and spatial processing methods are employed only to eliminate inter-cell interference. In another embodiment of the disclosure, the power transmitted from the multiple antennas is not constrained to any particular power level (as long as their power emission level falls within the regulatory, safety or practical (e.g. available power, transmitter and / or antenna specifications) limits), thereby creating intentionally higher levels of inter-cell interference throughout the cell that is exploited to achieve inter-cell multiplexing gain and increase the capacity of the wireless communications network.

[0374] In one embodiment, the wireless communications network is a cellular network as in Figures 1 and 3, such as a cellular network based on LTE standards and the multiple antennas serendipitously deployed are transceivers for macro-cells or small-cells. In another embodiment of the disclosure, the wireless communications network is not constrained to any particular cell layout and the cell boundaries canextend over larger areas as in Figures 4-5. For example, the wireless communications network could be a wireless local area network (WLAN) with multiple antennas being WiFi access points, or a mesh, ad-hoc or sensor network, or a distributed antenna system, or a DIDO system with access points placed serendipitously without any transmit power constraint. But, such example network structures should not be considered as limiting the general applicability of the present disclosure to wireless communications networks. The present disclosure applies to any wireless network where multiplexing gain is achieved by transmitting signals from multiple antennas that interfere where received by multiple UEs so as to create simultaneous non-interfering data streams to multiple UEs.

[0375] The MU-MAS is made up of a centralized processor, a network and M transceiver stations (or distributed antennas) communicating wirelessly to N client devices or UEs. The centralized processor unit receives N streams of information with different network content (e.g., videos, web-pages, video games, text, voice, etc., streamed from Web servers or other network sources) intended for different client devices. Hereafter, we use the term “stream of information” to refer to any stream of data sent over the network containing information that can be demodulated or decoded as a standalone stream, according to certain modulation / coding scheme or protocol, to produce any data, including but not limited to audio, Web and video content. In one embodiment, the stream of information is a sequence of bits carrying network content that can be demodulated or decoded as a standalone stream.

[0376] The centralized processor utilizes precoding transformation to combine (according to algorithms, such as those described in the Related Patents and Applications) the N streams of information from the network content into M streams of bits. By way of example, but not limitation, the precoding transformation can be linear (e.g., zero-forcing [Reference 65], block-diagonalization [References 66-67], matrix inversion, etc.) or non-linear (e.g., dirty-paper coding [References 68-70] or Tomlinson-Harashima precoding [References 71-72], lattice techniques or trellis precoding [References 73-74], vector perturbation techniques [References 75-76]). Hereafter, we use the term “stream of bits” to refer to any sequence of bits that does not necessarily contain any useful bit of information and as such cannot be demodulated or decoded as a standalone stream to retrieve the network content. In one embodiment of the disclosure, the stream of bits is the complex baseband signalproduced by the centralized processor and quantized over given number of bits to be sent to one of the M transceiver stations.

[0377] Precoding is computed at the centralized processor by employing the Channel State Information (CSI) and applied over the DL or UL channels to multiplex data streams to or from multiple users. In one embodiment of the disclosure, the centralized processor is aware of the CSI between the distributed antennas and the client devices, and utilizes the CSI to precode data sent over the DL or UL channels. In the same embodiment, the CSI is estimated at the client devices and fed back to the distributed antennas. In another embodiment, the DL-CSI is derived at the distributed antennas from the UL-CSI using radio frequency (RF) calibration and exploiting UL / DL channel reciprocity.

[0378] In one embodiment, the MU-MAS is a distributed-input distributed-output (DIDO) system as described in Related Patents and Patent Applications. In another embodiment, the MU-MAS depicted in Figure 13 is made up of:• User Equipment (UE) 1301: An RF transceiver for fixed and / or mobile clients receiving data streams over the downlink (DL) channel from the backhaul and transmitting data to the backhaul via the uplink (UL) channel• Base Transceiver Station (BTS) 1302: The BTSs interface the backhaul with the wireless channel. BTSs of one embodiment are access points made up of Digital-to-Analog Converter (DAC) / Analog-to-Digital Converter (ADC) and radio frequency (RF) chain to convert the baseband signal to RF. In some cases, the BTS is a simple RF transceiver equipped with power amplifier / antenna and the RF signal is carried to the BTS via RF-over-fiber technology as described in Related Patents and Applications.• Controller (CTR) 1303: A CTR is one particular type of BTS designed for certain specialized features such as transmitting training signals for time / frequency synchronization of the BTSs and / or the UEs, receiving / transmitting control information from / to the UEs, receiving the channel state information (CSI) or channel quality information from the UEs. One or multiple CTR stations can be included in any MU-MAS system. When multiple CTRs are available, the information to or from those stations can be combined to increase diversity and improve link quality. In one embodiment, the CSI is received from multiple CTRs via maximum ratio combining (MRC) techniques to improve CSI demodulation. In another embodiment, the controlinformation is sent from multiple CTRs via maximum ratio transmission (MRT) to improve SNR at the receiver side. The scope of the disclosure is not limited to MRC or MRT, and any other diversity technique (such as antenna selection, etc.) can be employed to improve wireless links between CTRs and UEs.• Centralized Processor (CP) 1304: The CP is a server interfacing the Internet or other types of external networks 1306 with the backhaul. In one embodiment, the CP computes the MU-MAS baseband processing and sends the waveforms to the distributed BTSs for DL transmission• Base Station Network (BSN) 1305: The BSN is the network connecting the CP to the distributed BTSs carrying information for either the DL or the UL channel. The BSN is a wireline or a wireless network or a combination of the two. For example, the BSN is a DSL, cable, optical fiber network, or Line-of-Sight (LOS) or Non-Line-of-Sight (NLOS) wireless link. Furthermore, the BSN is a proprietary network, or a local area network, or the Internet.

[0379] Hereafter we describe how the above MU-MAS framework is incorporated into the LTE standard for cellular systems (and also non-cellular system utilizing LTE protocols) to achieve additional gains in spectral efficiency. We begin with a general overview of LTE framework and modulation techniques employed in the DL and UL channels. Then we provide a brief description of the physical layer frame structure and resource allocation in the LTE standard. Finally, we define MU-MAS precoding methods for downlink (DL) and uplink (UL) channels in multi-user scenarios using the LTE framework. For the DL schemes, we propose two solutions: open-loop and closed-loop DIDO schemes.

[0380] LTE is designed with a flat network architecture (as opposed a hierarchical architecture from previous cellular standards) to provide: reduced latency, reduced packet losses via ARQ, reduced call setup time, improved coverage and throughput via macro-diversity. The network elements in LTE networks depicted in Figure 6 are per [Reference 79]:• GW (gateway): is the router connecting the LTE network to external networks (i.e., the Internet). The GW is split into serving gateway (S-GW) 601 that terminates the E-UTRAN interface 608 and PDN gateway (P-GW) 602 being the interface with external networks. The S-GW and P-GW are part of the so called evolved packet core (EPC) 609;• MME (mobility management entity) 603: manages mobility, security parameters and UE identity. The MME is also part of the LTE EPC;• eNodeB (enhanced Node-B) 604: is the base station handling radio resource management, user mobility and scheduling;• UE (user equipment) 605: is the mobile station.• S1 and X2 interfaces (606 and 607): are the wireline or wireless backhauls between the MME and eNodeBs (S1-MME), the S-GW and eNodeBs (S1-U) and between multiple eNodeBs (X2).

[0381] In one embodiment of the disclosure, the MU-MAS network is an LTE network wherein the UE is the LTE UE, the BTS is the LTE eNodeB, the CTR is the LTE eNodeB or MME, the CP is the LTE GW, the BSN is the S1 or X1 interface. Hereafter we use the terms distributed antennas, BTS and eNodeB interchangeably to refer to any base station in MU-MAS, DIDO or LTE systems.

[0382] The LTE frame has duration of 10msec and is made up of ten subframes as depicted in Figures 7A-7B [References 33,80], Every subframe is divided in two slots of duration 0.5msec each. The LTE standards defines two types of frames: i) type 1 for FDD operation as in Figure 7A), where all subframes are assigned either for the DL or UL channels; ii) type 2 for TDD operation as in Figure 7B), where, part of the subframes are assigned to the DL and part to the UL (depending on the selected configuration), whereas a few subframes are reserved for “special use”. These is at least one special subframe per frame and it is made up of three fields: i) downlink pilot time slot (DwPTS) reserved for DL transmission; ii) guard period (GP); iii) uplink pilot time slot (UpPTS), for UL transmission.

[0383] LTE employs orthogonal frequency division multiplexing (OFDM) and orthogonal frequency division multiple access (OFDMA) modulation for the DL and single-carrier frequency division multiple access (SC-FDMA) for the UL. The “resource element” (RE) is the smallest modulation structure in LTE and is made up of one OFDM subcarrier in frequency and one OFDM symbol duration in time, as shown in Figure 8A for the DL channel and in Figure 8B for the UL channel. The “resource block” (RB) is made up of 12 subcarriers in frequency and one 0.5msec slot in time (made up of 3 to 7 OFDM symbol periods, depending on DL versus UL channel and type of cyclic prefix). Resource blocks for every UE are assigned on a subframe basis. Since the MU-MAS in the present disclosure uses spatial processing to send multipledata streams to different UEs, at every subframe all resource blocks can be allocated to the same UE. In one embodiment, all or a subset of resource blocks are allocated to every UE and simultaneous non-interfering data streams are sent to the UEs via precoding.

[0384] To setup the link between the BTS and the UEs, the LTE standard defines the synchronization procedure. The BTS sends two consecutive signals to the UE: the primary synchronization signal (P-SS) sent over the primary synchronization channel (PSCH) and the secondary synchronization signal (S-SS) sent over the secondary synchronization channel (SSCH). Both signals are used by the UE for time / frequency synchronization as well as to retrieve the cell ID. The P-SS is made up of length-63 Zadoff-Chu sequence from which the UE derives the physical layer ID (0 to 2). The S-SS is an interleaved concatenation of two length-31 binary sequences and is used to derive the cell ID group number (0 to 167). From the two identity numbers above, the UE derives the physical cell ID (PCI, defined from 0 to 503).

[0385] In the MU-MAS system described in the present disclosure, there are no cell boundaries as the power transmitted from the BTSs is increased intentionally to produce interference that is exploited to create areas of coherence around the UEs. In the present disclosure, different BTSs are grouped into “antenna-clusters” or “DI DO-clusters” as defined in related U. S. Patent No. 8,170,081, issued May 1, 2012, entitled “System And Method For Adjusting DIDO Interference Cancellation Based On Signal Strength Measurements”. For example, Figure 9 shows the main antenna-cluster 901 and one adjacent antenna-cluster 902. Every antenna-cluster is made up of multiple BTSs 903.

[0386] The cell ID can be used in MU-MAS and DIDO systems to differentiate the antenna-clusters. In one embodiment of the disclosure, the same cell ID is transmitted from all BTSs of the same antenna-cluster via the P-SS and S-SS. In the same embodiment, different antenna-clusters employ different cell IDs. In another embodiment of the disclosure, all BTSs within the same antenna-cluster 1001 are grouped into “antenna-subclusters” 1003 depicted in Figure 10 with different shaded colors and a different cell ID 1004 is associated to every antenna-subcluster. In one embodiment, the antenna-subclusters are defined statically according to predefined cluster planning or based on GPS positioning information. In another embodiment, the antenna-subclusters are defined dynamically based on measurements of relative signal strength between BTSs or GPS positioning information. In a differentembodiment of the disclosure, a different cell ID is assigned to every area of coherence (described in related U. S. Patent No. 10,277,290, entitled “Systems and Methods to Exploit Areas of Coherence in Wireless Systems”) associated to the UEs.

[0387] When all BTSs within the same antenna-cluster or antenna-subcluster transmit the LTE broadcast channels (e.g., P-SS and S-SS) to the UEs, destructive interference may degrade the performance of time or frequency synchronization enabled by the broadcast channel. Destructive interference may be caused by multipaths generated from spatially distributed BTSs that recombine incoherently at some UE locations. To avoid or mitigate this effect, in one embodiment of the disclosure, only one BTS out of all BTSs within the same antenna-cluster or antennasubcluster transmits the LTE broadcast channels (e.g., P-SS and S-SS) to all UEs. In the same embodiment, the BTS that transmits the LTE broadcast channels is selected to maximize the power received at the UEs over the broadcast channels. In another embodiment, only a limited set of BTSs is selected to transmit simultaneously the LTE broadcast channels to all UEs, such that destructive interference is avoided at the UE. In a different embodiment of the disclosure, the LTE broadcast channels are sent at higher power than the payload to reach all the UEs within the same antenna-cluster or antenna-subcluster.

[0388] As described above, LTE-Advanced supports carrier aggregation (CA) schemes to increase data rate over the DL channel. In MU-MASs, CA can be used in combination with precoding to increase per-user data rate. In one embodiment of this disclosure, transmit precoding is applied to different portions of the RF spectrum (interband CA) or different bands within the same portion of the spectrum (intra-band CA) to increase per-user data rate. When employing inter-band CA, pathloss at different bands may change significantly as those bands are centered at different carrier frequencies. In conventional LTE cellular systems, frequency bands at lower carrier frequencies may experience lower pathloss than higher carrier frequencies. Hence, applying inter-band CA in cellular systems may cause undesired inter-cell interference at lower carrier frequencies. By contrast, the MU-MAS in the present disclosure is not limited by interference at the cell boundary as the BTSs are distributed and there is no concept of cell. This more flexible system layout allows different methods for interband CA in MU-MAS. In one embodiment of the present disclosure, the MU-MAS enables inter-band CA by employing one set of BTSs to operate at lower carrier frequencies and another set of BTSs to operate at higher carrier frequencies, suchthat the two sets intersect or one set is the subset of the other. In another embodiment, the MU-MAS with precoding employs CA methods in conjunction with frequency hopping patterns to improve robustness against frequency-selective fading or interference.1. Downlink closed-loop MU-MAS precoding methods in LTE

[0389] MU-MAS closed-loop schemes can be used either in time-division duplex (TDD) or frequency division duplex (FDD) systems. In FDD systems, DL and UL channels operate at different frequencies and therefore the DL channel state information (CSI) must be estimated at the UE side and reported back to the CP through the BTSs or the CTRs via the UL channel. In TDD systems, DL and UL channels are set at the same frequency and the system may employ either closed-loop techniques or open-loop schemes exploiting channel reciprocity (as described in the following section). The main disadvantage of closed-loop schemes is they require feedback, resulting in larger overhead for control information over the UL.

[0390] The general mechanism for closed-loop schemes in MU-MASs is described as follows: i) the BTSs send signaling information to the UEs over the DL; ii) the UEs exploit that signaling information to estimate the DL CSI from all the “active BTSs”; iii) the UEs quantize the DL CSI or use codebooks to select the precoding weights to be used for the next transmission; iv) the UEs send the quantized CSI or the codebook index to the BTSs or CTRs via the UL channel; v) the BTSs or CTRs report the CSI information or codebook index to the CP that calculates the precoding weights for data transmission over the DL. The “active BTSs” are defined as the set of BTSs that are reached by given UE. For example, in related U. S. Patent No. 9,826,537, entitled “System And Method For Managing Inter-Cluster Handoff Of Clients Which Traverse Multiple DIDO Clusters” and related U. S. Patent No. 8,542,763, entitled “Systems And Methods To Coordinate Transmissions In Distributed Wireless Systems Via User Clustering” we defined the “user-cluster” 905 as the set of BTSs that are reached by given UE, as depicted in Figure 9. The number of active BTSs are limited to a usercluster so as to reduce the amount of CSI to be estimated from the BTSs to given UE, thereby reducing the feedback overhead over the UL and the complexity of the MU-MAS precoding calculation at the CP.

[0391] As described above, MU-MAS precoding employs either linear or nonlinear methods. In the case of non-linear methods (e.g., dirty-paper coding[References 68-70] or Tomlinson-Harashima precoding [References 71-72], lattice techniques or trellis precoding [References 73-74], vector perturbation techniques [References 75-76]), successive interference cancellation is applied at the transmitter to avoid inter-user interference. In this case the precoding matrix is computed accounting for the CSI to all the UEs within the antenna-cluster. Alternatively, linear precoding methods (e.g., zero-forcing [Reference 65], block-diagonalization [References 66-67], matrix inversion, etc.) can be used on a user-cluster basis, since the precoding weights for every UE are computed independent on the other UEs. Depending on the number of UEs and eNodeBs inside the antenna-cluster and userclusters, linear versus non-linear precoding methods offer different computational performance. For example, if the MU-MAS is made up of K UEs per antenna-cluster, M eNodeBs per antenna-cluster and C eNodeBs per user-cluster, the complexity of linear precoding is O(K*C3) whereas for non-linear precoding it is O(M*K2). It is thus desirable to develop a method that dynamically switches between the two types of precoding techniques based on the number if UEs and eNodeBs in MU-MASs to reduce the computational complexity at the CP. In one embodiment of the disclosure, the MU-MAS employs linear precoding methods. In another embodiment, the MU-MAS employs non-linear precoding methods. In the same embodiment of the disclosure, the MU-MAS dynamically switches between linear and non-linear precoding methods based on the number of UEs and eNodeBs in the antenna-clusters and user-clusters to reduce computational complexity at the CP. In a different embodiment, the MU-MAS switches between precoding multiplexing methods for UEs experiencing good channel quality (e.g., in the proximity of eNodeBs) and beamforming or diversity methods for UEs with poor link quality (e.g., far away from the eNodeBs).1.1 Downlink MU-MAS signaling methods within the LTE standard

[0392] The LTE standard defines two types of reference signals (RS) that can be used for DL signaling in closed-loop schemes [References 33,50,82-83]: i) cell-specific reference signal (CRS); ii) UE specific RS such as channel state information (CSI) reference signal (CSI-RS) and demodulation RS (DM-RS). The cell-specific RS is not precoded, whereas the UE-specific RS is precoded [Reference 50], CRS is used in LTE Release 8 that employs SU / MU-MIMO codebook-based techniques with up to four antennas in every cell. LTE-Advanced Release 10 supports non-codebook basedSU / MU-MIMO schemes with up to eight transmit antennas as well as CoMP schemes with antennas distributed over different cells. As such, Release 10 allows for more flexible signaling schemes via CSI-RS. In the present disclosure, we describe how either types of signaling schemes can be used in MU-MAS systems to enable precoding.1.1.1 MU-MAS signaling using CRS

[0393] The CRS is employed in LTE (Release 8) systems to estimate the CSI from all transmit antennas at the BTS to the UE [References 80,84], The CRS is obtained as the product of a two-dimensional orthogonal sequence and a two-dimensional pseudo-random numerical (PRN) sequence. There are 3 orthogonal sequences (i.e., placed on orthogonal sets of OFDM subcarriers) and 168 possible PRN sequences, for a total of 504 different CRS sequences. Every sequence uniquely identifies one cell. Each of the three orthogonal CRSs is associated to one of the three physical layer IDs (0 to 2) that generate a different cell ID, as explained in the previous subsection. The CRS is transmitted within the first and third-last OFDM symbol of every slot, and every sixth subcarrier. Orthogonal patterns in time and frequency are designed for every transmit antenna of the BTS, for the UE to uniquely estimate the CSI from each of transmit antennas. Release 8 defines up to four orthogonal patters per CRS, one for each of the four transmit antennas employed in MIMO 4x4. This high density of CRS in time and frequency (i.e., sent every slot of 0.5msec, and every sixth subcarrier), producing 5% overhead, was designed intentionally to support scenarios with fast channel variations over time and frequency [Reference 83],

[0394] In Release 8, since there are up to 3 orthogonal CRSs with 4 orthogonal patterns each for multi-antenna modes (or 6 orthogonal CRSs for single antenna mode), it is possible to discriminate up to 12 transmit antennas within the same coverage area, without causing interference to the CRS. In one embodiment of the disclosure, the antenna-cluster 1001 is divided into three antenna-subclusters 1003 as in Figure 10. Different physical layer IDs (or cell IDs) are associated to each of the antenna-subclusters, such that each antenna-subcluster is assigned with one of the three orthogonal CRSs with four orthogonal patterns (i.e., each antenna-subcluster can support up to four BTS without causing interference to the CRS from other BTSs). In this embodiment, every cluster can support up to 12 BTSs without causing interference to the CRS.

[0395] In scenarios where more than twelve BTSs are placed within the same cluster, it is desirable to increase the number of available orthogonal CRSs to support larger number of active BTSs (i.e., BTSs that simultaneously transmit precoded signals to the UEs). One way to achieve that is to define more than three antennasubclusters 1003 per antenna-cluster 1101 and assign the same three physical layer IDs (or cell ID 1104 from 0 to 2) to the antenna-subclusters 1103 with a repetition pattern as shown in Figure 11. We observe that the antenna-subclusters may come in different shapes and are defined in such a way that every user-cluster 1102 cannot reach two antenna-subclusters with the same physical layer ID, thereby avoiding interference to the CRS. For example, one way to achieve that is to define the area of the antenna-subcluster 1103 larger than the user-cluster 1102 and avoid that adjacent antenna-subcluster use the same physical layer ID. In one embodiment of the disclosure, the multiple antenna-subclusters are placed within the same antennacluster with repetition patterns such that their respective CRSs do not interfere, thereby enabling simultaneous non-interfering transmissions from more than twelve BTSs.

[0396] In practical MU-MAS systems, it may be the case that every UE sees more than only four BTSs within its user-cluster. For example, Figure 12 shows the SNR distribution for practical deployment of DIDO or MU-MAS systems in downtown San Francisco, CA. The propagation model is based on 3GPP pathloss / shadowing model [Reference 81] and assumes a carrier frequency of 900MHz. The dots in the map indicate the location of the DIDO-BTSs, whereas the dark circle represents the usercluster (with the UE being located at the center of the circle). In sparsely populated areas 1201, the UE sees only a few BTSs within its user-cluster (e.g., as low as three BTSs for the example in Figure 12), whereas in densely populated areas 1202 each user-cluster may comprise as many as 26 BTSs as in Figure 12.

[0397] The high redundancy of the CRS can be exploited in MU-MASs to enable CSI estimation from any number of transmit antennas greater than four. For example, if the channel is fixed-wireless or characterized by low Doppler effects, there is no need to compute the CSI from all four transmit antennas every 0.5msec (slot duration). Likewise, if the channel is frequency-flat, estimating the CSI every sixth subcarrier is redundant. In that case, the resource elements (RE) occupied by the redundant CRS can be re-allocated for other transmit antennas or BTSs in the MU-MAS. In one embodiment of the disclosure, the system allocates resource elements of redundantCRS to extra antennas or BTSs in the MU-MAS system. In another embodiment, the system estimates time and frequency selectivity of the channel and dynamically allocates the CRS for different BTSs or only the BTSs within the user-cluster to different resource elements.

[0398] The number of BTSs included in every user-cluster depends on the signal power level measured at the UE from all BTSs in the user-cluster relative to the noise power level, or signal-to-noise ratio (SNR). In one embodiment, the UE estimates the SNR from all BTSs in its neighborhood and selects the BTSs that belong to its usercluster based on the SNR information. In another embodiment, the CP is aware of the SNR from the BTSs to every UE (based on feedback information from the UEs or information obtained from the UL channel, assuming UL / DL channel reciprocity) and selects the set of BTSs to be included in every user-cluster.

[0399] The number of BTSs included in every user-cluster determines the performance of the MU-MAS methods described in the present disclosure. For example, if the number of BTSs per user-cluster is low, the UE experiences higher level of out-of-cluster interference, resulting in high signal-to-interference-plus-noise ratio (SINR) and low data rate. Similarly, if large number of BTSs is selected for every user-cluster, the SNR measured at the UE from the BTSs at the edge of the usercluster is low and may be dominated by the out-of-cluster interference from adjacent BTSs outside the user-cluster. There is an optimal number of BTSs per user-cluster that produces the highest SINR and data rate. In one embodiment of the disclosure, the CP selects the optimal number of BTSs per user-cluster to maximize SINR and data rate to the UE. In another embodiment of the disclosure, the BTSs per usercluster are dynamically selected to adapt to the changing conditions of the propagation environment or UE mobility.

[0400] Another drawback of using large number of BTSs per user-cluster is high computational load. In fact, the more BTSs in the user-cluster the larger the computation complexity of the MU-MAS precoder. In one embodiment of the disclosures, the BTSs per user-cluster are selected to achieve optimal tradeoff between SINR or data rate performance and computational complexity of the MU-MAS precoder. In another embodiment, the BTSs per user-cluster are dynamically selected based on tradeoffs between propagation conditions and computational resources available in the MU-MAS.1.1.2 MU-MAS signaling using CSI-RS and DM-RS

[0401] In the LTE-Advanced (Release 10) standard the CSI-RS is used by every UE to estimate the CSI from the BTSs [References 33,83], The standard defines orthogonal CSI-RS for different transmitters at the BTS, so that the UE can differentiate the CSI from different BTSs. Up to eight transmit antennas at the BTS are supported by the CSI-RS as in Tables 6.10.5.2-1,2 in [Reference 33], The CSI-RS is sent with a periodicity that ranges between 5 and 80 subframes (i.e., CSI-RS send every 5 to 80 msec) as in Tables 6.10.5.3-1 in [Reference 33], The periodicity of the CSI-RS in LTE-Advanced was designed intentionally larger than the CRS in LTE to avoid excessive overhead of control information, particularly for legacy LTE terminals unable to make use of these extra resources. Another reference signal used for CSI estimation is to demodulation RS (DM-RS). The DM-RS is a demodulation reference signal intended to a specific UE and transmitted only in the resource block assigned for transmission to that UE.

[0402] When more than eight antennas (maximum number of transmitters supported by the LTE-Advanced standard) are within the user-cluster, alternative techniques must be employed to enable DIDO precoding while maintaining system compliance to the LTE-Advanced standard. In one embodiment of the disclosure, every UE uses the CSI-RS or the DM-RS or combination of both to estimate the CSI from all active BTSs in its own user-cluster. In the same embodiment, the DIDO system detects the number of BTSs within the user-cluster and whether or not the user-cluster is compliant to the LTE-Advanced standard (supporting at most eight antennas). If it not compliant, the DIDO system employs alternative techniques to enable DL signaling from the BTSs to the current UE. In one embodiment, the transmit power from the BTSs is reduced until at most eight BTSs are reachable by the UE within its usercluster. This solution, however, may result in reduction of data rate as coverage would be reduced.

[0403] Another solution is to divide the BTSs in the user-cluster in subsets and send one set of CSI-RS for every subset at a time. For example, if the CSI-RS periodicity is 5 subframes (i.e., 5msec) as in Table 6.10.5.3-1 in [Reference 33], every 5msec the CSI-RS is sent from a new subset of BTSs. Note that this solution works as long as the CSI-RS periodicity is short enough to cover all BTS subsets within the channel coherence time of the UE (which is a function of the Doppler velocity of the UE). For example, if the selected CSI-RS periodicity is 5msec and the channelcoherence time is 100msec, it is possible to define up to 20 BTS subsets of 8 BTS each, adding up to a total of 160 BTSs within the user-cluster. In another embodiment of the disclosure, the DIDO system estimates the channel coherence time of the UE and decides how many BTSs can be supported within the user-cluster for given CSI-RS periodicity, to avoid degradation due to channel variations and Doppler effect.

[0404] The solutions for CSI-RS proposed so far are all compliant with the LTE standard and can be deployed within the framework of conventional LTE systems. For example, the proposed method that allows more than eight antennas per user-cluster would not require modifications of the UE LTE hardware and software implementation, and only slight modification of the protocols used at the BTSs and CP to enable selection of BTSs subset at any given time. These modifications can be easily implemented in a cloud-based software defined radio (SDR) platform, which is one promising deployment paradigm for DIDO and MU-MAS systems. Alternatively, if it is possible to relax the constraints of the LTE standard and develop slightly modified hardware and software for LTE UEs to support similar, but non-LTE-compliant DIDO or MU-MAS modes of operation, so as enable UEs to be able to operate in full LTE-compliant mode, or in a modified mode that supports non-LTE-compliant DIDO or MU-MAS operation. For example, this would enable another solution is to increase the amount of CSI-RS to enable higher number of BTSs in the system. In another embodiment of the disclosure, different CSI-RS patterns and periodicities are allowed as a means to increase the number of supported BTSs per user-cluster. Such slight modifications to the LTE standard may be small enough that existing LTE UE chipsets can be used with simply software modification. Or, if hardware modification would be needed to the chipsets, the changes would be small.1.2 Uplink MU-MAS CSI feedback methods within the LTE standard

[0405] In the LTE and LTE-Advanced standards, the UE feedbacks information to the BTS to communicate its current channel conditions as well as the precoding weights for closed-loop transmission over the DL channel. Three different channel indicators are included in those standards [Reference 35]:• Rank indicator (RI): indicates how many spatial streams are transmitted to given UE. This number is always equal or less than the number of transmit antennas.• Precoding matrix indicator (PMI): is the index of the codebook used for precoding over the DL channel.• Channel quality indicator (CQI): defines the modulation and forward error correction (FEC) coding scheme to be used over the DL to maintain predefined error rate performance for given channel conditions

[0406] Only one Rl is reported for the whole bandwidth, whereas the PMI and CQI reporting can be wideband or per sub-band, depending on the frequency-selectivity of the channel. These indicators are transmitted in the UL over two different types of physical channels: i) the physical uplink control channel (PUCCH), used only for control information; ii) the physical uplink shared channel (PUSCH), used for both data and control information, allocated over one resource block (RB) and on a sub-frame basis. On the PUCCH, the procedure to report the Rl, PMI and CQI is periodic and the indicators can be either wideband (for frequency-flat channels) or UE-selected on a sub-band basis (for frequency-selective channels). On the PUSCH, the feedback procedure is aperiodic and can be UE-selected on a sub-band basis (for frequency-selective channels) or higher-layer configured sub-band (e g., for transmission mode 9 in LTE-Advance with eight transmitters).

[0407] In one embodiment of the disclosure, the DIDO or MU-MAS system employs Rl, PMI and CQI to report to BTSs and CP its current channel conditions as well as precoding information. In one embodiment, the UE uses the PUCCH channel to report those indicators to the CP. In another embodiment, in case a larger number of indicators is necessary for DIDO precoding, the UE employs the PUSCH to report additional indicators to the CP. Incase the channel is frequency-flat, the UE can exploit extra UL resources to report the PMI for a larger number of antennas in the DIDO systems. In one embodiment of the disclosure, the UE or BTSs or CP estimate the channel frequency selectivity and, in case the channel is frequency-flat, the UE exploits the extra UL resources to report the PMI for a larger number of BTSs.2. Downlink open-loop MU-MAS precoding methods in LTE

[0408] Open-loop MU-MAS precoding schemes can only be used in time-division duplex (TDD) systems employing RF calibration and exploiting channel reciprocity. The general mechanism of open-loop schemes in MU-MASs is made up of: i) the UEs send signaling information to the BTSs or CTRs over the UL; ii) the BTSs or CTRs exploit that signaling information to estimate the UL CSI from all UEs; ill) the BTSs orCTRs employ RF calibration to convert the UL CSI into DL CSI; iv) the BTSs or CTRs send the DL CSI or codebook index to the CP via the BSN; v) based on that DL CSI, the CP calculates the precoding weights for data transmission over the DL. Similarly to closed-loop MU-MAS precoding schemes, user-clusters can be employed to reduce the amount of CSI to be estimated at the BTSs from the UEs, thereby reducing the computational burden at the BTSs as well as the amount of signaling required over the UL. In one embodiment of the disclosure, open-loop precoding techniques are employed to send simultaneous non-interfering data streams from the BTSs to the UEs over the DL channel.

[0409] In LTE there are two types of reference signal for the uplink channel [References 31,33,87]: i) sounding reference signal (SRS), used for scheduling and link adaptation; ii) demodulation reference signal (DMRS), used for data reception. In one embodiment of the disclosure, the DMRS is employed in open-loop precoding systems to estimate the UL channels form all UEs to all BTSs. In the time domain, the DMRS is sent at the fourth OFDM symbol (when a normal cyclic prefix is used) of every LTE slot (of duration 0.5msec). In the frequency domain, the DMRS sent over the PUSCH is mapped for every UE to the same resource block (RB) used by that UE for UL data transmission.The length of the DMRS is MRS=mNRB, where m is the number of RBs and NRB=12 is the number of subcarriers per RB. To support multiple UEs, up to twelve DMRSs are generated from one base Zadoff-Chu [Reference 88] or computer-generated constant amplitude zero autocorrelation (CG-CAZAC) sequence, via twelve possible cyclic shifts of the base sequence. Base sequences are divided into 30 groups and neighbor LTE cells select DMRS from different groups to reduce inter-cell interference. For example, if the maximum number of resource blocks within one OFDM symbol is 110 (i.e., assuming 20MHz overall signal bandwidth), it is possible to generate up to 110x30 = 3300 different sequences. We observe that the 30 base sequences are not guaranteed to be orthogonal and are designed to reduce interference across cells, without eliminating it completely. By contrast, the 12 cyclic shifts of the same base sequence are orthogonal, thereby allowing up to 12 UEs to transmit in the UL over the same RB without interference. The value of cyclic shift to be used by every UE is provided by the BTS through the downlink control information (DCI) message sent over the PDCCH. The DCI in Release 8 is made up of 3 bits, that enables the UE to use only up to 8 values of cyclic shift in the pool of twelve possible options.

[0410] The cyclic shifts of the base DMRS sequence are exploited in the present disclosure to enable MU-MIMO schemes over the UL channel as well as to estimate the CSI from multiple UEs for DL precoding when channel reciprocity is exploited in TDD mode. In one embodiment of the disclosure, open-loop precoding methods are employed to send simultaneous non-interfering data streams from the distributed BTSs to the UEs over the DL channel. In a different embodiment of the disclosure, open-loop MU-MIMO methods are employed to receive simultaneous non-interfering data streams from the UEs to the BTSs over the UL channel. The same CSI estimated over the UL from all active UEs can be used to compute the receiver spatial filter for MU-MIMO operation in the UL as well as the weights for DL precoding. Since Release 8 defines only up to 8 orthogonal DMRSs (due to limited DOI bits, as explained above), MU-MIMO schemes for the UL channel and MU-MAS precoding schemes for the DL channel can support at most eight UEs, assuming all UEs utilize the full UL bandwidth.

[0411] One way to increase the number of simultaneous UEs being served through MU-MIMO in UL or MU-MAS precoding in DL is to multiplex the DMRS of the UEs over the frequency domain. For example, if 10MHz bandwidth is used in TDD mode, there are 50 RBs that can be allocated to the UEs. In this case, 25 interleaved RBs can be assigned to one set of eight UEs and the remaining 25 interleaved RBs to another set of UEs, totaling to 16 UEs that can be served simultaneously. Then, the CSI is computed by interpolating the estimates from the DMRS sent over interleaved RBs. Larger number of simultaneous UEs can be supported by increasing the number of interleaving patterns of the UL RBs. These patterns can be assigned to different UEs statically or dynamically according to certain frequency hopping sequence. In one embodiment of the disclosure, DMRSs are assigned to the UEs over orthogonal interleaved RBs to increase the number of UEs to be supported via MU-MIMO or MU-MAS precoding. In the same embodiment, the interleaved RBs are assigned statically. In another embodiment, the interleaved RBs are assigned dynamically according to certain frequency hopping pattern.

[0412] An alternative solution is to multiplex the DMRS of different UEs in the time domain. For example, the UEs are divided into different groups and the DMRSs for those groups are sent over consecutive time slots (of duration 0.5msec each). In this case, however, it is necessary to guarantee that the periodicity of the DMRS assignment for different groups is lower than the channel coherence time of the fastest moving UE. In fact, this is necessary condition to guarantee that the channel does notvary for all UEs from the time the CSI is estimated via DMRS to the time system transmits DL data streams to the UEs via DIDO precoding. In one embodiment of the disclosure, the system divides the active UEs into groups and assigns the same set of DMRS to each group over consecutive time slots. In the same embodiment, the system estimates the shortest channel coherence time for all active UEs and calculates the maximum number of UE groups as well as the periodicity of the DMRS time multiplexing based on that information.

[0413] Another solution is to spatially separate different groups of UEs employing the same sets of DMRSs. For example, the same set of orthogonal DMRSs can be used for all the UEs from different antenna-subclusters in Figure 11 identified by the same cell ID. In one embodiment of the disclosure, groups of UEs employing the same set of orthogonal DMRSs are spatially separated to avoid interference between the groups. In the same embodiment, the same set of orthogonal DMRSs is employed by different antenna-subclusters identified by the same cell ID. The MU-MAS may assign the UEs to “virtual cells” to maximize the number of DMRS that can be used in the UL. In one exemplary embodiment, the virtual cell is the area of coherence (described in related U. S. Patent No. 10,277,290, entitled “Systems and Methods to Exploit Areas of Coherence in Wireless Systems”) around the UE and the DIDO system generates up to 3300 areas of coherence for different UEs. In another embodiment of the disclosure, each of the 30 base sequences is assigned to a different antenna-cluster (clusters are defined in related U. S. Patent No. 8,170,081, issued May 1, 2012, entitled “System And Method For Adjusting DIDO Interference Cancellation Based On Signal Strength Measurements”) to reduce inter-cluster interference across adjacent antenna-clusters.3. Uplink MU-MAS methods in LTE

[0414] The present disclosure employs open-loop MU-MIMO schemes over the UL channel to receive simultaneous UL data streams from all UEs to the BTSs. The UL open-loop MU-MIMO scheme is made up of the following steps: i) UEs send signaling information and data payload to all BTSs; ii) the BTSs compute the channel estimations from all UEs using the signaling information; iii) the BTSs send the channel estimates and data payloads to the CP; iv) the CP uses the channel estimates to remove inter-channel interference from all UEs’ data payloads via spatial filtering and demodulates the data streams form all UEs. In one embodiment, the open-loop MU-MIMO system employs single-carrier frequency division multiple access (SC-FDMA)to increase the number of UL channels from the UEs to the BTSs and multiplex them in the frequency domain.

[0415] In one embodiment, synchronization among UEs is achieved via signaling from the DL and all BTSs are assumed locked to the same time / frequency reference clock, either via direct wiring to the same clock or sharing a common time / frequency reference, in one embodiment through GPSDO. Variations in channel delay spread at different UEs may generate jitter among the time references of different UEs that may affect the performance of MU-MIMO methods over the UL. In one embodiment, only the UEs within the same antenna-cluster (e.g., UEs in close proximity with one another) are processed with MU-MIMO methods to reduce the relative propagation delay spread across different UEs. In another embodiment, the relative propagation delays between UEs are compensated at the UEs or at the BTSs to guarantee simultaneous reception of data payloads from different UEs at the BTSs.

[0416] The methods for enabling signaling information for data demodulation over the UL are the same methods used for signaling in the downlink open-loop DIDO scheme described at the previous section. The CP employs different spatial processing techniques to remove inter-channel interference from the UEs data payload. In one embodiment of the disclosure, the CP employs non-linear spatial processing methods such as maximum likelihood (ML), decision feedback equalization (DFE) or successive interference cancellation (SIC) receivers. In another embodiment the CP employs linear filters such as zeros-forcing (ZF) or minimum mean squared error (MMSE) receivers to cancel co-channel interference and demodulate the uplink data streams individually.4. Integration with Existing LTE Networks

[0417] In the United States and other regions of the world, LTE networks are already in operation or are in the process of being deployed and / or committed to be deployed. It would be of significant benefit to LTE operators if they could gradually deploy DIDO or MU-MAS capability into their existing or already-committed deployments. In this way, they could deploy DIDO or MU-MAS in areas where it would provide the most immediate benefit, and gradually expand the DIDO or MU-MAS capability to cover more their network. In time, once they have sufficient DIDO or MU-MAS coverage in an area, they can choose to cease using cells entirely, and instead switch entirely to DIDO or MU-MAS and achieve much higher spectral density at much lower cost. Throughout this entire transition from cellular to DIDO or MU-MAS, the LTEoperator’s wireless customers will never see a loss in service. Rather, they’ll simply see their data throughput and reliability improve, while the operator will see its costs decline.

[0418] There are several embodiments that would enable a gradual integration of DIDO or MU-MAS into existing LTE networks. In all cases, the BTSs for DIDO or MU-MAS will be referred as DIDO-LTE BTSs and will utilize one of the LTE-compatible DIDO or MU-MAS embodiments described above, or other LTE-compatible embodiments as they may be developed in the future. Or, the DIDO-LTE BTSs will utilize a slight variant of the LTE standard, such as those described above and the UEs will either be updated (e.g. if a software update is sufficient to modify the UE to be DIDO or MU-MAS compatible), or a new generation of UEs that are DIDO- or MU-MAS-compatible will be deployed. In either case, the new BTSs that support DIDO or MU-MAS either within the constraints of the LTE standard, or as a variant of the LTE standard will be referred to below as DIDO-LTE BTSs.

[0419] The LTE standard supports various channel bandwidths (e.g., 1.4, 3, 5, 10, 15 and 20 MHz). In one embodiment, an operator with an existing LTE network would either allocate new bandwidth for the LTE-DIDO BTSs, or would subdivide the existing LTE spectrum (e.g. 20MHz could be subdivided into two 10MHz blocks) to support conventional LTE BTSs in a cellular configuration in one block of spectrum and DIDO LTE BTSs in another block of spectrum. Effectively, this would establish two separate LTE networks, and UE devices would be configured to use one or the other network, or select between the two. In the case of subdivided spectrum, the spectrum could be divided evenly between the conventional LTE network and the DIDO-LTE BTS network, or unevenly, allocated more spectrum to whichever network could best utilize it given the level of cellular LTE BTS and DI DO-LTE BTS deployment and / or UE usage patterns. This subdivision could change as needed overtime, and at some point, when there are sufficient DIDO-LTE BTSs deployed to provide the same or better coverage as the cellular BTSs, all of the spectrum can be allocated to DIDO-LTE BTSs, and the cellular BTSs can be decommissioned.

[0420] In another embodiment, the conventional cellular LTE BTSs can be configured to be coordinated with the DIDO-LTE BTSs such that they share the same spectrum, but take turns using the spectrum. For example, if they were sharing the spectrum use equally, then each BTS network would utilize one 10ms frame time in alternation, e.g. one 10ms frame for the cellular LTE BTS, followed by one 10ms framefor the DIDO-LTE BTS. The frame times could be subdivided in unequal intervals as well. This interval splitting could change as needed overtime, and at some point, when there are sufficient DIDO-LTE BTSs deployed to provide the same or better coverage as the cellular BTSs, all of the time can be allocated to DIDO-LTE BTSs, and the cellular BTSs can be decommissioned.

[0421] In another embodiment of the disclosure, DIDO or MU-MAS is employed as LOS or NLOS wireless backhaul to small cells in LTE and LTE-Advanced networks. As small-cells are deployed in LTE networks, DIDO or MU-MAS provides high-speed wireless backhaul to those small cells. As the demand for higher data rate increases, more small-cells are added to the network until the wireless network reaches a limit where no more small-cells can be added in a given area without causing inter-cell interference. In the same embodiment of the disclosure, DIDO-LTE BTSs are used to replace gradually small-cells, thereby exploiting inter-cell interference to provide increased network capacity.5. MU-MAS LTE Scheduler

[0422] In MU-MAS, distributed antennas or BTSs transmit simultaneous precoded data streams to multiple UEs. As described in Related Patents and Applications, the number of BTSs must be equal or larger than the number of UEs to enable simultaneous data transmissions. In practical deployments, the number of UEs may exceed the number of BTSs. In this case, the extra UEs can be selected for transmission at different time slots or frequency bands according to certain scheduling policy. The scheduler exploits the channel quality information of the UEs to decide the best set of UEs to be serviced at a given time and frequency. Different scheduling methods are used in the present disclosure, including proportional fair scheduler, round-robin or greedy algorithms.

[0423] As described in the previous sections, the LTE standard defines two parameters to inform the scheduler about the link quality of every UE: CQI and SRS. The CQI measures the quality of the DL channel and is fed back from the UE to the BTS. The SRS is signaling information sent from the UE to the BTS to measure the UL channel quality. Both indicators provide information of the UL / DL channel quality over time and frequency domains. In FDD systems, the DL scheduler must use the CQI as performance measure, since the DL and UL channel quality may vary due to different carrier frequencies. In TDD mode, the DL schedule employs either the CSI or the SRS or combination of both to perform its scheduling decision. The sameperformance metrics can be used for UL scheduling. In one embodiment of the disclosure, the MU-MAS scheduler employs the CQI and SRS as performance metrics used by the scheduling algorithm.

[0424] The MU-MAS described in the present disclosure enables one additional channel quality indicator not disclosed in prior art: the spatial selectivity indicator (SSI), described in related U. S. Application Serial No. 13 / 475,598, entitled “Systems and Methods to enhance spatial diversity in distributed-input distributed-output wireless systems”. The SSI can be computed based on the CSI obtained from all UEs via feedback mechanisms or from the UL channel (applying UL / DL channel reciprocity). In one embodiment of the disclosure, the scheduler employs the SSI as performance metric. The SSI is a measure of the spatial diversity available in the wireless link. The SSI depends on the spatial characteristics of the BTSs as well as the UEs. In one exemplary embodiment of the disclosure, the scheduler obtains the SSI from all the UEs and schedules the UEs with the “optimal” SSI according to certain scheduling criterion. If more BTSs are available than the active BTSs, the users selection criterion described above is combined with the antenna selection method described in related U. S. Application Serial No. 13 / 475,598, entitled “Systems and Methods to enhance spatial diversity in distributed-input distributed-output wireless systems”. In one embodiment of the disclosure, the scheduler selects the optimal subset of BTSs and UEs based on certain scheduling criterion.

[0425] With respect to Figures 9, 10 and 11, in certain scenarios there may not be enough orthogonal signaling sequences to enable large number of BTSs within the same antenna-cluster or antenna-subcluster. In this case, some level of interference may occur if additional BTSs are activated to cover regions with larger numbers of active UEs. In one embodiment of the disclosure, the scheduler measures the level of interference between antenna-clusters or antenna-subclusters and schedules the UEs to minimize the effect of that interference over the wireless link.

[0426] The antenna selection algorithm described in related U. S. Patent No.9,685,997, entitled “Systems and Methods to enhance spatial diversity in distributed-input distributed-output wireless systems” is employed in the present disclosure to select the optimal set of active BTSs based on the SSI. This antenna selection algorithm, however, may require high computational complexity as MU-MAS precoding processing must be applied over all possible permutations of antenna subsets before making a decision on the best subset based on the SSI performancemetric. In MU-MAS with large number of cooperative BTSs, this computational burden may become expensive or untenable to achieve in practical deployments. It is thus desirable to develop alternative techniques to reduce the number of antenna subsets while maintaining good performance of the antenna selection method. In one embodiment of the disclosure, the MU-MAS employs methods based on queuing of the antenna subset ID numbers, hereafter referred to as “antenna shuffling method”. In one embodiment of the disclosure, the antenna shuffling method subdivides the queue containing all possible antenna subset IDs (i.e., all possible permutations of active BTSs forgiven set of available BTSs) into different groups and assigns different priorities to those groups. These groups are defined to assign fair chances to all subset IDs to be selected, but the SSI metric is computed only for limited number of subsets (e.g., those ones with highest priority) thereby reducing computational complexity. In one exemplary embodiment, the queue of subset ID is divided into three groups where each group is assigned a different rule: i) group #1 contains the IDs with highest priority which are pulled out of the group only in case a new subset with higher priority is identified; ii) group #2 where new antenna subsets (selected from group #3) are included at every iteration of the method; iii) group #3 where the antenna subset IDs are shuffled according to round-robin policy. All subset IDs within group #1 and #2 are sorted at each iteration of the method based on their priority to give opportunity to subsets IDs from group #2 to be upgraded to group #1. The SSI is computed only for the subsets within groups #1 and #2 and the antenna selection algorithm is applied only to those subsets.6. MU-MAS LTE User Equipment

[0427] The present disclosure comprises of different designs of the LTE UE. In one embodiment, the UE is an LTE UE that is compatible with the MU-MAS employing precoding as described above and depicted in Figure 13.

[0428] In a different embodiment, the UE 1401 connects to different devices 1402 and 1403 through a first network interface 1404 (e.g., Wi-Fi, USB, Ethernet, Bluetooth, optical fiber, etc.) and to the MU-MAS through a second network interface 1405 as shown in Figure 14. The UE in Figure 14 is equipped with two different network interfaces wherein each network interface comprises of one or multiple antennas (although in alternative embodiments, first network interface 1404 may be a wired interface without antennas). The antennas of the first network interface are denoted with circles, whereas the antennas of the second network interface are denoted withtriangles. In the same embodiment, the second network interface supports MU-MAS precoding, MU-MAS implemented with LTE-compliant protocols, or MU-MAS (implemented with or without LTE-compliant protocols) and an alternative network. In the same embodiment, the alternative network is a cellular network, an LTE network or Wi-Fi network. In the same embodiment, the UE works with either and / or both MU-MAS and / or the alternative network and the UE selects either MU-MAS or the alternative network based on some criteria. In the same embodiment, the criteria are: i) whether only one network is available and is chosen; ii) whether one network has better performance; iii) whether one network is more economical; iv) whether one network is less congested; v) whether one network uses less UE resources.

[0429] In one embodiment of the disclosure, the UE 1501 is in a case that physically attaches to the user device 1502 as depicted in Figure 15. In the same embodiment, the case serves as a decorative addition to the user device. In another embodiment, the case serves to protect the user device from physical damage. The UE comprises of battery 1503, and one or multiple network interfaces 1504.

[0430] In one embodiment, the UE electronics are embedded within a case. In the same embodiment, the UE electronics include a battery 1503. The battery includes a power charger coupling through a physical electrical contact or a wireless contact. Exemplary power couplings are conductive, inductive, RF, light, or thermal, but power couplings are not limited these approaches. In the same embodiment, the UE electronics are coupled to receive power from the user device. This power coupling is through a physical contact or through an inductive or wireless contact. In the same embodiment, the user device is coupled to receive power from the MU-MAS UE. This coupling is through a physical contact or through an inductive or wireless contact. In a different embodiment, the same power charger powers both the user device and the MU_MAS UE.

[0431] In one embodiment of the disclosure, the UE is configured to communicate to the user device. In the same embodiment, the UE can be reset (e.g., via switch, or by removing power) so the user device can initially connect to it, and once the connection is established, the UE can be configured by the user device. Such configuration includes configuring a private password and / or other security protocols. In a different embodiment, the UE includes a means to be configured to communicate with the user device. Such configuration is done via a communications port to anotherdevice, wherein the communications port is USB, or via controls and / or buttons on the UE, or via display, wherein buttons or touch input are used.

[0432] In another embodiment, the same RF chain is used for MU-MAS communications as well as for the alternative network. In another embodiment, a different RF chain is used for MU-MAS communications and the alternative network.7. Radio Frequency (RF) Calibration Exploiting Channel Reciprocity

[0433] Conventional closed-loop MU-MAS methods employ UL channel to feedback quantized CSI or codebook indices (as in codebook-based limited feedback schemes) from the UEs to the BTSs or CP. This scheme, however, results in large feedback overhead and high protocol complexity to enable the CSI feedback channel. In TDD systems, where UL and DL are set at the same frequency, it is thus desirable to avoid CSI feedback by exploiting UL / DL channel reciprocity. In practical systems, transmit and receive RF chains at the BTS or UE typically have different characteristics due to different RF components and circuit layout. Therefore, to preserve UL / DL reciprocity it is necessary to employ RF calibration methods to compensate for RF mismatch between transmit and receive chains.

[0434] Models for RF mismatch in typical wireless transceivers were described in [Reference 91] and hardware solutions to mitigate the effect of RF mismatch on the performance of adaptive digital beamforming systems were discussed in [Reference 92], Software techniques to enable RF calibration in multiple-input multiple-output (MIMO) systems where proposed in [References 93,94] and experimental results for multiple-input single-output (MISO) and for systems employing antenna selection where shown in [Reference 95] and [Reference 96], respectively.

[0435] Prior art, however, assumes all RF chains are collocated on the same circuit board as in MIMO systems, thereby simplifying the RF calibration problem since information about the RF mismatch between all the RF chains is available locally. By contrast, the present disclosure is made up of distributed antennas geographically placed far apart such that communication between those antennas only happens through the network. Hence, we define a novel system unit that we call “beacon station” designed specifically to enable RF calibration in MU-MASs with distributed antennas. Moreover, in prior art MIMO systems significant RF coupling between transmit / receive chains occurs due to the close proximity of the RF chains on the same board. By contrast, in the present disclosure, RF coupling occurs only between onetransmit and one receive chain of the same distributed antenna. Hence, techniques employed for RF calibration are significantly different than the ones described in prior art as we will demonstrate hereafter. Finally, the RF calibration methods disclosed in prior art were limited to systems with a single user (e.g. a single User Equipment device). As shown in the derivations at the following paragraphs, systems with multiple users (e.g., MU-MASs) are particularly sensitive to RF mismatch, since that yields inter-user interference. As such, special techniques must be employed to enable RF calibration while exploiting channel reciprocity, as described below.

[0436] The present disclosure is made up of a MU-MAS that employs radio frequency (RF) calibration and exploits reciprocity between downlink (DL) and uplink (UL) channels, comprising of multiple distributed antennas, multiple User Equipment devices (UEs) and one or multiple beacon stations. In one embodiment, the RF calibration is employed to compute the DL MU-MAS precoding weights from the UL channel estimates. Figure 16 shows the block diagram of the system including the distributed antennas 1601, multiple UEs 1613, one beacon station 1619, one base station network (BSN) 1607 connecting the distributed antennas, one centralized processor (CP) 1621 and one feedback channel 1620, that is the calibration control channel from the beacon to the CP.

[0437] Every distributed antenna unit is made up of baseband unit 1602, transmit RF chain 1603, receive RF chain 1604, RF switch unit 1605 that dynamically selects transmit / receive RF chains for TDD operation, and antenna 1606. In one embodiment, the baseband unit comprises baseband signal processing and digital-to-analog converter (DAC). In another embodiment, all the baseband processing is executed at the CP such that RF signal is sent to every distributed antenna (e.g., via RF coax cables or RF over fiber networks). Every UE is made up of baseband unit 1608, transmit / receive RF chains 1609 and 1610, respectively, RF switch 1611 and antenna 1612. The beacon station is composed of baseband unit 1614, transmit / receive RF chains 1615 and 1616, respectively, RF switch 1617 and antenna 1618.

[0438] The wireless links between the distributed antennas and the UEs are modeled as complex Gaussian channel matrix H of dimensions MxN, where M is the number of UEs and N is the number of distributed antennas. We define HDL the DL channel matrix 1622 and HUL the UL channel matrix 1623. Channel reciprocity holds as long as DL and UL are set to the same carrier frequency. In this case, the following property holdsHDL= H†UL= Hwhere the symbol f denotes the transpose matrix operation.

[0439] The model above holds for either single-carrier or multicarrier systems. In multicarrier systems (e.g., OFDM) the complex matrix H represents the channel of one subcarrier, and the same model extends to any subcarrier in the system. Figure 16 also shows transmit and receive RF units at the distributed antennas, modeled with complex channel matrices AT and AR, respectively, of dimension NxN. Likewise, the transmit and receive RF units at the UEs are modeled by the matrices BT and BR, respectively, of dimension MxM. In the case of MU-MAS with distributed antennas, RF coupling between distributed antennas and / or UEs is negligible due to relative antenna separation, such that AT, AR, BT and BR are represented as diagonal matrices. We observe this is a unique feature of MU-MAS with distributed antennas and distributed UEs. As such, the present disclosure is novel over prior art related to multiple-input multiple-output (MIMO) systems.

[0440] Based on the block diagram in Figure 16, we write the effective DL channel matrix (modeling transmit / receive RF units and wireless links) asH̄DL= BRHDLAT= BRH ATand the effective UL channel matrix asH̄UL= ARHULBT= ARH†BTIn the present disclosure, RF calibration is obtained by preconditioning the matrix of the UL channel estimates HULwith the complex RF calibration matrix C, as follows HDL= (C HUL) tIn one embodiment of the disclosure comprising LTE cellular networks, the effective UL channel is estimated at the eNodeB employing the DMRS from all UEs.

[0441] As shown in Figure 17, the matrix C is computed from the effective DL (kDL) channel 1722 and UL (k^) channel 1723 vectors between every distributed antenna 1701 and the beacon station 1719, defined ask̄DL= DRkDLATandk̄UL= ARkULDTwhere kDL= kUL= k are column vectors, assuming DL and UL channel reciprocity between the distributed antennas and the beacon station. In one embodiment, the DL channel between the distributed antennas and the beacon station is estimated bysending training signals from the distributed antennas to the beacon. In one exemplary embodiment comprising LTE cellular networks, the DL sequences CRS, or CSI-RS, or DM-RS are used by the beacon to estimate the effective DL channel from all eNodeBs. In the same embodiment, the UL channel between the beacon station and the distributed antennas is estimated by sending training signals from the beacon station to the antennas. In one embodiment of the disclosure, multiple beacon stations are employed to improve the estimation of the RF calibration matrix. In the present disclosure, there is no RF coupling between the distributed antennas, such that the RF calibration matrix C is diagonal.

[0442] When linear precoding (e.g., zero-forcing [Reference 65], blockdiagonalization or BD [References 66-67], matrix inversion, etc.) is employed, the symbol received at the m-th UE is given byM^DL,m ^DL,m $m + ' ^DL,m ^DL,u $u +u=l,u^mwhere hDLmis the m-th row of the effective channel matrix HDL, wDL mis the precoding vector for the m-th UE derived from HDL, smis the symbol transmitted to the m-th UE and nmis white Gaussian noise at the m-th UE. For the sake of simplicity, the above model assumes a single receive antenna at every UE, but the present disclosure extends to any number of antennas at the UE. It is possible to show that when the RF calibration method described above is employed the inter-client interference at every UE is pre-cancelled at the transmitter such that the following condition holds ^DL,m ™DL,u = ^DL,m ™DL,u = 0, V U = 1,..., M with U #= m where wDLuis the precoding weight vector derived from the RF calibrated channel matrix HDL. In one embodiment, the precoding weights are computed from the RF calibrated channel matrix to pre-cancel inter-client interference at every UE. Figure 18 shows the symbol error rate (SER) performance of MU-MAS employing BD precoding and 4-QAM modulation in frequency-flat channels for three scenarios: i) no RF mismatch; ii) RF mismatch without calibration; iii) RF mismatch with calibration. We observe the RF calibration method in the present disclosure reduces the SER down to ideal performance (i.e., with no RF mismatch).

[0443] In another embodiment of the disclosure, non-linear precoding methods (e.g., dirty-paper coding [References 68-70] or Tomlinson-Harashima precoding or THP [References 71-72], lattice techniques or trellis precoding [References 73-74],vector perturbation techniques [References 75-76]) are applied to the RF calibrated channel matrix to pre-cancel inter-client interference at every UE. Figure 19 shows that the SER obtained with non-linear precoding techniques using RF calibration and UL / DL reciprocity matches the performance of linear precoding. Figure 20A shows the constellation before THP modulo operation for UE 1, whereas Figure 20B shows the constellation before THP modulo operation for UE 2 (THP lattice structure) in MU-MAS with two distributed antennas and two UEs. THP precoding is designed to completely cancel interference to the “reference-UE” and applies successive interference cancellation schemes to the other UEs. As such it is expected the SER performance for the reference-UE may be better than the other UEs. In one embodiment, Round-Robin or proportional fair scheduling or other types of scheduling techniques are applied to the UEs to guarantee similar average SER performance to all UEs.

[0444] The computational performance of BD and THP methods may vary depending on the number of distributed antennas and / or UEs within every usercluster. In one embodiment of the disclosure, the MU-MAS dynamically switches between linear and non-linear precoding techniques to minimize the computational complexity of the precoder, depending on the number of distributed antennas and / or UEs in every user-cluster.

[0445] In practical MU-MASs, the beacon station is a wireless transceiver dedicated to the use for RF calibration. Since the beacon requires feedback channel to communicate the estimated effective DL channel from all distributed antennas for calibration purposes, the beacon communicates to the CP via wireless or wireline link. In another embodiment, the beacon station is any of the distributed antennas, and the calibration parameters are computed with respect to that antenna. In the same embodiment, the distributed antennas are organized as in a mesh network and pair-wise RF calibration between adjacent distributed antennas is computed to guarantee good link quality. The RF calibration is carried across all antennas and calibration information is fed back to the CP such that all distributed antennas are calibrated with one another. In another embodiment, the beacon is any of the UEs that use any wireless or wireline link to feedback calibration information to the CP.

[0446] The calibration information from the beacon to the CP is quantized over limited number of bits or sent via codebook-based limited feedback methods to reduce overhead over the control channel. We observe that RF calibration can be run at aslow rate (depending on the rate of variation of the RF characteristics, due to temperature changes, etc.). If the rate of update of the calibration information is low, the wireless data channel can be used to send that information to the CP without causing any severe loss of data rate. In one exemplary embodiment, in LTE cellular networks the PUSCH is used to feedback calibration information from the UE to the CP.

[0447] One or multiple geographically distributed beacons are employed per usercluster, or antenna-cluster or antenna-subcluster depending on the relative link quality between the beacon and the distributed antennas in that cluster. In one embodiment, the beacon with the best signal quality to all distributed antennas in the cluster is used for RF calibration. In another embodiment, the beacons are dynamically selected at every instance of time to adapt to the changing quality of the links to the distributed antennas due to variations in the propagation environment. In another embodiment, multiple beacons are employed cooperatively (e.g., via maximum ratio combining / transmission) to maximize the SNR or SINR over the links from / to the distributed antennas. In a different embodiment, one or more RF calibrations are carried out per cluster.

[0448] In one embodiment of the disclosure, the beacon station is used not only for RF calibration but also to send signaling information to the distributed antennas and / or UEs including time and frequency synchronization reference. The distributed antennas and / or UEs employ that reference to maintain time and frequency synchronization with the MU-MAS master reference clock. In one embodiment, this reference clock distribution from the beacon to the distributed antennas and UEs is enabled via the LTE multimedia broadcast single frequency network (MBSFN) communication channel.

[0449] The present application discloses systems and methods to deliver multiple simultaneous non-interfering data streams within the same frequency band between a network and a plurality of volumes of coherence in a wireless link through Virtual Radio Instances (VRIs). In one embodiment, the system is a multiuser multiple antenna system (MU-MAS) as depicted in Figure 21. The color-coded units in Figure 21 show one-to-one mapping between the data sources 2100, the VRIs 2106 and the volumes of coherence 2103 as described hereafter.

[0450] In Figure 21, the data sources 2100 are data files or streams carrying web content or files in a local or remote server, such as text, images, sounds, videos or combinations of those. One or multiple data files or streams are sent or received between the network 2102 and every volume of coherence 2103 in the wireless link 2110. In one embodiment the network is the Internet or any wireline or wireless local area network. Element 2103 will be interchangeably referred to herein as a volume of coherence, an independent channel, or a pCell, and may be used in the singular or plural (when referring to multiple independent instances).

[0451] The volume of coherence is a volume in space where the waveforms in the same frequency band from different antennas of the MU-MAS add up coherently in a way that only the data stream 2112 of one VRI is received within that volume of coherence, without any interference from other data outputs from other VRIs sent simultaneously over the same wireless link. In the present application, we use the term “volume of coherence” to describe “personal cells” (e.g., “pCells®” 2103), previously disclosed using the phrase “areas of coherence” in previous patent applications, such as U. S. Patent No. 10,277,290, entitled “Systems and Methods to Exploit Areas of Coherence in Wireless Systems.” In one embodiment, the volumes of coherence correspond to the locations of the user equipment (UE) 2111 or subscribers of the wireless network, such that every subscriber is associated to one or multiple data sources 2100. The volumes of coherence may vary in size and shape depending on propagation conditions as well as the type of MU-MAS precoding techniques employed to generate them. In one embodiment of the disclosure, the MU-MAS precoder dynamically adjusts size, shape and location of the volumes of coherence, thereby adapting to the changing propagation conditions to deliver content to the users with consistent quality of service.

[0452] The data sources 2100 are first sent through the Network 2102 to the Radio Access Network (RAN) 2101. Then, the RAN translates the data files or streams into a data format that can be received by the UEs at UE locations 2111 and sends the data files or streams simultaneously to the plurality of volumes of coherence, such that every UE receives its own data files or streams without interference from other data files or streams sent to other UEs. In one embodiment, the RAN 2101 is made up of a gateway 2105 as the interface between the network and the VRIs 2106. The VRIs translates packets being routed by the gateway into data streams 2112, either as raw data, or in a packet or frame structure that are fed to a MU-MAS baseband unit. In oneembodiment, the VRI comprises the open systems interconnection (OSI) protocol stack made up of several layers: application, presentation, session, transport, network, data link and physical, as depicted in Figure 22A. In another embodiment, the VRI only comprises a subset of the OSI layers.

[0453] In another embodiment, the VRIs 2106 are defined from different wireless standards. By way of example, but not limitation, a first VRI is made up of the protocol stack from the GSM standard, a second VRI from the 3G standard, a third VRI from HSPA+ standard, a fourth VRI from the LTE standard, a fifth VRI from the LTE-A standard and a sixth VRI from the Wi-Fi standard. In an exemplary embodiment, the VRIs comprise the control-plane or user-plane protocol stack defined by the LTE standards. The user-plane protocol stack is shown in Figure 22B. Every UE 2202 communicates with its own VRI 2204 through the PHY, MAC, RLC and PDCP layers, with the gateway 2203 through the IP layer and with the network 2205 through the application layer, and despite the fact that, using prior art techniques, different wireless standards are spectrum-incompatible and could not concurrently share the same spectrum, by implementing different wireless standards in different VRIs in this embodiment, all of the wireless standards concurrently share the same spectrum and further, each link to a user device can utilize the full bandwidth of the spectrum concurrently with the other user devices, regardless of which wireless standards are used for each user device. Different wireless standard have different characteristics. For example, Wi-Fi is very low latency, GSM requires only one user device antenna, whereas LTE requires a minimum of two user device antennas. LTE-Advanced supports high-order 256-QAM modulation. Bluetooth Low Energy is inexpensive and very low power. New, yet unspecified standards may have other characteristics, including low latency, low power, low cost, high-order modulation. For the controlplane protocol stack, the UE also communicates directly with the mobility management entity (MME) through the NAS (as defined in the LTE standard stack) layer.

[0454] The Virtual Connection Manager (VCM) 2107 is responsible for assigning the PHY layer identity of the UEs (e.g., cell-specific radio network temporary identifier, C-RNTI) as well as instantiating, authenticating and managing mobility of the VRIs and mapping one or more C-RNTIs to VRIs for the UEs. The data streams 2112 at the output of the VRIs are fed to the Virtual Radio Manager (VRM) 2108. The VRM comprises a scheduler unit (that schedules DL (downlink) and UL (uplink) packets for different UEs), a baseband unit (e.g., comprising of FEC encoder / decoder,modulator / demodulator, resource grid builder) and a MU-MAS baseband processor (comprising of matrix transformation, including DL precoding or UL post-coding methods). In one embodiment, the data streams 2112 are l / Q samples at the output of the PHY layer in Figure 22B that are processed by the MU-MAS baseband processor. The data streams 2112 of l / Q samples may be a purely digital waveform (e.g. LTE, GSM), a purely analog waveform (e.g. FM radio with no digital modulation, a beacon, or a wireless power waveform), or a mixed analog / digital waveform (e.g. FM radio embedded with Radio Data System data, AMPS) at the output of the PHY layer that are processed by the MU-MAS baseband processor. In a different embodiment, the data streams 2112 are MAC, RLC or PDCP packets sent to a scheduler unit that forwards them to a baseband unit. The baseband unit converts packets into l / Q fed to the MU-MAS baseband processor. Thus, either as l / Q samples themselves, or converted from packets to l / Q samples, the data streams 2112 result in a plurality of digital waveforms that are processed by the MU-MAS baseband processor.

[0455] The MU-MAS baseband processor is the core of the VRM 2108 in Figure 21 that converts the M l / Q samples from the M VRIs into N data streams 2113 sent to N access points (APs) 2109. In one embodiment, the data streams 2113 are l / Q samples of the N waveforms transmitted over the wireless link 2110 from the APs 2109. In this embodiment the AP is made up of ADC / DAC, RF chain and antenna. In a different embodiment, the data streams 2113 are bits of information and MU-MAS precoding information that are combined at the APs to generate the N waveforms sent over the wireless link 2110. In this embodiment, every AP is equipped with a CPU, DSP or SoC to carry out additional baseband processing before the ADC / DAC units. In one embodiment the data streams 2113 are bits of information and MU-MAS precoding information that are combined at the APs to generate the N waveforms sent over the wireless link 2110 that have a lower data rate than data streams 2113 that are l / Q samples of the N waveforms. In one embodiment lossless compression is used to reduce the data rate of data streams 2113. In another embodiment lossy compression is used to reduce the data rate of data streams.8. Supporting Mobility and Handoff

[0456] The systems and methods described thus far work as long the UEs are within reach of the APs. When the UEs travel away from the AP coverage area the link may drop and the RAN 2301 as illustrated in Figure 23 is unable to create volumesof coherence. To extend the coverage area, the systems can gradually evolve by adding new APs. There may not be enough processing power in the VRM, however, to support the new APs or there may be practical installation issues to connect the new APs to the same VRM. In these scenarios, it is necessary to add adjacent RANs 2302 and 2303 to support the new APs as depicted in Figure 23.

[0457] In one embodiment a given UE is located in the coverage area served by both the first RAN 2301 and the adjacent RAN 2302. In this embodiment, the adjacent RAN 2302 only carries out MU-MAS baseband processing forthat UE, jointly with the MU-MAS processing from the first RAN 2301. No VRI is handled by the adjacent RAN 2302 for the given UE, since the VRI forthat UE is already running within the first RAN 2301. To enable joint precoding between the first and adjacent RANs, baseband information is exchanged between the VRM in the first RAN 2301 and the VRM in the adjacent RAN 2302 through the cloud-VRM 2304 and the links 2305. The links 2305 are any wireline (e.g., fiber, DSL, cable) or wireless link (e.g., line-of-sight links) that can support adequate connection quality (e.g. low enough latency and adequate data rate) to avoid degrading performance of the MU-MAS precoding.

[0458] In a different embodiment a given UE moves out of the coverage area of the first RAN 2301 into the coverage area of the adjacent RAN 2303. In this embodiment the VRI associated to that UE is “teleported” from the first RAN 2301 to the adjacent RAN 2303. What is meant by the VRI being teleported or “VRI teleportation” is the VRI state information is transferred from RAN 2301 to RAN 2303, and the VRI ceases to execute within RAN 2301 and begins to execute within RAN 2303. Ideally, the VRI teleportation occurs fast enough that, from the perspective of the UE served by the teleported VRI, it does not experience any discontinuity in its data stream from the VRI. In one embodiment, if there is a delay before the VRI is fully executing after being teleported, then before the VRI teleportation begins, the UE served by that VRI is put into a state where it will not drop its connection or otherwise enter an undesirable state until the VRI starts up at the adjacent RAN 2303, and the UE once again is served by an executing VRI. “VRI teleportation” is enabled by the cloud-VCM 2306 that connects the VCM in the first RAN 2301 to the VCM in the adjacent RAN 2303. The wireline or wireless links 2307 between VCM do not have the same restrictive performance constraints as the links 2305 between VRMs, since the links 2307 only carry data and do not have any effect on performance of the MU-MAS precoding. In the same embodiment of the disclosure, additional links 2305 areemployed between the first RAN 2301 and the adjacent RAN 2303 to connect their VRMs that can support adequate connection quality (e.g. low enough latency and adequate data rate) to avoid degrading performance of the MU-MAS precoding. In one embodiment of the disclosure, the gateways of the first and adjacent RANs are connected to the cloud-gateway 2308 that manages all network address (or IP address) translation across RANs.

[0459] In one embodiment of the disclosure, VRI teleportation occurs between the RAN 2401 disclosed in the present application and any adjacent wireless network 2402 as depicted in Figure 24. By way of example, but not limitation, the wireless network 2402 is any conventional cellular (e.g., GSM, 3G, HSPA+, LTE, LTE-Advanced, CDMA, WiMAX, AMPS) or wireless local area network (WLAN, e.g., WiFi). By way of example, but not limitation, the wireless protocol can also be broadcast digital or analog protocols, such as ATSC, DVB-T, NTSC, PAL, SECAM, AM or FM radio, with or without stereo or RDS, or broadcast carrier waveforms for any purpose, such as for timing reference or beacons. Or the wireless protocol can create waveforms for wireless power transmission, for example, to be received by a rectifying antenna, such as those described in U. S. patents 7,451,839, 8,469,122, and 8,307,922. As the VRI is teleported from the RAN 2401 to the adjacent wireless network 2402 the UE is handed off between the two networks and its wireless connection may continue.

[0460] In one embodiment, the adjacent wireless network 2402 is the LTE network shown in Figure 25. In this embodiment, the Cloud-VCM 2502 is connected to the LTE mobility management entity (MME) 2508. All the information about identity, authentication and mobility of every UE handing-off between the LTE and the RAN 2501 networks is exchanged between the MME 2508 and the cloud-VCM 2502. In the same embodiment, the MME is connected to one or multiple eNodeBs 2503 connecting to the UE 2504 through the wireless cellular network. The eNodeBs are connected to the network 2507 through the serving gateway (S-GW) 2505 and the packet data network gateway (P-GW) 2506.9. Systems and Methods for DL and UL MU-MAS processing

[0461] Typical downlink (DL) wireless links are made up of broadcast physical channels carrying information for the entire cell and dedicated physical channels with information and data for given UE. For example, the LTE standard defines broadcastchannels such as P-SS and S-SS (used for synchronization at the UE), MIB and PDCCH as well as channels for carrying data to given UE such as the PDSCH. In one embodiment of the present disclosure, all the LTE broadcast channels (e.g., P-SS, S-SS, MIC, PDCCH) are precoded such that every UE receives its own dedicated information. In a different embodiment, part of the broadcast channel is precoded and part is not. By way of example, but not limitation, the PDCCH contains broadcast information as well as information dedicated to one UE, such as the DCI 1A and DCI 0 used to point the UEs to the resource blocks (RBs) to be used over DL and uplink (UL) channels. In one embodiment, the broadcast part of the PDCCH is not precoded, whereas the portion containing the DCI 1 A and 0 is precoded in such a way that every UE obtains its own dedicated information about the RBs that carry data.

[0462] In another embodiment of the disclosure precoding is applied to all or only part of the data channels, such as the PDSCH in LTE systems. By applying precoding over the entire data channel, the MU-MAS disclosed in the present disclosure allocates the entire bandwidth to every UE and the plurality of data streams of the plurality of UEs are separated via spatial processing. In typical scenarios, however, most, if not all, of the UEs do not need the entire bandwidth (e.g., ~55 Mbps per UE, peak DL data rate for TDD configuration #2 and S-subframe configuration #7, in 20MHz of spectrum). Then, the MU-MAS in the present disclosure subdivides the DL RBs in multiple blocks as in frequency division multiple access (FDMA) or orthogonal frequency division multiple access (OFDMA) systems and assigns each FDMA or OFMDA block to a subset of UEs. All the UEs within the same FDMA or OFDMA block are separated into different volumes of coherence through the MU-MAS precoding. In another embodiment, the MU-MAS allocates different DL subframes to different subsets of UEs, thereby dividing up the DL as in TDMA systems. In yet another embodiment, the MU-MAS both subdivides the DL RBs in multiple blocks as in OFDMA systems among subsets of UEs and also allocates different DL subframes to different subsets of UEs as in TDMA systems, thus utilizing both OFDMA and TDMA to divide up the throughput. For example, if there are 10 APs in a TDD configuration #2 in 20 MHz, then there is an aggregate DL capacity of 55 Mbps * 10 = 550 Mbps. If there are 10 UEs, then each UE could receive 55 Mbps concurrently. If there are 200 UEs, and the aggregate throughput is to be divided up equally, then using OFDMA, TDMA or a combination thereof, the 200 UEs would be divided into 20 groups of 10 UEs, whereby each UE would receive 550 Mbps / 200 = 2.75 Mbps. As anotherexample, if 10 UEs required 20 Mbps, and the other UEs were to evenly share the remaining throughput, then 20 Mbps * 10 = 200 Mbps of the 550 Mbps would be used for 10 UEs, leaving 550 Mbps - 200 Mbps = 350 Mbps to divide among the remaining 200-10=190 UEs. As such, each of the remaining 90 UEs would receive 350 Mbps / 190 = 1.84 Mbps. Thus, far more UEs than APs can be supported in the MU-MAS system of the present application, and the aggregate throughput of all the APs can be divided among the many UEs.

[0463] In the UL channel, the LTE standard defines conventional multiple access techniques such as TDMA or SC-FDMA. In the present disclosure, the MU-MAS precoding is enabled over the DL in a way to assign UL grants to different UEs to enable TDMA and SC-FDMA multiple access techniques. As such, the aggregate UL throughput can be divided among far more UEs than there are APs.

[0464] When there are more UEs than there are APs and the aggregate throughput is divided among the UEs, as described above, in one embodiment, the MU-MAS system supports one VRI for each UE, and the VRM controls the VRIs such that VRIs utilize RBs and resource grants in keeping with the chosen OFDMA, TDMA or SC-FDMA system(s) used to subdivide the aggregate throughput. In another embodiment, one or more individual VRIs may support multiple UEs and manage the scheduling of throughput among these UEs via OFDMA, TDMA or SC-FDMA techniques.

[0465] In another embodiment, the scheduling of throughput is based on load balancing of user demand, using any of many prior art techniques, depending upon the policies and performance goals of the system. In another embodiment, scheduling is based upon Quality of Service (QoS) requirements for particular UEs (e.g. UEs used by subscribers that pay for a particular tier of service, guaranteeing certain throughput levels) or for particular types of data (e.g. video for a television service).

[0466] In a different embodiment, uplink (UL) receive antenna selection is applied to improve link quality. In this method, the UL channel quality is estimated at the VRM based on signaling information sent by the UEs (e.g., SRS, DMRS) and the VRM decides the best receive antennas for different UEs over the UL. Then the VRM assigns one receive antenna to every UE to improve its link quality. In a different embodiment, receive antenna selection is employed to reduce cross-interference between frequency bands due to the SC-FDMA scheme. One significant advantage of this method is that the UE would transmit over the UL only to the AP closest to itslocation. In this scenario, the UE can significantly reduce its transmit power to reach the closest AP, thereby improving battery life. In the same embodiment, different power scaling factors are utilized for the UL data channel and for the UL signaling channel. In one exemplary embodiment, the power of the UL signaling channel (e.g., SRS) is increased compared to the data channel to allow UL CSI estimation and MU-MAS precoding (exploiting UL / DL channel reciprocity in TDD systems) from many APs, while still limiting the power required for UL data transmission. In the same embodiment, the power levels of the UL signaling and UL data channels are adjusted by the VRM through DL signaling based on transmit power control methods that equalize the relative power to / from different UEs.

[0467] In a different embodiment, maximum ratio combining (MRC) is applied at the UL receiver to improve signal quality from every UE to the plurality of APs. In a different embodiment, zero-forcing (ZF) or minimum mean squared error (MMSE) or successive interference cancellation (SIC) or other non-linear techniques or the same precoding technique as for the DL precoding are applied to the UL to differentiate data streams being received simultaneously and within the same frequency band from different UEs’ volumes of coherence. In the same embodiment, receive spatial processing is applied to the UL data channel (e.g., PUSCH) or UL control channel (e.g., PUCCH) or both.10. Additional embodiments

[0468] In one embodiment, the volume of coherence, or pCell as described above, of a first UE is the volume in space wherein the signal intended for the first UE has high enough signal-to-interference-plus-noise ratio (SINR) that the data stream for the first UE can be demodulated successfully, while meeting predefined error rate performance. Thus, everywhere within the volume of coherence, the level of interference generated by data streams sent from the plurality of APs to the other UEs is sufficiently low that the first UE can demodulate its own data stream successfully.

[0469] In another embodiment, the volume of coherence or pCell is characterized by one specific electromagnetic polarization, such as linear, circular or elliptical polarization. In one embodiment, the pCell of a first UE is characterized by linear polarization along a first direction and the pCell of a second UE overlaps the pCell of the first UE and is characterized by linear polarization along a second direction orthogonal to the first direction of the first UE, such that the signals received at the two UEs do not interfere with one another. By way of example, but not limitation, a first UEpCell has linear polarization along the x-axis, a second UE pCell has linear polarization along the y-axis and a third UE pCell has linear polarization along the z-axis (wherein x-, y- and z-axes are orthogonal) such that the three pCells overlap (i.e., are centered at the same point in space) but the signals of the three UEs do not interfere because their polarizations are orthogonal.

[0470] In another embodiment, every pCell is uniquely identified by one location in three dimensional space characterized by (x,y,z) coordinates and by one polarization direction defined as linear combination of the three fundamental polarizations along the x-, y- and z-axes. As such, the present MU-MAS system is characterized by six degrees of freedom (i.e., three degrees of freedom from the location in space and three from the direction of polarization), which can be exploited to create a plurality of non-interfering pCells to different UEs.

[0471] In one embodiment, the VRIs, as described in the above paragraphs, are independent execution instances that run on one or multiple processors. In another embodiment, every execution instance runs either on one processor, or on multiple processors in the same computer system, or on multiple processors in different computer systems connected through a network. In another embodiment, different execution instances run either on the same processor, or different processors in the same computer system, or multiple processors in different computer systems. In another embodiment, the processor is a central processing unit (CPU), or a core processor in a multi-core CPU, or an execution context in a hyper-threaded core processor, or a graphics processing unit (GPU), or a digital signal processor (DSP), or a field-programmable gate array (FPGA), or an application-specific integrated circuit.

[0472] Embodiments of the disclosure may include various steps, which have been described above. The steps may be embodied in machine-executable instructions which may be used to cause a general-purpose or special-purpose processor to perform the steps. Alternatively, these steps may be performed by specific hardware components that contain hardwired logic for performing the steps, or by any combination of programmed computer components and custom hardware components.

[0473] As described herein, instructions may refer to specific configurations of hardware such as application specific integrated circuits (ASICs) configured to perform certain operations or having a predetermined functionality or software instructions stored in memory embodied in a non-transitory computer readable medium. Thus, thetechniques shown in the figures can be implemented using code and data stored and executed on one or more electronic devices. Such electronic devices store and communicate (internally and / or with other electronic devices over a network) code and data using computer machine-readable media, such as non-transitory computer machine-readable storage media (e.g., magnetic disks; optical disks; random access memory; read only memory; flash memory devices; phase-change memory) and transitory computer machine-readable communication media (e.g., electrical, optical, acoustical or other form of propagated signals - such as carrier waves, infrared signals, digital signals, etc.).

[0474] Throughout this detailed description, for the purposes of explanation, numerous specific details were set forth in order to provide a thorough understanding of the present disclosure. It will be apparent, however, to one skilled in the art that the disclosure may be practiced without some of these specific details. In certain instances, well known structures and functions were not described in elaborate detail in order to avoid obscuring the subject matter of the present disclosure. Accordingly, the scope and spirit of the disclosure should be judged in terms of the claims which follow.

[0475] The following additional details are provided to further illustrate the precoding and modulation techniques employed by embodiments of the disclosure.

[0476] First, the mathematical model and framework of the disclosure will be described.

[0477] Before presenting the solution, it is useful to explain the core mathematical concept. We explain it assuming l / Q gain and phase imbalance (phase delay is not included in the description but is dealt with automatically in the DIDO-OFDM version of the algorithm). To explain the basic idea, suppose that we want to multiply two complex numbers s = si + jso and h = hi + jho and let x = h * s. We use the subscripts to denote inphase and quadrature components. Recall thatXi = Sihi - SohoandXQ = Siho + Sohi.

[0478] In matrix form this can be rewritten as

[0479] Note the unitary transformation by the channel matrix (H). Now suppose that s is the transmitted symbol and h is the channel. The presence of l / Q gain and phase imbalance can be modeled by creating a non-unitary transformation as follows

[0480] The trick is to recognize that it is possible to write

[0481] Now, rewriting (A)

[0482] Let us defineand

[0483] Both of these matrices have a unitary structure thus can be equivalently represented by complex scalars asheh \ i "4" "4* J (^21 — -^12 Iandhc“ / ijj — Ji-22 *4~ J (^21 + ^12 )-

[0484] Using all of these observations, we can put the effective equation back in a scalar form with two channels: the equivalent channel heand the conjugate channel hc. Then the effective transformation in (5) becomesx— + k,(.*4*

[0485] We refer to the first channel as the equivalent channel and the second channel as the conjugate channel. The equivalent channel is the one you would observe if there were no l / Q gain and phase imbalance.

[0486] Using similar arguments, it can be shown that the input-output relationship of a discrete-time MIMO NxM system with l / Q gain and phase imbalance is (using the scalar equivalents to build their matrix counterparts)^=0where t is the discrete time index, he,hcc('"&s=[xl,..,.' ],x=and L is the number of channel taps.

[0487] In DIDO-OFDM systems, the received signal in the frequency domain is represented. Recall from signals and systems that ifF 7 { [ / ]} = [£] then FFTK{s*[r]}= £*[(-£)] = s* \K-k\for k = 0,l,..., / f -l.With OFDM, the equivalent input-output relationship for a MIMO-OFDM system for subcarrier k isx[ ]= HJi]sW + H^]s '[A-£] (1)where k= 0, 1,..., K- 1 is the OFDM subcarrier index, Heand Hcdenote the equivalent and conjugate channel matrices, respectively, defined asandL HJ£] =Xhc [^e’'7”F1=0

[0488] The second contribution in (1 ) is interference from the mirror tone. It can be dealt with by constructing the following stacked matrix system (note carefully the conjugates)xU -il] H*[AT-£] HX -^JLS'K-^]where s = 51,52 J and x= [x x2J are the vectors of transmit and receive symbols in the frequency domain, respectively.

[0489] Using this approach, an effective matrix is built to use for DIDO operation. For example, with DIDO 2 x 2 the input-output relationship (assuming each user has a single receive antenna) the first user device sees (in the absence of noise)5i [A]*1M H«[^] H^[A] 5* [AT - k\W (2)xf[A? -k\ 52^]52^ -k]while the second user observes51 [£] X2[£] H? UI H®[£]w 51 [^ -£](3)x’.\K -k] H^3)*[^ -£J H^2|*[A7 — A] 52 [£]52^ ~ k]whereGC112denote the m-th row of the matrices Heand Hc, respectively, and w eC4x4is the DIDO pre-coding matrix. From (2) and (3) it is observed that the received symbol x„, [4] of usermis affected by two sources of interference caused by l / Q imbalance: inter-carrier interference from the mirror tone (i.e.,and inter-user interference (i.e., 5P[^]ar|d with The DIDO precoding matrix W in (3) is designed to cancel these two interference terms.

[0490] There are several different embodiments of the DIDO precoder that can be used here depending on joint detection applied at the receiver. In one embodiment, block diagonalization (BD) is employed (see, e.g., Q. H. Spencer, A. L. Swindlehurst, and M. Haardt, “Zeroforcing methods for downlink spatial multiplexing in multiuser MIMO channels,” IEEE Trans. Sig. Proc., vol. 52, pp. 461-471, Feb. 2004. K. K. Wong, R. D. Murch, and K. B. Letaief, “A joint channel diagonalization for multiuser MIMO antenna systems,” IEEE Trans. Wireless Comm., vol. 2, pp. 773-786, Jul 2003 (Reference

[0066] ). L. U. Choi and R. D. Murch, “A transmit preprocessing technique for multiuser MIMO systems using a decomposition approach,” IEEE Trans. Wireless Comm., vol. 3, pp. 20-24, Jan 2004. Z. Shen, J. G. Andrews, R. W. Heath, and B. L. Evans, “Low complexity user selection algorithms for multiuser MIMO systems with block diagonalization,” accepted for publication in IEEE Trans. Sig. Proc., Sep. 2005. Z. Shen, R. Chen, J. G. Andrews, R. W. Heath, and B. L. Evans, “Sum capacity of multiuser MIMO broadcast channels with block diagonalization,” submitted to IEEE Trans. Wireless Comm., Oct. 2005, computed from the composite channel(rather than Hm)). So, the current DIDO system chooses the precoder such thatwhere at Jare constants and e C2×2. This method is beneficial because using this precoder, it is possible to keep other aspects of the DIDO precoder the same as before, since the effects of l / Q gain and phase imbalance are completely cancelled at the transmitter.

[0491] It is also possible to design DIDO precoders that pre-cancel inter-user interference, without pre-cancelling ICI due to IQ imbalance. With this approach, the receiver (instead of the transmitter) compensates for the IQ imbalance by employing one of the receive filters described below. Then, the pre-coding design criterion in (4) can be modified as0 w =a2 ” 0 (5) H2|^ | H>^| 0 «• H'2)*[^-£] H<2)*[^-£](6)andX2M-[^21)ni-

[0492] whereS,„[A] = [. S„,[A-],. SL[A' A]]' for the m-th transmit symbol and x #]=[xm[ ],xm[ / -A]]7is the receive symbol vector for user m.

[0493] At the receive side, to estimate the transmit symbol vector sm[ ], user m employs ZF filter and the estimated symbol vector is given bys^W[(4'”’”')t(8)

[0494] While the ZF filter is the easiest to understand, the receiver may apply any number of other filters known to those skilled in the art. One popular choice is the MMSE filter where[£] = ( + p ’z) (9)and p is the signal-to-noise ratio. Alternatively, the receiver may perform a maximum likelihood symbol detection (or sphere decoder or iterative variation). For example, the first user might use the ML receiver and solve the following optimizations^L)M = arg min | || (10IIy 1 [£]- [ «(U))where S is the set of all possible vectors s and depends on the constellation size. The ML receiver gives better performance at the expense of requiring more complexity at the receiver. A similar set of equations applies for the second user.

[0495] Note thatand *c21)in (6) and (7) are assumed to have zero entries. This assumption holds only if the transmit precoder is able to cancel completely the inter-user interference as for the criterion in (4). Similarly,and2)are diagonal matrices only if the transmit precoder is able to cancel completely the inter-carrier interference (i.e., from the mirror tones).

[0496] Figure 26 illustrates one embodiment of a framework for DIDO-OFDM systems with l / Q compensation including IQ-DIDO precoder 2602 within a Base Station (BS), a wireless transmission channel 2604, channel estimation logic 2606 within a user device, and a ZF, MMSE or ML receiver 2608. The channel estimation logic 2606 estimates the channelsand via training symbols and feedbacks these estimates to the precoder 2602 within the AP. The BS computes the DIDO precoder weights (matrix W) to pre-cancel the interference due to l / Q gain and phase imbalance as well as inter-user interference and transmits the data to the users through the wireless channel 2604. User device m employs the ZF, MMSE or ML receiver 2608, by exploiting the channel estimates provided by the Channel Estimation unit 2606, to cancel residual interference and demodulates the data.

[0497] The following three embodiments may be employed to implement this l / Q compensation algorithm:

[0498] Method 1 - TX compensation: In this embodiment, the transmitter calculates the pre-coding matrix according to the criterion in (4). At the receiver, the user devices employ a “simplified” ZF receiver, whereand are assumed to be diagonal matrices. Hence, equation (8) simplifies as0xm[£]. (10)0

[0499] Method 2 - RX compensation: In this embodiment, the transmitter calculates the pre-coding matrix based on the conventional BD method described in R. Chen, R. W. Heath, and J. G. Andrews, “Transmit selection diversity for unitary precoded multiuser spatial multiplexing systems with linear receivers,” accepted to IEEE Trans, on Signal Processing, 2005, without canceling inter-carrier and inter-user interference as for the criterion in (4). With this method, the pre-coding matrix in (2) and (3) simplifies as0 00 w’j [£■-&] 0 W*2[AT-£](12)W2, IM 0 w22[k] 00w’JilX- k\ 0w2,2 [K ~k]

[0500] At the receiver, the user devices employ a ZF filter as in (8). Note that this method does not pre-cancel the interference at the transmitter as in the method 1 above. Hence, it cancels the inter-carrier interference at the receiver, but it is not able to cancel the inter-user interference. Moreover, in method 2 the users only need to feedback the vectorfor the transmitter to compute the DIDO precoder, as opposed to method 1 that requires feedback of bothand Therefore, method 2 is particularly suitable for DIDO systems with low rate feedback channels. On the other hand, method 2 requires slightly higher computational complexity at the user device to compute the ZF receiver in (8) rather than (11).

[0501] Method 3 - TX-RX compensation: In one embodiment, the two methods described above are combined. The transmitter calculates the pre-coding matrix as in (4) and the receivers estimate the transmit symbols according to (8).

[0502] l / Q imbalance, whether phase imbalance, gain imbalance, or delay imbalance, creates a deleterious degradation in signal quality in wireless communication systems. For this reason, circuit hardware in the past was designed to have very low imbalance. As described above, however, it is possible to correct this problem using digital signal processing in the form of transmit pre-coding and / or a special receiver. One embodiment of the disclosure comprises a system with several new functional units, each of which is important for the implementation of l / Q correction in an OFDM communication system or a DIDO-OFDM communication system.

[0503] One embodiment of the disclosure uses pre-coding based on channel state information to cancel inter-carrier interference (ICI) from mirror tones (due to l / Q mismatch) in an OFDM system. As illustrated in Figure 27, a DIDO transmitter according to this embodiment includes a user selector unit 2702, a plurality of coding modulation units 2704, a corresponding plurality of mapping units 2706, a DIDO IQ-aware precoding unit 2708, a plurality of RF transmitter units 2714, a user feedback unit 2712 and a DIDO configurator unit 2710.

[0504] The user selector unit 2702 selects data associated with a plurality of users U1-UM, based on the feedback information obtained by the feedback unit 2712, and provides this information each of the plurality of coding modulation units 2704. Each coding modulation unit 2704 encodes and modulates the information bits of each user and send them to the mapping unit 2706. The mapping unit 2706 maps the input bits to complex symbols and sends the results to the DIDO IQ-aware precoding unit 2708. The DIDO IQ-aware precoding unit 2708 exploits the channel state information obtained by the feedback unit 2712 from the users to compute the DIDO IQ-aware precoding weights and precoding the input symbols obtained from the mapping units 2706. Each of the precoded data streams is sent by the DIDO IQ-aware precoding unit 2708 to the OFDM unit 2715 that computes the IFFT and adds the cyclic prefix. This information is sent to the D / A unit 2716 that operates the digital to analog conversion and send it to the RF unit 2714. The RF unit 2714 upconverts the baseband signal to intermediate / radio frequency and send it to the transmit antenna.

[0505] The precoder operates on the regular and mirror tones together for the purpose of compensating for l / Q imbalance. Any number of precoder design criteriamay be used including ZF, MMSE, or weighted MMSE design. In a preferred embodiment, the precoder completely removes the ICI due to l / Q mismatch thus resulting in the receiver not having to perform any additional compensation.

[0506] In one embodiment, the precoder uses a block diagonalization criterion to completely cancel inter-user interference while not completely canceling the l / Q effects for each user, requiring additional receiver processing. In another embodiment, the precoder uses a zero-forcing criterion to completely cancel both inter-user interference and ICI due to l / Q imbalance. This embodiment can use a conventional DIDO-OFDM processor at the receiver.

[0507] One embodiment of the disclosure uses pre-coding based on channel state information to cancel inter-carrier interference (ICI) from mirror tones (due to l / Q mismatch) in a DIDO-OFDM system and each user employs an IQ-aware DIDO receiver. As illustrated in Figure 28, in one embodiment of the disclosure, a system including the IQ-Aware Receiver unit 2802 includes a plurality of RF units 2808, a corresponding plurality of A / D units 2810, an IQ-Aware Channel Estimate unit 2804 and a DIDO feedback generator unit 2806.

[0508] The RF units 2808 receive signals transmitted from the DIDO transmitter units 2714, downconverts the signals to baseband and provide the downconverted signals to the A / D units 2810. The A / D units 2810 then convert the signal from analog to digital and send it to the OFDM units 2813. The OFDM units 2813 remove the cyclic prefix and operates the FFT to report the signal to the frequency domain. During the training period the OFDM units 2813 send the output to the IQ-Aware Channel Estimate unit 2804 that computes the channel estimates in the frequency domain. Alternatively, the channel estimates can be computed in the time domain. During the data period the OFDM units 2813 send the output to the IQ-Aware Receiver unit 2802. The IQ-Aware Receiver unit 2802 computes the IQ receiver and demodulates / decodes the signal to obtain the data 2814. The IQ-Aware Channel Estimate unit 2804 sends the channel estimates to the DIDO feedback generator unit 2806 that may quantize the channel estimates and send it back to the transmitter via the feedback unit 2712.

[0509] The IQ-Aware Receiver unit 2802 illustrated in Figure 28 may operate under any number of criteria known to those skilled in the art including ZF, MMSE, maximum likelihood, or MAP receiver. In one preferred embodiment, the receiver uses an MMSE filter to cancel the ICI caused by IQ imbalance on the mirror tones. In another preferred embodiment, the receiver uses a nonlinear detector like a maximumlikelihood search to jointly detect the symbols on the mirror tones. This method has improved performance at the expense of higher complexity.

[0510] In one embodiment, an IQ-Aware Channel Estimate unit 2804 is used to determine the receiver coefficients to remove ICI. Consequently, we disclose a DIDO-OFDM system that uses pre-coding based on channel state information to cancel intercarrier interference (ICI) from mirror tones (due to l / Q mismatch), an IQ-aware DIDO receiver, and an IQ-aware channel estimator. The channel estimator may use a conventional training signal or may use specially constructed training signals sent on the inphase and quadrature signals. Any number of estimation algorithms may be implemented including least squares, MMSE, or maximum likelihood. The IQ-aware channel estimator provides an input for the IQ-aware receiver.

[0511] Channel state information can be provided to the station through channel reciprocity or through a feedback channel. One embodiment of the disclosure comprises a DIDO-OFDM system, with l / Q-aware precoder, with an l / Q-aware feedback channel for conveying channel state information from the user terminals to the station. The feedback channel may be a physical or logical control channel. It may be dedicated or shared, as in a random access channel. The feedback information may be generated using a DIDO feedback generator at the user terminal, which we also claim. The DIDO feedback generator takes as an input the output of the l / Q aware channel estimator. It may quantize the channel coefficients or may use any number of limited feedback algorithms known in the art.

[0512] The allocation of users, modulation and coding rate, mapping to spacetime-frequency code slots may change depending on the results of the DI DO feedback generator. Thus, one embodiment comprises an IQ-aware DIDO configurator that uses an IQ-aware channel estimate from one or more users to configure the DIDO IQ-aware precoder, choose the modulation rate, coding rate, subset of users allowed to transmit, and their mappings to space-time-frequency code slots.

[0513] To evaluate the performance of the proposed compensation methods, three DIDO 2 x 2 systems will be compared:1. With l / Q mismatch: transmit over all the tones (except DC and edge tones), without compensation for l / Q mismatch;2. With l / Q compensation: transmit over all the tones and compensate for l / Q mismatch by using the “method 1” described above;3. Ideal: transmit data only over the odd tones to avoid inter-user and inter-carrier (i.e., from the mirror tones) interference caused to l / Q mismatch.

[0514] Hereafter, results obtained from measurements with the DIDO-OFDM prototype in real propagation scenarios are presented. Figure 29 depicts the 64-QAM constellations obtained from the three systems described above. These constellations are obtained with the same users’ locations and fixed average signal-to-noise ratio (~45 dB). The first constellation 2901 is very noisy due to interference from the mirror tones caused by l / Q imbalance. The second constellation 2902 shows some improvements due to l / Q compensations. Note that the second constellation 2902 is not as clean as the ideal case shown as constellation 2903 due to possible phase noise that yields inter-carrier interference (ICI).

[0515] Figure 30 shows the average SER (Symbol Error Rate) 3001 and peruser goodput 3002 performance of DIDO 2x2 systems with 64-QAM and coding rate 3 / 4, with and without l / Q mismatch. The OFDM bandwidth is 250 KHz, with 64 tones and cyclic prefix length Lcp= 4. Since in the ideal case we transmit data only over a subset of tones, SER and goodput performance is evaluated as a function of the average per-tone transmit power (rather than total transmit power) to guarantee a fair comparison across different cases. Moreover, in the following results, we use normalized values of transmit power (expressed in decibel), since our goal here is to compare the relative (rather than absolute) performance of different schemes. Figure 30 shows that in presence of l / Q imbalance the SER saturates, without reaching the target SER (~ 10-2), consistently to the results reported in A. Tarighat and A. H. Sayed, “MIMO OFDM receivers for systems with IQ imbalances,” IEEE Trans. Sig. Proc., vol.53, pp. 3583-3596, Sep. 2005. This saturation effect is due to the fact that both signal and interference (from the mirror tones) power increase as the TX power increases. Through the proposed l / Q compensation method, however, it is possible to cancel the interference and obtain better SER performance. Note that the slight increase in SER at high SNR is due to amplitude saturation effects in the DAC, due to the larger transmit power required for 64-QAM modulations.

[0516] Moreover, observe that the SER performance with l / Q compensation is very close to the ideal case. The 2 dB gap in TX power between these two cases is due to possible phase noise that yields additional interference between adjacentOFDM tones. Finally, the curves of goodput 3002 show that it is possible to transmit twice as much data when the l / Q method is applied compared to the ideal case, since we use all the data tones rather than only the odd tones (as for the ideal case).

[0517] Figure 31 graphs the SER performance of different QAM constellations with and without l / Q compensation. We observe that, in this embodiment, the proposed method is particularly beneficial for 64-QAM constellations. For 4-QAM and 16-QAM the method for l / Q compensation yields worse performance than the case with l / Q mismatch, possibly because the proposed method requires larger power to enable both data transmission and interference cancellation from the mirror tones. Moreover, 4-QAM and 16-QAM are not as affected by l / Q mismatch as 64-QAM due to the larger minimum distance between constellation points. See A. Tarighat, R. Bagheri, and A. H. Sayed, “Compensation schemes and performance analysis of IQ imbalances in OFDM receivers,” Signal Processing, IEEE Transactions on [see also Acoustics, Speech, and Signal Processing, IEEE Transactions on], vol. 53, pp. 3257-3268, Aug. 2005. This can be also observed in Figure 31 by comparing the l / Q mismatch against the ideal case for 4-QAM and 16-QAM. Hence, the additional power required by the DIDO precoder with interference cancellation (from the mirror tones) does not justify the small benefit of the l / Q compensation for the cases of 4-QAM and 16-QAM. Note that this issue may be fixed by employing the methods 2 and 3 for l / Q compensation described above.

[0518] Finally, the relative SER performance of the three methods described above is measured in different propagation conditions. For reference, also described is the SER performance in presence of l / Q mismatch. Figure 32 depicts the SER measured for a DIDO 2 x 2 system with 64-QAM at carrier frequency of 450.5 MHz and bandwidth of 250 KHz, at two different users’ locations. In Location 1 the users are ~6A from the BS in different rooms and NLOS (Non-Line of Sight)) conditions. In Location 2 the users are ~A from the BS in LOS (Line of Sight).

[0519] Figure 32 shows that all three compensation methods always outperform the case of no compensation. Moreover, it should be noted that method 3 outperforms the other two compensation methods in any channel scenario. The relative performance of method 1 and 2 depends on the propagation conditions. It is observed through practical measurement campaigns that method 1 generally outperforms method 2, since it pre-cancels (at the transmitter) the inter-user interference caused by l / Q imbalance. When this inter-user interference is minimal,method 2 may outperform method 1 as illustrated in graph 3202 of Figure 32, since it does not suffer from power loss due to the l / Q compensation precoder.

[0520] So far, different methods have been compared by considering only a limited set of propagation scenarios as in Figure 32. Hereafter, the relative performance of these methods in ideal i.i.d. (independent and identically-distributed) channels is measured. DIDO-OFDM systems are simulated with l / Q phase and gain imbalance at the transmit and receive sides. Figure 33 shows the performance of the proposed methods with only gain imbalance at the transmit side (i.e., with 0.8 gain on the I rail of the first transmit chain and gain 1 on the other rails). It is observed that method 3 outperforms all the other methods. Also, method 1 performs better than method 2 in i.i.d. channels, as opposed to the results obtained in Location 2 in graph 3202 of Figure 32.

[0521] Thus, given the three novel methods to compensate for l / Q imbalance in DIDO-OFDM systems described above, Method 3 outperforms the other proposed compensation methods. In systems with low rate feedback channels, method 2 can be used to reduce the amount of feedback required for the DIDO precoder, at the expense of worse SER performance.

[0522] A novel adaptive DIDO transmission strategy is described herein that switches between different numbers of users, numbers of transmit antennas and transmission schemes based on channel quality information as a means to improve the system performance. Note that schemes that adaptively select the users in multiuser MIMO systems were already proposed in M. Sharif and B. Hassibi, “On the capacity of MIMO broadcast channel with partial side information,” IEEE Trans. Info. Th., vol. 51, p. 506522, Feb. 2005; and W. Choi, A. Forenza, J. G. Andrews, and R. W. Heath Jr., “Opportunistic space division multiple access with beam selection,” to appear in IEEE Trans, on Communications. The opportunistic space division multiple access (OSDMA) schemes in these publications, however, are designed to maximize the sum capacity by exploiting multi-user diversity and they achieve only a fraction of the theoretical capacity of dirty paper codes, since the interference is not completely pre-canceled at the transmitter. In the DIDO transmission algorithm described herein block diagonalization is employed to pre-cancel inter-user interference. The proposed adaptive transmission strategy, however, can be applied to any DIDO system, independently on the type of pre-coding technique.

[0523] The present patent application describes an extension of the embodiments of the disclosure described above and in the Related Patents and Applications, including, but not limited to the following additional features:1. The training symbols of the Related Patents and Applications for channel estimation can be employed by the wireless client devices to evaluate the link-quality metrics in the adaptive DIDO scheme;2. The base station receives signal characterization data from the client devices as described in the Related Patents and Applications. In the current embodiment, the signal characterization data is defined as link-quality metric used to enable adaptation;3. The Related Patents and Applications describe a mechanism to select the number of transmit antennas and users as well as defines throughput allocation. Moreover, different levels of throughput can be dynamically assigned to different clients as in the Related Patents and Applications. The current embodiment of the disclosure defines novel criteria related to this selection and throughput allocation.

[0524] Embodiments of the Disclosure

[0525] The goal of the proposed adaptive DIDO technique is to enhance per-user or downlink spectral efficiency by dynamically allocating the wireless resource in time, frequency and space to different users in the system. The general adaptation criterion is to increase throughput while satisfying the target error rate. Depending on the propagation conditions, this adaptive algorithm can also be used to improve the link quality of the users (or coverage) via diversity schemes. The flowchart illustrated in Figure 34 describes steps of the adaptive DIDO scheme.

[0526] The Base Station (BS) collects the channel state information (CSI) from all the users in 3402. From the received CSI, the BS computes the link quality metrics in time / frequency / space domains in 3404. These link quality metrics are used to select the users to be served in the next transmission as well as the transmission mode for each of the users in 3406. Note that the transmission modes are made up of different combinations of modulation / coding and DIDO schemes. Finally, the BS transmits data to the users via DIDO precoding as in 3408.

[0527] At 3402, the Base Station collects the channel state information (CSI) from all the user devices. The CSI is used by the Base Station to determine the instantaneous or statistical channel quality for all the user devices at 3404. In DIDO-OFDM systems the channel quality (or link quality metric) can be estimated in the time, frequency and space domains. Then, at 3406, the Base Station uses the link quality metric to determine the best subset of users and transmission mode for the current propagation conditions. A set of DIDO transmission modes is defined as combinations of DIDO schemes (i.e., antenna selection or multiplexing), modulation / coding schemes (MCSs) and array configuration. At 3408, data is transmitted to user devices using the selected number of users and transmission modes.

[0528] The mode selection is enabled by lookup tables (LLITs) pre-computed based on error rate performance of DIDO systems in different propagation environments. These LUTs map channel quality information into error rate performance. To construct the LUTs, the error rate performance of DIDO systems is evaluated in different propagation scenarios as a function of the SNR. From the error rate curves, it is possible to compute the minimum SNR required to achieve certain pre-defined target error rate. We define this SNR requirement as SNR threshold. Then, the SNR thresholds are evaluated in different propagation scenarios and for different DIDO transmission modes and stored in the LUTs. For example, the SER results in Figures 35 and 36 can be used to construct the LUTs. Then, from the LUTs, the Base Station selects the transmission modes for the active users that increase throughput while satisfying predefined target error rate. Finally, the Base Station transmits data to the selected users via DIDO pre-coding. Note that different DIDO modes can be assigned to different time slots, OFDM tones and DIDO substreams such that the adaptation may occur in time, frequency and space domains.

[0529] One embodiment of a system employing DIDO adaptation is illustrated in Figures 37-38. Several new functional units are introduced to enable implementation of the proposed DIDO adaptation algorithms. Specifically, in one embodiment, a DIDO Configurator unit 3710 performs a plurality of functions including selecting the number of users, DIDO transmission schemes (i.e., antenna selection or multiplexing), modulation / coding scheme (MCS), and array configurations based on the feedback unit 3712 which receives channel quality information feedback provided by user devices.

[0530] The user selector unit 3702 selects data associated with a plurality of users U1-UM, based on the feedback information obtained by the DIDO configurator unit 3710, and provides this information each of the plurality of coding modulation units 3704. Each coding modulation unit 3704 encodes and modulates the information bits of each user and sends them to the mapping unit 3706. The mapping unit 3706 maps the input bits to complex symbols and sends it to the precoding unit 3708. Both the coding modulation units 3704 and the mapping unit 3706 exploit the information obtained from the DIDO configurator unit 3710 to choose the type of modulation / coding scheme to employ for each user. This information is computed by the DIDO configurator unit 3710 by exploiting the channel quality information of each of the users as provided by the feedback unit 3712. The DIDO precoding unit 3708 exploits the information obtained by the DIDO configurator unit 3710 to compute the DIDO precoding weights and precoding the input symbols obtained from the mapping units 3706. Each of the precoded data streams are sent by the DIDO precoding unit 3708 to the OFDM unit 3715 that computes the IFFT and adds the cyclic prefix. This information is sent to the D / A unit 3716 that operates the digital to analog conversion and sends the resulting analog signal to the RF unit 3714. The RF unit 3714 upconverts the baseband signal to intermediate / radio frequency and send it to the transmit antenna.

[0531] The RF units 3808 of each client device receive signals transmitted from the DIDO transmitter units 3714, downconverts the signals to baseband and provide the downconverted signals to the A / D units 3810. The A / D units 3810 then convert the signal from analog to digital and send it to the OFDM units 3813. The OFDM units 3813 remove the cyclic prefix and carries out the FFT to report the signal to the frequency domain. During the training period the OFDM units 3813 send the output to the channel estimate unit 3804 that computes the channel estimates in the frequency domain. Alternatively, the channel estimates can be computed in the time domain. During the data period the OFDM units 3813 send the output to the receiver unit 3802 which demodulates / decodes the signal to obtain the data 3814. The channel estimate unit 3804 sends the channel estimates to the DIDO feedback generator unit 3806 that may quantize the channel estimates and send it back to the transmitter via the feedback unit 3712.

[0532] The DIDO Configurator unit 3710 may use information derived at the Base Station or, in a preferred embodiment, uses additionally the output of a DIDOFeedback Generator 3806 (see Figure 38), operating at each user device. The DIDO Feedback Generator 3806 uses the estimated channel state from channel estimate unit 3804 and / or other parameters like the estimated SNR at the receiver to generate a feedback message to be input into the DIDO Configurator unit 3710. The DIDO Feedback Generator 3806 may compress information at the receiver, may quantize information, and / or use some limited feedback strategies known in the art.

[0533] The DIDO Configurator unit 3710 may use channel quality information recovered from a DIDO Feedback Unit 3712. The DIDO Feedback Unit 3712 is a logical or physical control channel that is used to send the output of the DIDO Feedback Generator 3806 from the user to the Base Station. The DIDO Feedback Unit 3712 may be implemented in any number of ways known in the art and may be a logical or a physical control channel. As a physical channel it may comprise a dedicated time / frequency slot assigned to a user. It may also be a random access channel shared by all users. The control channel may be pre-assigned or it may be created by stealing bits in a predefined way from an existing control channel.

[0534] In the following discussion, results obtained through measurements with the DIDO-OFDM prototype are described in real propagation environments. These results demonstrate the potential gains achievable in adaptive DIDO systems. The performance of different order DIDO systems is presented initially, demonstrating that it is possible to increase the number of antennas / user to achieve larger downlink throughput. The DIDO performance as a function of user device’s location is then described, demonstrating the need for tracking the changing channel conditions. Finally, the performance of DIDO systems employing diversity techniques is described.11. Performance of Different Order DIDO Systems

[0535] The performance of different DIDO systems is evaluated with increasing numberof transmit antennas N = M, where M is the number of users. The performance of the following systems is compared: SISO, DIDO 2 x 2, DIDO 4 × 4, DIDO 6 x 6 and DIDO 8 x 8. DIDO N x M refers to DIDO with N transmit antennas at the BS and M users.

[0536] Figure 39 illustrates the transmit / receive antenna layout. The transmit antennas 3901 are placed in squared array configuration and the users are located around the transmit array. In Figure 39, T indicates the “transmit” antennas and U refers to the “user devices” 3902.

[0537] Different antenna subsets are active in the 8-element transmit array, depending on the value of Al chosen for different measurements. For each DIDO order (A / ) the subset of antennas that covers the largest real estate for fixed size constraint of the 8-element array was chosen. This criterion is expected to enhance the spatial diversity for any given value of N.

[0538] Figure 40 shows the array configurations for different DIDO orders that fit the available real estate (i.e., dashed line). The squared dashed box has dimensions of 24”x24”, corresponding to ~ λ × λ at the carrier frequency of 450 MHz.

[0539] Based on the comments related to Figure 40 and with reference to Figure 39, the performance of each of the following systems will now be defined and compared:SISO with T1 and U1 (4001)DIDO 2 x 2 with T1,2 and U1,2 (4002)DIDO 4 x 4 with T1,2,3,4 and U1,2,3,4 (4003)DIDO 6 x 6 with T1,2, 3, 4, 5, 6 and U1,2, 3, 4, 5, 6 (4004)DIDO 8 x 8 with T1, 2, 3, 4, 5, 6, 7, 8 and U1, 2, 3, 4, 5, 6, 7, 8 (4005)

[0540] Figure 35 shows the SER, BER, SE (Spectral Efficiency) and goodput performance as a function of the transmit (TX) power for the DIDO systems described above, with 4-QAM and FEC (Forward Error Correction) rate of 1 / 2. Observe that the SER and BER performance degrades for increasing values of / V. This effect is due to two phenomena: for fixed TX power, the input power to the DI DO array is split between increasing number of users (or data streams); the spatial diversity decreases with increasing number of users in realistic (spatially correlated) DIDO channels.

[0541] To compare the relative performance of different order DIDO systems the target BER is fixed to 10“4(this value may vary depending on the system) that corresponds approximately to SER= 10"2as shown in Figure 35. We refer to the TX power values corresponding to this target as TX power thresholds (TPT). For any A / , if the TX power is below the TPT, we assume it is not possible to transmit with DIDO order A / and we need to switch to lower order DIDO. Also, in Figure 35, observe that the SE and goodput performance saturate when the TX power exceeds the TPTs for any value of Al. From these results, an adaptive transmission strategy may bedesigned that switches between different order DIDO to enhance SE or goodput for fixed predefined target error rate.

[0542] Alternatively, in one embodiment, the various functional modules illustrated herein and the associated steps may be performed by specific hardware components that contain hardwired logic for performing the steps, such as an application-specific integrated circuit (“ASIC”) or by any combination of programmed computer components and custom hardware components.

[0543] In one embodiment, certain modules such as the coding and modulation units 2704 described above may be implemented on a programmable digital signal processor (“DSP”) (or group of DSPs) such as a DSP using a Texas Instruments' TMS320x architecture (e.g., a TMS320C6000, TMS320C5000,... etc). The DSP in this embodiment may be embedded within an add-on card to a personal computer such as, for example, a PCI card. Of course, a variety of different DSP architectures may be used while still complying with the underlying principles of the disclosure.

[0544] One solution to overcome many of the above prior art limitations is to have user devices concurrently operate in TDD mode in the same spectrum as currently used UL or DL FDD spectrum, such that the TDD spectrum usage is coordinated so as to not conflict with current FDD spectrum usage. Particularly in the FDD UL channel, there is increasingly more unused spectrum, and TDD devices could use that spectrum without impacting the throughput of the existing FDD network. The also enables TDD usage highly propagation-efficient UHF spectrum which, in many regions of the world is almost entirely allocated to FDD, relegating TDD to far less propagationefficient microwave bands.

[0545] In another embodiment is to have user devices concurrently operated in FDD mode in the same spectrum as currently used UL or DL FDD spectrum, such that the UL and DL channels are reversed and each network’s spectrum usage is coordinated so as not to conflict with the other network’s spectrum usage. Given that the UL channel of each network is increasingly underutilized relative to the DL channel, it allows each network’s DL channel to utilize the unused spectrum in the other network’s UL channel.12. Systems and Methods for Concurrent spectrum usage within actively used spectrum

[0546] As detailed in the Background section above, and shown in Figure 41 and Figure 42 mobile data usage has changed dramatically from being dominated bylargely symmetric voice data to highly asymmetric non-voice data, particularly media such as video streaming. Most mobile LTE deployments worldwide are FDD LTE, whose physical layer structure is illustrated in the upper half of Figure 43, which have fixed, symmetric uplink (“UL”) and downlink (“DL”) channels, and as a result, as the DL channels have become increasingly congested with exponential growth of DL data relative to UL data, the UL data channels have been increasingly underutilized.

[0547] The LTE standard also supports TDD LTE (also called “TD-LTE”) whose physical layer structure is illustrated in the lower half of Figure 43, and the mobile operator can choose whether the UL and DL channels are symmetric (as shown in this illustration) or asymmetric (e.g. with more subframes allocated to either the DL or UL channel), and as a result, as the DL channels become increasingly congested with exponential growth of DL data relative to UL data, the mobile operator can choose to allocate more subframes to DL than to UL. For example, in one configuration TD-LTE supports an 8:1 DL: UL ratio, allocating 8 times as many subframes to DL as to UL.

[0548] Other than the fact that TD-LTE is bi-directional in one channel, the structure and details of TD-LTE and FDD LTE are almost identical. In both modes every frame has 10ms duration and is made up of ten subframes of 1ms each. The modulation and coding schemes are almost identical, and the upper layers of the protocol stack are effectively the same. In both cases, the time and frequency reference for the user equipment (“UE”) devices (e.g. mobile phones, tablets) is provided by the eNodeB (the LTE base station protocol stack) to all devices (via the DL channel with FDD LTE and during DL subframes with TD-LTE).

[0549] Notably, in the case of both FDD and TDD LTE, the network can be configured so that a UE may only transmit UL data when given a grant to do so by the eNodeB, received through a DL transmission. As such, the eNodeB not only controls when it transmits DL data, but it also controls when UEs may transmit UL data.

[0550] Also, notably, in the case of an LTE FDD UE, its receiver is only tuned to its DL channel and has no receiver tuned to its UL channel. As such an FDD UE is “deaf” to anything that is transmitted in its UL channel by another device.

[0551] And, in the case of all LTE UEs, whether FDD or TDD, even to the extent their receivers are tuned to a particular channel, other than certain control signals intended for all UEs (or for a given UE) which maintain their time reference and connection to the network, or give them directions at what time and frequency they are to receive data, they ignore DL data not intended to them. Or to put it another way, theonly relevant DL data to an LTE UE is data that is either control information or is data that is directed to the UE. During other times, whether the channel is utilized with a DL to another UE, not utilized at all or utilized for a purpose that falls outside of the LTE standard, the UE is “deaf” to any DL transmissions that are not control information or DL data directed to that UE. Thus, LTE receivers, whether FDD or TDD, only receive control data intended for all UEs or for a given UE, or receive data for a given UE. Other transmissions in the DL channel are ignored.

[0552] Figure 44 illustrates how an FDD and TDD network can concurrently utilize actively utilize FDD spectrum. The top two lines of boxes labeled “FDD LTE 4410” illustrate one LTE frame interval (10ms) made up of ten 1ms subframe intervals, in both the Uplink (“UL”) and Downlink (“DL”) channels. This illustration shows the type of asymmetric data transmission that is increasingly more typical (e.g. downlink streaming video) where there is far more DL data than UL data. Boxes with solid outlines filled with slanted lines (e.g. box 4412 and boxes 4411) indicate subframes where data is being transmitted, boxes with dotted outlines that are blank (e.g. boxes 4414) show “idle” subframe intervals where no data is being transmitted (i.e. there are no transmissions in the channel during that subframe interval). Boxes 4411 are 2 of the 10 DL subframes, all of which are full of data. Box 4412 shows 1 UL subframe which has data. And boxes 4414 are 3 of the 9 idle UL subframe intervals which have no data transmissions.

[0553] The middle two lines of boxes in Figure 44 labeled “TDD LTE 4420” illustrate one LTE frame interval (10ms) made up of 10 1ms subframe intervals, including 2 “Special” subframe intervals, but unlike the FDD LTE 4410 lines, both lines of boxes in the TDD LTE 4420 line not only share the same spectrum with each other, but they share the same spectrum as the FDD Uplink. This illustration shows asymmetric data transmission where there are 4 DL subframes and 3 UL subframes transmitting data. Boxes with solid outlines filled with dashed lines (e.g. box 4421, box 4422 and box 4423) indicate subframes where data is being transmitted, the box with a dotted outline that is blank (i.e. box 4424) shows an idle subframe interval where no data is being transmitted (i.e. there are no transmissions in the channel during that subframe interval). Box 4421 is 1 of 4 DL subframes, all of which are full of data. Box 4422 shows 1 of 3 UL subframes all of which have data. Box 4424 is the 1 idle UL subframe interval which is empty.

[0554] The third two lines of boxes in Figure 44 labeled “FDD+TDD LTE 4430” illustrate one LTE frame interval (10ms) made up of 10 1ms subframe intervals, including 2 “Special” subframe intervals, and shows the concurrent operation of the FDD LTE 4410 system and the TDD LTE 4420 system, with the TDD LTE 4420 system sharing the same spectrum as the FDD LTE 4410 Uplink. The two systems do not interfere with each other because, (a) during the time interval of subframe 4412 where the FDD LTE 4410 system has UL data transmission, the TDD LTE 4420 system has an idle interval 4424 when it is neither an UL or DL and (b) during the subframe intervals where the TDD LTE 4420 system has transmissions in either the UL or DL direction (e.g. during subframes 4421, 4423 and 4422), the FDD LTE 4410 system has idle UL intervals (e.g. idle UL subframe intervals 4414) with no UL data transmissions. Thus, the two systems coexist using the same spectrum with no interference between them.

[0555] For FDD LTE 4410 and TDD LTE 4420 networks to concurrently use the same spectrum, their operation must be coordinated by either one eNodeB that is set up to operate two spectrum sharing networks concurrently, or by the coordination of an eNodeB operating the existing TDD LTE 4420 network and a second network controller that could be a second eNodeB or another system compatible with LTE timing and frame structure, such as the Distributed-Input Distributed-Output Distributed antenna MU-MAS C-RAN system disclosed above and in the Related Patents and Applications. In any of these cases, both the frames of the FDD LTE 4410 and TDD LTE 4420 systems have to be synchronized, not only in terms of timing, but in terms of subframe resource allocations. For example, in the case of Figure 44, the system controlling the FDD LTE 4410 system will need to be aware of which subframes are TDD UL subframes that are available to be used for UL (e.g. will not conflict with TDD DL control signals sent over subframes #0 and #5 for time and frequency synchronization at the UE), and use one of those subframes for its FDD UL subframe 4412. If the same system is also controlling the TDD LTE 4420 system, it will also have to be sure not to schedule an UL from a TDD device during that subframe 4412 time interval, and if it is not controlling the TDD LTE 4420 system, it will have to notify whatever system is controlling the TDD LTE 4420 system to not schedule an UL from a TDD device during that subframe 4412 time interval. Of course, it may be the case that the FDD LTE 4410 system requires more than one UL subframe during a frame time, and if so, its controller would use any or all of the 3 TDD LTE 4420subframes 4422 for its UL subframes, appropriately controlling or notifying as described above. Note that it may be the case that in some 10 ms frames all of the UL subframes are allocated to one of the networks and the other network gets no UL subframes. LTE devices do not expect to be able to transmit UL data every frame time (e.g. when an LTE network is congested, an LTE device may wait many frame times before it is granted even a portion of a UL subframe), so one embodiment of the present disclosure will function when all of the available TDD LTE 4420 UL subframes in a given frame are utilized by one network (i.e. “starving” the other network of UL subframes). However, starving one network for too many successive frames or allowing too few UL frames in aggregate will result in poor network performance (e.g., low UL throughput, or high round-trip latency) and, at some point, if the LTE devices attached to the network seeking to transmit UL data may determine the network is not usable and disconnect. As such, establishing appropriate scheduling priorities and paradigms to balance the UL subframe resources between the FDD LTE 4410 and TDD LTE 4420 networks may result in the best overall network performance and user (and / or UE) experience.

[0556] One tool that is available for balancing the UL subframe resources (and to meet network operator priorities) that is not available in a standalone FDD LTE system are the TDD LTE Duplex Configurations shown in Figure 45. Figure 44 illustrates TDD LTE 4420 system TDD LTE Duplex Configuration 1, in which during the 10 subframes in the 10 ms frame, there are 4 UL subframes, 4 DL subframes and 2 Special subframes. As can be seen in Figure 45, there are several TDD LTE Duplex Configurations which can be used, depending on the mobile operator’s needs and data traffic patterns, and for balancing the UL subframe resources with the FDD LTE 4410 network needs. The TDD LTE Duplex Configuration can also be changed over time as data traffic patterns change. Any of the TDD LTE Duplex Configurations can be used with the embodiments of the disclosure. For example, in Configuration 1, as shown in Figure 44, 1 UL subframe has been allocated to the FDD network and 3 UL subframes have been assigned to the TDD network. If the FDD network had a sudden need for more UL throughput, then 2 UL subframes can be allocated for FDD, leaving 2 for TDD, the very next frame time. So, switching UL subframe allocation between the FDD and TDD network can be extremely dynamic.

[0557] Note that, if desired, UL resource allocation between the FDD LTE 4410 and TDD LTE 4420 networks can be even more fine-grained than a subframe basis.It is possible to allocate some resource blocks within a single subframe to FDD devices and others to TDD devices. For example, the LTE standard employs SC-FDMA multiple access technique for the UL channel. As such, UL channels from FDD and TDD devices can be assigned to different resource blocks within the same subframe via SC-FDMA scheme.

[0558] Finally, it is possible to schedule an FDD LTE 4410 UL during what would be a TDD LTE 4420 DL or Special subframe. One consideration is that TDD DL control signals used by the TDD LTE UEs to maintain their connections and maintain timing (e.g., P-SS and S-SS broadcast signaling sent over subframes #0 and #5) must be received by the TDD LTE UEs with sufficient regularity or else the UEs may disconnect.

[0559] Figure 46 shows the same concept in Figure 44 and described above, except the shared channel is the FDD DL channel, not the FDD UL channel. The same subframe filling and outlining designations from Figure 44 are used in Figure 46 and as can be seen, the FDD traffic situation is reversed with all of the subframes of FDD LTE 4610 UL channel being used for data while only 1 of the FDD LTE 4610 DL subframes is used for data, while all of the other DL subframes are “idle” and not transmitting data. Similarly, all of the TDD LTE 4620 UL subframes are used for data, while all but one of the TDD LTE 4620 DL subframes are used for data, and in this case the TDD LTE 4620 LTE channel is the same frequency as the FDD LTE 4610 DL channel. The result of the combined FDD LTE 4610 and TDD LTE 4620 networks is shown in the FDD+TDD LTE 4620 channels. As with the example in Figure 44 the two networks can be controlled by a single controller or by coordination of multiple controllers, with scheduling between them to be sure both networks operate as desired by the network operator with adequate performance to the users and user devices.

[0560] Note that the FDD devices attached to the FDD LTE 4610 network are relying on DL transmissions for control and timing information, as well as for data and they must receive adequate control signals on a sufficiently regular basis to remain connected. In embodiments in accordance with the present invention, the FDD devices use the broadcast signaling sent by the TDD LTE 4620 network over the DL subframes (e.g., subframes #0 and #5) to obtain time and frequency synchronization. In a different embodiment, subframes #0 and #5 carrying broadcast signaling are assigned to the FDD LTE 4610 network and used to derive time and frequency synchronization at every FDD device.

[0561] Although, as described above, typically the FDD DL channel is far more congested than the FDD UL channel, there may be reasons why a mobile operator wishes to share the DL channel. For example, some UL channels are limited to only UL use by the spectrum regulating authority (e.g. there may be concerns about output power interfering with adjacent bands). Also, once a mobile operator begins to offer TDD devices compatible with its FDD spectrum, the mobile operator will likely find these devices to be using spectrum more efficiently than FDD devices and, as such, may discontinue sales of FDD devices. As old FDD devices gradually are replaced and an increasing percentage of devices are TDD, the operator may wish to allocate increasingly more of its spectrum to TDD devices, but still maintain compatibility with the remaining FDD devices in the market.

[0562] Toward this end, as there are fewer and fewer FDD devices remaining in operation, the operator may decide to use both the UL and DL bands for TDD operation. This is illustrated in Figure 47 where FDD LTE 4710 only has one subframe in use for UL and one for DL and the remainder are idle. There are two TDD LTE networks 4720 and 4730 each respectively using the FDD LTE 4710 UL and DL channels, resulting in the three networks sharing the two channels as show in FDD+TDD LTE 4740. The same flexibilities and constraints apply as described previously, and there can be a single controller of all 3 networks or multiple controllers. The two TDD networks can be operated independently, or by using Carrier Aggregation techniques.

[0563] An operator may also choose to forgo TDD altogether but instead add a second FDD network in the same spectrum as an existing FDD network, but with the Uplink and Downlink channels swapped. This is illustrated in Figure 48 where FDD LTE 4810 network is very asymmetrically utilized in favor of the DL channel, so only one subframe is used for UL, and a second FDD LTE 4820 network is also very asymmetrically utilized in favor of the DL channel, but notice that in Figure 48 the channel allocation for FDD LTE 4820 is swapped, with the FDD Downlink channel shown above the FDD Uplink channel, contrary to the channel orderfor FDD LTE 4810 or as shown in prior figures. In the case of both FDD LTE 4810 and 4820, the DL channel leaves one DL subframe idle that corresponds with the one UL frame that is used by the other network. When the networks are combined as shown in FDD+TDD LTE 4730, all of the subframes in both channels are DL, except for subframes 4731 and 4732. Thus, 90% of the subframes are devoted to DL, which better matchesmobile traffic patterns as they have evolved than symmetric spectrum allocation for UL and DL.

[0564] Also, this structure enables the controller (or controllers) that manage the network to dynamically change the number of UL and DL subframes allocated to each network on a subframe-by-subframe basis, affording extremely dynamic UL / DL traffic adaptation, despite the fact that FDD devices are using both networks.

[0565] As with the combined FDD / TDD networks previously described, the same constraints apply for FDD mode in that the LTE devices must receive sufficient control and timing information to remain connected and operate well, and they need sufficiently regular and adequate number of UL frames.

[0566] The two FDD networks can be operated independently or through Carrier Aggregation.

[0567] In another embodiment, the control information transmitted by the DL channel an existing active network (e.g. in Figures 44, 46, 47 and 48 FDD LTE 4410, FDD LTE 4610, FDD LTE 4710, or FDD LTE 4810) is used by a new network (or networks) using the same channel (e.g. in Figures 44, 46, 47 and 48 TDD LTE 4420, TDD LTE 4620, TDD LTE 4720 and TDD LTE 4730, or FDD LTE 4820) to determine which subframes and / or resource blocks and and / or other intervals will be idle. In this way, the new network(s) can determine when it is able to transmit (whether DL or UL) without interfering with the existing active network. This embodiment may make it possible to concurrently use the spectrum of the existing active network without any modification of the existing active network or relying upon any special connection to the existing active network’s controller, since it is just a matter of the controller of the new network(s) receiving what is already in the DL transmission from the existing active network. In another embodiment, the only modification to the existing active network is to make sure it enables the new network(s) to transmit essential control and timing information to maintain connections with UEs. For example, the existing active network could be configured to not transmit during times when essential timing and synchronization information are being transmitted, but otherwise operate unmodified.

[0568] Although the above embodiments of concurrently supporting networks in the same spectrum used the LTE standard for examples, similar techniques can be utilized with other wireless protocols as well.13. Utilizing Distributed Antenna MU-MAS concurrently with actively used spectrum

[0569] The Distributed Antenna MU-MAS techniques (collectively called “DIDO”) as disclosed above and in the Related Patents and Applications, dramatically increase the capacity of wireless networks, improve reliability and throughput per device, and make it possible to reduce the cost of devices as well.

[0570] In general, DIDO operates more efficiently in TDD than FDD networks because the UL and DL are in the same channel and, as a result, training transmission received in the UL channel can be used to derive channel state information for the DL channel by exploiting channel reciprocity. Also, as described above, TDD mode inherently better suits the asymmetry of mobile data, allowing for more efficient spectrum utilization.

[0571] Given that most of the world’s current LTE deployments are FDD, by utilizing the techniques disclosed in Section 3, it is possible to deploy a TDD network in spectrum actively used for FDD, and DIDO can be used with that new TDD network, thereby dramatically increasing the capacity of the spectrum. This is particularly significant in that, UHF frequencies propagate far better than microwave frequencies, but most UHF mobile frequencies are already in use by FDD networks. By combining DI DO-based TDD networks with existing FDD networks in UHF spectrum, an exceptionally efficient TDD network can be deployed. For example, Band 44 is a TDD band from 703-803 MHz, overlaying a large number of 700 MHz FDD bands in the U. S. Band 44 devices could be used concurrently in the same spectrum as 700 MHz FDD devices, enabling DIDO TDD in prime spectrum.

[0572] DIDO does not add significant new constraints to the spectrum combining techniques described above. The RAN 2101 shown in Figure 21 would either replace the existing eNodeBs in the coverage area, or coordinate with the existing eNodeBs in adjacent wireless network 2402, as shown in Figure 24 per the subframe (or resource block) sharing techniques described above.

[0573] Notably, if the DIDO system is controlling the entire system and providing the eNodeB for the FDD network, then DIDO can use a training signal such as the SRS UL from the FDD devices so as to decode via spatial processing the UL from multiple existing FDD devices at the same time and within the same frequency band, thus dramatically increasing the spectral efficiency of the existing FDD UL channeland also reducing the UL power required (and / or receiving better signal quality) since the distributed DIDO APs are likely closer to the UEs than a single cellular base station, and also can utilize signal combining techniques, such as maximum ratio combining (MRC) or other techniques as described previously for DIDO.

[0574] Thus, DIDO can replace existing eNodeBs and simultaneously use existing spectrum with DIDO TDD devices, while also applying the benefits of DIDO to the UL of the existing FDD devices that are already deployed.14. Mitigating interference in actively used spectrum

[0575] As noted previously, when a TDD network is deployed in either UL or DL frequencies in a band that has been allocated as an FDD band, there may be concerns about output power interfering with adjacent bands. This can be caused by out of band emissions (OOBE) interference and / or receiver “blocking” or receiver “desensitization”. OOBE refers to power emissions outside of the allocated band. OOBE are typically are at highest power in frequencies immediately adjacent to a transmit band and typically diminish as frequencies become more distant to the transmit band. “Receiver blocking” or “receiver desensitization” refers to a receiver’s front-end amplifier losing sensitivity to a desired in-band signal due to the presence of a powerful out-of-band signal, typically in a nearby band.

[0576] When regulatory authorities (e.g. the FCC) allocate spectrum in adjacent bands for use by multiple mobile operators or other users of spectrum, typically rules are put in place to limit OOBE and power levels so that mobile devices (e.g. mobile phones) and base stations can be manufactured to practical specifications given technology available at the time of the regulatory ruling. Further, consideration is given to existing users of adjacent spectrum and the rules under which those devices were manufactured. For example, a new allocation of spectrum may take into account the availability of technology that will better tolerate OOBE to better reject powerful out-of-band transmissions than technology made during prior spectrum allocations, where older technology was deployed that is more sensitive to OOBE and powerful out-of-band transmissions. Since it is often impractical to replace prior generation base stations and mobile devices, it is necessary for the new deployments to adhere to the OOBE and powerful out-of-band transmission limitations of the prior deployments.

[0577] In the case of TDD deployments in FDD bands, there are additional constraints that must be adhered to. In an FDD pair, each of the UL or DL bands wasallocated with an expectation of, respectively, UL-only transmissions or DL-only transmissions. Since TDD transmits alternatively in both UL and DL, then if a TDD deployment is operating in a FDD band the was previously allocated as UL-only or DL-only band, then it is operating in a transmit direction that was not anticipated. Thus, to be sure the TDD transmissions do not interfere with previously-defined FDD usage in adjacent spectrum, the TDD transmissions in the opposite direction of the previously-defined FDD usage must meet the emission requirements for the existing usage. For example, if TDD is deployed in an FDD UL band, then the UL part of the TDD transmission should not be a problem, since UL is the direction of previously-defined usage. But, since the DL part of the TDD transmission is in the opposite direction of the previously-defined UL usage, typically the TDD DL transmission must meet the OOBE and powerful out-of-band transmission requirements defined for UL transmissions.

[0578] In the case of deploying TDD in an UL band, the UL part of the TDD transmission will typically be a transmission from a mobile device (e.g. a mobile phone). FDD phones in adjacent bands and base stations in adjacent bands will have been designed to tolerate the UL transmissions from mobile phones in adjacent bands. For example, Figure 51A shows the FDD band 7 UL band divided into sub-bands A through G. FDD mobile phones and base stations operating in shaded sub-band E are designed to tolerate UL transmission in FDD sub-bands A through D, F and G. Thus, if a TDD device is operated in adjacent sub-band D (as shown shaded in Figure 51 B in TDD band 41 sub-band D, the same frequency as FDD band 7 sub-band D), the FDD band 7 mobile phone and base station devices will have no issue with UL part of the TDD transmission in band 41 sub-band D.

[0579] But, the DL transmission in TDD band 41 sub-band D is not a scenario that was anticipated in the allocation of FDD band 7 or in mobile phones and base stations designed to operate in that band. Let’s consider each device in turn.

[0580] In the case of a FDD band 7 mobile phone in sub-band E, it is unlikely to be adversely impacted by base station DL transmissions in adjacent TDD band 41 sub-band D because a mobile phone’s band 7 receiver is designed to reject UL transmissions from other mobile phones transmitting in adjacent UL bands. In normal usage, mobile phones might operate within inches of each other (e.g. if two people seated next to each other at a stadium are both making calls) resulting in very high transmit power incident upon each phone’s receiver. Technologies (e.g. cavity filters)reject such powerful nearby band transmissions, enabling mobile phones that are physically close to mobile phones using an adjacent band to transmit UL signals without adversely impacting the adjacent mobile phone’s DL reception.

[0581] But the case of a FDD band 7 base station operating in sub-band E is different. Its receiver was designed to receive UL from mobile devices in FDD band 7 sub-band E and to reject UL from mobiles devices in adjacent FDD band 7 sub-bands A through D, F and G. It was also designed to reject DL transmissions in band 38 TDD sub-band H and band 7 FDD DL in sub-bands A’-H’ shown in Figure 51A. Thus, the only scenario the FDD band 7 base station was not designed for is to reject DL transmissions from other base stations in sub-band A through D, F and G. We shall consider this case.

[0582] Figures 50A, 50B, 50C and 50D consider four transmission scenarios between a TDD band 41 base station (BTS) 5010 on structure 5001 (e.g. a building, a tower, etc.) transmitting in sub-band D and an FDD band 7 base station (BTS) 5030 on structure 5002 receiving in UL sub-band E and transmitting in DL sub-band E’. In scenario:

[0583] 50A: there is no path between TDD BTS 5010 and FDD BTS 5030 because the transmission is completely obstructed by building 5005 and there is no multi-path route around building 5005, and as a result no TDD DL signal will reach FDD BTS 5030.

[0584] 50B: there is only a Line of Sight (LOS) path between TDD BTS 5010 and FDD BTS 5030. A LOS path will result in a very powerful TDD DL signal reaching FDD BTS 5030.

[0585] 50C: there is a Non-Line of Sight (NLOS) path between TDD BTS 5010 and FDD BTS 5030, but no LOS path. While it is possible that an NLOS path is via a highly efficient reflector (e.g. a large wall of metal) that is exactly angled such that the signal reaching FDD BTS 5030 approaches the power of an LOS signal, it is statistically unlikely in real-world scenarios that an NLOS path exists that approaches the efficiency of a LOS path. In contrast, what is likely in real-world scenarios is that an NLOS path will be affected by objects that reflect and scatter in a variety of angles as well as objects that absorb and refract the signal to a greater or lesser degree. Further, by definition NLOS paths are longer than LOS paths resulting in higher path loss. All of these factors result in significant path loss in NLOS paths relative to LOS paths. Thus, statistically, it is likely in real-world scenarios that the TDD DL NLOSsignal power received by the FDD BTS 5030 will be much less than the TDD DL LOS signal power received by the FDD BTS 5030 as illustrated in Figure 50B.

[0586] 50D: there is both an LOS and NLOS path between TDD BTS 5010 and FDD BTS 5030. This scenario is effectively the sum of scenarios 50B and 50C, resulting in the FDD BTS 5030 receiving the sum of a very powerful signal from the LOS path from TDD BTS 5010 as well as a statistically much weaker signal from the NLOS path from TDD BTS 5010.

[0587] In considering the four scenarios of the previous paragraph, clearly scenario 50A presents no issue at all since there is no signal received by FDD BTS 5030. NLOS scenario 50C results in some TDD DL BTS 5010 signal reaching FDD BTS 5030, but statistically it is a much weaker signal than an LOS signal. Further, in the unlikely, but possible, scenario where an NLOS path is a highly efficient reflector, then that can often be mitigated by site planning, e.g., repositioning or repointing the TDD DL BTS 5010 antenna such that the NLOS path is not efficiently reflected. Scenarios 50B (LOS) and 50D (LOS + NLOS) are the problematic scenarios because of the LOS component in each resulting in a high power signal in an adjacent band, which the FDD BTS 5030 was not designed to tolerate.

[0588] While the NLOS components of scenarios 50C and 50D certainly can result in a lower power signal received by the FDD BTS 5030 in an adjacent UL band, the FDD BTS 5030 is designed to reject lower power, largely NLOS signal from the entire UL band from mobile devices, e.g., using cavity filters. Thus, if the LOS component of scenarios 50B and 50D can be mitigated, leaving only a lower power (e.g. avoiding unlikely highly efficient reflections) NLOS signal component from scenarios 50C and 50D, then this would result in the FDD BTS 5030 only receiving transmissions in the UL band at power levels it was designed to tolerate and would thus enable DL transmissions from TDD BTS 5010 in the UL band without disrupting the operation of the FDD BTS 5030. As noted previously, no other transmission direction in the FDD UL band will disrupt adjacent band operation and, thus, if the TDD DL BTS 5010 LOS transmission component to the FDD BTS 5030 can be mitigated, then FDD UL bands can be used for TDD bi-directional operation without disrupting adjacent band FDD operation.

[0589] As previously disclosed in the Related Patents and Applications, a multiuser multi-antennas system (MU-MAS), such as the DIDO system, the technology marketed under pCell® trademark, or other multi-antenna systems are able to utilizechannel state information (CSI) knowledge from the location of a user antenna to either synthesize a coherent signal at the location of the user antenna, or synthesize a null (i.e. zero RF energy) at that location. Typically, such CSI is determined from an in-band (IB) training signal, either transmitted from the base station to the user device, with the user device responding with CSI information, or transmitting from the user device to the base station, with the base station exploiting reciprocity to determine CSI as the location of the user antenna.

[0590] In one embodiment the MU-MAS system as depicted in Figure 49 and operates as described above, estimates the CSI at each UE location 2111, synthesizing independent pCells 2103 (pCell1, pCell2, … pCellM) in the same frequency band at each UE location 2111 with the signal from each of the respective VRIs 2106 (VRI1, VRI2, … VRIM). In addition to estimating the CSI at each UE location 2111 as described above, in this embodiment the MU-MAS system also estimates CSI at each antenna 4903 shown on structures 4931-4933 and as it synthesizes pCells 2103 at each UE location 2111, it also concurrently synthesizes pCells 4911 (pCells 1..7, 8..14, and (b-6)..b, (collectively, pCellsi.b)) at the location of each antenna 4903, with all pCells in the same frequency band. But unlike pCells 2103, which each contains a synthesized waveform from its respective VRI, each pCell 4911 is a null with zero RF energy.

[0591] In one embodiment the null pCells 4911 described in the previous paragraph are synthesized by instantiating VRIs 4966 that input flat (Direct Current (DC1..b)) signals to the VRM 2108. In another embodiment, they are calculated within the VRM as null locations using techniques previously disclosed in the Related Patents and Applications for synthesizing null signal (zero RF energy) contributions at antenna locations.

[0592] When an in-band (“IB”) training signal is used to estimate the CSI at the location of each antenna 4903, a highly accurate CSI estimation will result, using the techniques described above and in the Related Patents and Applications. For example, if the pCell transmission band is from 2530 to 2540 MHz, band D in Figure 51 B, if a training signal in the same frequency range of 2530 to 2540 is used, a highly accurate CSI estimation will result. But when an out-of-band (“OOB”) signal (e.g. at 2660 to 2670 MHz) is used to estimate the CSI at the location of an antenna instead of an IB signal (e.g. at 2530 to 2540 MHz, band E’ in Figure 51A), such an OOB CSI estimate will only be reasonably accurate if the channel is “frequency flat” between theI B and OOB frequencies. Frequency flat means that the channel has flat fading in both the IB and OOB frequencies, such that the signals in each of the IB and OOB frequencies experience the same magnitude of fading. If the IB and OOB frequencies have selective fading, i.e. frequency components of IB and OOB frequencies experience uncorrelated fading, then using the CSI estimate obtained from an OOB signal may not be very accurate for an IB signal. Thus, if band E’ of Figure 51 A is frequency flat relative to band D of Figure 51 B then a training signal in band E’ can be used to obtain a highly accurate CSI for band D. But, if band E’ has significant selective fading relative to band D, then a training signal from band E’ will not result in an accurate CSI for band D.

[0593] A purely LOS signal in free space where there is no NLOS component (e.g. as illustrated in Figure 50B) is in a frequency-flat channel. Thus, if the only component to the signal is LOS, then an OOB signal can be used to accurately estimate the CSI for an IB signal in at the location of a user antenna. In many real-world deployments, however, there is not a purely LOS signal, but rather there is either no signal at all (e.g. Figure 50A), only an NLOS signal (e.g. Figure 50C) or a combined LOS and NLOS signal (e.g. Figure 50D).

[0594] If an OOB signal is used to estimate the CSI of FDD BTS 5030’s antenna from the perspective of TDD BTS antenna 5010, then the following be the results for each of the scenarios in Figures 50A, 50B, 50C and 50D:

[0595] 50A: no signal, so no CSI will result.

[0596] 50B: LOS-only will result in CSI that is consistently accurate.

[0597] 50C: NLOS-only will result in CSI that is not consistently accurate due to the likelihood of selective fading from the NLOS-only channel.

[0598] 50D: LOS + NLOS that, the resulting CSI will be a combination of CSI components where the NLOS component is not consistently accurate and LOS component is consistently accurate.

[0599] We refer to the CSI derived from a pure LOS channel as CL, the CSI derived from a pure NLOS channel as CN, and the CSI derived from a channel with a combination of pure LOS and pure NLOS components as CLN. The CSI of a combined LOS and NLOS can then be formulated as CLN = CL + CN.

[0600] In the case of a pure LOS channel between Access Points 2109 (API.. N) and antennas 4903 in Figure 49, then the only CSI component is a CL for each antenna 4903. Since pure LOS channels are frequency flat, if an OOB signal is usedfor the deriving the CSI, the CSI for each antenna 4903 will still be accurate. Thus, when using an OOB signal to derive the CSI, the LOS signal from each AP 2109 will be nulled with a high degree of accuracy at the location of each antenna 4903, resulting in little or no detectable signal by each antenna 4903 from the transmissions of APs 2109.

[0601] In the case of a pure NLOS channel between APs 2109 and the antennas 4903, then the only CSI component for is a CN for each antenna 4903. If an OOB signal is used for the deriving the CSI, the CSI for each antenna 4903 will be more or less accurate, depending on how frequency flat the channel is. Thus, when using an OOB signal to derive the CSI, the NLOS signal from each AP 2109 will be either nulled completely (in the case of a perfectly frequency-flat channel), partially nulled, or not nulled at all, depending on the degree of channel frequency selectivity. To the extent the NLOS signals are not nulled, each antenna 4903 will receive some random summation of the NLOS signals from the APs 2109. Thus, there may be some reduction in the NLOS signal strength from APs 2109 to the antennas 4903, but the NLOS signal strength will be no higher than NLOS signal strength than would have been received had no CSI been applied to attempt to null the NLOS signals.

[0602] In the case of a combined LOS and NLOS channel between APs 2109 and the antennas 4903, then the CSI is a combination of LOS and NLOS components CLN = CL + CN for each antenna 4903. If an OOB signal is used for the deriving the CSI, the CL component of the CSI for each antenna 4903 will be highly accurate and CSI for CN component will be more or less accurate, depending on how frequency flat the channel is. The CL component of the CSI affects the nulling of the LOS component of the signal between the APs 2109 and the antennas 4903, while the CN component of the CSI affects the nulling of the NLOS component of the signal between the APs 2109 and the antennas 4903. Thus, when using an OOB signal to derive the CSI, the LOS signal from each AP 2109 will be consistently nulled completely, while the NLOS signal from each AP 2109 will be nulled to a greater or lesser degree, depending on the degree of channel frequency selectivity. So, in sum, the LOS components of the transmissions from APs 2109 will be completely nulled, and NLOS components of the transmissions from APs 2109 will have no greater signal strength than would have been received by the antennas 4903 had no CSI been applied to attempt to null the NLOS signals.

[0603] As previously noted above, in the scenarios shown in Figures 50A, 50B, 50C and 50D, the problematic scenarios are when the LOS component of TDD BTS 5010 is received by FDD BTS 5030. It is generally not a problem when the NLOS component of TDD BTS 5010 is received by FDD BTS 5030. Consider the MU-MAS embodiment described in the preceding paragraphs: If TDD BTS 5010 is one of the APs 109 from Figure 49 and FDD BTS 5030 is one of the antennas 4903, then if the training signal used to determine the CSI for antennas 4903 is an IB signal, then transmission from TDD BTS 5030 will be completely nulled at FDD BTS 5030. If the training signal used to determine the CSI for antennas 4903 is an OOB signal, then the LOS transmission from TDD BTS 5030 will be completely nulled at FDD BTS 5030, and the NLOS transmission from TDD BTS 5030 to FDD BTS 5030 will be no worse than if no CSI had been applied to attempt to null the NLOS signals. Thus, an OOB training signal from antenna 5030 will completely null any LOS component of a transmission from antenna 5010, but will neither reliable null nor make any stronger any NLOS component of a transmission from antenna 5010.

[0604] Since only the LOS component of the signal transmitted from antenna 5010 is problematic and it has been nulled, and NLOS component of antenna 5010 is not problematic and won’t be made any worse, we thus have an embodiment in which a TDD BTS 5030 can operate in a MU-MAS system such as that shown in Figure 49 in FDD UL spectrum without significantly disrupting the receiver performance of an adjacent band FDD BTS, provided that at least an OOB signal from the FDD BTS is available.

[0605] In the case of many FDD systems, such an OOB signal is indeed available. For example, in Figure 51A, the FDD BTS 5030 that is receiving UL in sub-band E is concurrently transmitting DL in sub-band E’. While data traffic may vary in the DL subband, the control signals typically (e.g. in the LTE standard) are transmitted repeatedly. So, at a minimum, these DL control signals can be used as the OOB training signal used for determining the CSI of the FDD BTS 5030, utilizing reciprocity techniques previously disclosed in the Related Patents and Applications below, and applying the CSI derived from channel reciprocity of the DL transmission from FDD BTS 5030 (corresponding to antennas 4903 in Figure 49) in sub-band E’ to create a null at FDD BTS 5030 (corresponding to antennas 4903 in Figure 49) in sub-band D concurrently with the TDD DL transmission from TDD BTS 5010 (corresponding to APs 2109 in Figure 49) to UEs at UE locations 2111. The LOS component of the sub-band D TDD DL transmission from TDD BTS 5010 (corresponding to APs 2109 in Figure 49) will be completely nulled at FDD BTS 5030 (corresponding to antennas 4903 in Figure 49), while the NLOS component of the sub-band D TDD DL transmission will be no worse that it would be had been had there been no nulling of the LOS component.

[0606] In addition to creating a null for TDD DL transmissions at the location of FDD BTS locations 5030 within the bandwidth of the TDD DL transmissions, it is desirable to also null high power OOBE from the TDD DL transmission at the FDD BTS locations. Because the OOBE from the LOS component is in a frequency-flat channel, then nulling of the in-band LOS component will also null the OOBE from the LOS component. However, to the extent the NLOS component is in a frequency-selective channel, the OOBE of the NLOS component will not be nulled, but it will be no worse than the OOBE from the NLOS would have been had there been no attempt to null the LOS component. The power of the OOBE of each of the LOS and NLOS transmissions is proportionate to the power of the in-band LOS and NLOS transmissions, respectively. Thus, nulling the OOBE of the LOS transmission, and making the OOBE of the NLOS transmission no worse than it would otherwise have been, addresses the highest-power and most problematic OOBE component, LOS, will making the less-problematic NLOS component no worse.

[0607] FDD base stations typically have multiple antennas for diversity, beamforming, MIMO or other reasons. This scenario is depicted in Figure 49 where there are multiple antennas 4903 on each structure 4931-4933. So, rather than the single FDD BTS antenna 5030 depicted in Figures 50A, 50B, 50C and 50D, typically there would be multiple FDD BTS antennas 4903. To the extent any such antennas are transmitting, then the MU-MAS system described above and depicted in Figure 49 would receive a transmission from each of the antennas 4903 that it would use to derive the CSI for each antenna and null the LOS component of the APs 2109 transmissions to that antenna. In another embodiment, nulls would only be created for some of the BTS antenna 4903. For example, some of the antennas 4903 might not be used in UL reception, and it would be unnecessary to create a null forthem.

[0608] In a wide-scale deployment of the above embodiments, many TDD BTS antennas and adjacent sub-band FDD BTS antennas would be distributed throughout a large coverage area (e.g. a city, a region, a country or a continent). Clearly, not all antennas would be within range of each other, and as such it would only be necessaryto null a TDD BTS DL transmission that is of sufficient power levels to interfere with a given FDD BTS antenna. In one embodiment, the VRM 2108 receives from TDD BTS DL APs 2109 transmissions from FDD BTS antennas 4903 and assesses the power level incident from the TDD BTS APs 2109 upon each FDD BTS antenna 4903 from each TDD BTS AP 2109. Various means can be used to make this assessment, including utilizing channel reciprocity. The VRM 2108 only synthesizes nulls at the FDD BTS antennas 4903 that would be receiving OOBE or receiver blocking / receiver desensitization power above a given threshold. The threshold can be set to any level, including, but not limited thresholds that are determined to be an interfering threshold or a threshold established by spectrum regulations.

[0609] The null pCells 4911 are similar to pCells 2103 transmitting a signal in that they require computing resources and AP 2109 resources. Thus, it is advantageous to minimize the number of AP 2109 resources needed to create null pCells throughout the coverage area. In another embodiment clustering techniques such as those previously disclosed in the Related Patents and Applications below can be utilized to reduce the number of APs 2109 needed to synthesize the pCells 2103 needed for user devices and pCells 4911 needed to null antennas 4903 throughout the coverage area.

[0610] The embodiments described above address creating nulls at FDD DL antennas that have no knowledge of the TDD operation in adjacent spectrum. In another embodiment the FDD DL antennas do have knowledge of the TDD operation in adjacent spectrum and cooperate with the TDD system. In one embodiment, the FDD DL antennas 4903 regularly transmit a training signal within the TDD band (e.g. such as the LTE SRS signal) the enables the MU-MAS system in Figure 49 to have an IB reference for determining accurate CSI for the FDD DL antennas 4903. With accurate CSI the VRM 2108 will be able to synthesize a null for both the LOS and NLOS components, thus enabling a very high power TDD DL transmission to be used in adjacent spectrum since even the NLOS signal will be nulled. In another embodiment the FDD DL transmission is timing and / or frequency interleaved with training signals from either the UEs (such as SRS) or the TDD DL BTS. In another embodiment the FDD DL antennas 4903 also transmit an IB training signal in their own UL spectrum (e.g. choosing a time when there is no concurrent UL activity) that the VRM 2108 can use to determine the OOBE CSI and create nulls for both the NLOS as well as the LOS OOBE.

[0611] In another embodiment the antennas 4903 are TDD antennas used in adjacent TDD spectrum. When adjacent TDD systems are synchronized in UL and DL, then interference from OOBE and receiver blocking / receiver desensitization is minimized since all BST s are in transmit or receive mode at the same time. Sometimes there is a need to have adjacent TDD system operate without synchronizing DL and UL times, for example, if adjacent networks require different DL and UL ratios or if they have different latency requirements, e.g., if one network needs more frequent DL or UL intervals to reduce round-trip latency. In these scenarios, adjacent bands will be in use with UL and DL at the same time. The same techniques described above can be used for one or both systems to synthesize nulls at the BST antennas of the other system during DL intervals. Per the techniques described above, one or both of the in-band and the OOBE transmissions can be nulled, either nulling the LOS component or the NLOS component as well.

[0612] In one embodiment the same spectrum for the MU-MAS system in Figure 49 is used to provide terrestrial wireless services while it is concurrently used as a DL band (i.e. with transmissions directed skyward) for aircraft. Even though the MU-MAS system is intended for terrestrial use, to the extent the aircraft falls within the antenna pattern of the APs 2109 the path from the APs 2109 to the aircraft will be LOS or largely LOS and potentially could interfere with the DL to the aircraft. By receiving the UL (i.e. transmission directed to the ground) from the aircraft, the VRM can derive the CSI to the aircraft antennas using the techniques described previously and thus synthesize a null at the locations of the aircraft antennas. Since the path to the aircraft is LOS, the CSI can be quite accurate, even if the aircraft UL signal is OOB. Thus, in this way spectrum can be concurrently used with aircraft DL. This is a very efficient use of spectrum since aircraft do not fly by very often and if spectrum were reserved exclusively for aircraft, it would be inactive most of the time.

[0613] In another embodiment the aircraft’s antenna(s) are treated as one or more UEs along with the terrestrial UEs, and when the aircraft flies within range of the MU-MAS system show in Figure 49, it uses UL and DL capacity the same as any other UEs. Multiple antennas can be used on the aircraft to increase capacity. The antennas can be located spread apart from each other on or in the aircraft and can be polarized to increase capacity. Individuals within the aircraft can also use their own devices (e.g. mobile phones) in the same spectrum, connected to the same MU-MAS. The MU-MAS would create independent pCells for the aircraft antennas and for the user UEs.15. Systems and Methods for Direct-to-Device Satellite Communications

[0614] In recent years, low earth orbit (“LEO”) satellite communications systems have started to offer data communications directly to mobile phones. For example, the Apple iPhone 14 and later models have an “Emergency SOS” feature that directly communicates from the phone to a satellite to send an emergency message, particularly if the phone is outside a mobile service area. Starlink recently demonstrated sending text messages “Direct to Cell” which were sent directly from a mobile phone coupled to a satellite. AST SpaceMobile recently demonstrated video conferencing directly from mobile phones coupled to a satellite in the United States and the United Kingdom.

[0615] Such Direct-to-Device (“D2D”) services face several challenges. These include the fact that (a) mobile phones have very small antennas and very limited transmit power and D2D satellites can be 500 to 750 km above earth, (b) the beam spot size that satellites can make on the ground is quite large, often 10s of km or more, limiting frequency reuse, (c) a given band used for D2D is often is not available in all areas in a region, and (d) the LOS path to the satellite from a mobile device may be attenuated or completely blocked by an obstacle, obstructing what is already a weak and fragile communications link.

[0616] Using pCell in connection with D2D communications addresses each of the above challenges. Figure 52A illustrates in accordance with embodiments of the present i...

Claims

CLAIMS:

1. A system for direct-to-device satellite communications, comprising:a centralized processor coupled to a network and configured to receive a plurality of data streams intended for a plurality of user equipment (UE) devices located in a coverage area on a surface of a celestial body; anda plurality of satellites in orbit above the coverage area, each satellite comprising at least one antenna and coupled to the centralized processor;wherein the centralized processor is configured to: obtain channel state information (CSI) characterizing a radio frequency (RF) channel between each of the plurality of UE devices and the at least one antenna of the plurality of satellites; compute precoding weights based on the obtained CSI for the plurality of UE devices; and generate a plurality of precoded waveforms by applying the computed precoding weights to the plurality of data streams;wherein the plurality of satellites are configured to cooperatively transmit the plurality of precoded waveforms such that the precoded waveforms combine coherently at the location of each of the plurality of UE devices to form a plurality of independent RF channels, wherein each independent RF channel delivers a distinct data stream to a corresponding UE device.

2. The system of claim 1, wherein the RF channel operates in a Frequency Division Duplex (FDD) mode.

3. The system of claim 1, wherein the RF channel operates in a Time Division Duplex (TDD) mode.

4. The system of claim 1, wherein the centralized processor is configured to obtain the CSI by exploiting uplink / downlink channel reciprocity.

5. The system of claim 1, wherein obtaining the CSI comprises receiving an uplink sounding signal from each of the plurality of UE devices.

6. The system of claim 1, wherein obtaining the CSI comprises receiving an uplink (UL) sounding signal from each of the plurality of UE devices, wherein the UL sounding signal occupies a bandwidth that is either a full bandwidth of the RF channel or a subband bandwidth that is narrower than the full bandwidth, and the centralized processor is configured to derive the CSI for the full bandwidth of the RF channel based on the UL sounding signal.

7. The system of claim 1, wherein obtaining the CSI comprises receiving an uplink (UL) sounding signal from each of the plurality of UE devices, wherein the UL sounding signal occupies a bandwidth that is either a full bandwidth of the RF channel or a subband bandwidth that is narrower than the full bandwidth, and the centralized processor is configured to derive the CSI for the full bandwidth of the RF channel based on the UL sounding signal, wherein the UL sounding signal is a 3rd Generation Partnership Project (3GPP) Sounding Reference Signal (SRS).

8. A method for providing direct-to-device satellite communications, comprising:receiving, at a centralized processor coupled to a network, a plurality of data streams intended for a plurality of user equipment (UE) devices located in a coverage area on a surface of a celestial body;obtaining, by the centralized processor, channel state information (CSI) characterizing a radio frequency (RF) channel between each of the plurality of UE devices and at least one antenna of each of a plurality of satellites orbiting above the coverage area;computing, by the centralized processor, precoding weights based on the obtained CSI for the plurality of UE devices;generating, by the centralized processor, a plurality of precoded waveforms by applying the computed precoding weights to the plurality of data streams; and cooperatively transmitting, by the plurality of satellites, the plurality of precoded waveforms such that the precoded waveforms combine coherently at the location of each of the plurality of UE devices to form a plurality of independent RF channels, wherein each independent RF channel delivers a distinct data stream to a corresponding UE device.

9. The method of claim 8, wherein the RF channel operates in a Frequency Division Duplex (FDD) mode.

10. The method of claim 8, wherein the RF channel operates in a Time Division Duplex (TDD) mode.

11. The method of claim 8, wherein obtaining the CSI comprises exploiting uplink / downlink channel reciprocity.

12. The method of claim 8, wherein obtaining the CSI comprises receiving an uplink sounding signal from each of the plurality of UE devices.

13. The method of claim 8, wherein obtaining the CSI comprises receiving an uplink (UL) sounding signal from each of the plurality of UE devices, wherein the UL sounding signal occupies a bandwidth that is either a full bandwidth of the RF channel or a subband bandwidth that is narrower than the full bandwidth, and further comprising deriving the CSI for the full bandwidth of the RF channel based on the UL sounding signal.

14. The method of claim 8, wherein obtaining the CSI comprises receiving an uplink (UL) sounding signal from each of the plurality of UE devices, wherein the UL sounding signal occupies a bandwidth that is either a full bandwidth of the RF channel or a subband bandwidth that is narrower than the full bandwidth, and further comprising deriving the CSI for the full bandwidth of the RF channel based on the UL sounding signal, wherein the UL sounding signal is a 3rd Generation Partnership Project (3GPP) Sounding Reference Signal (SRS).

15. A non-transitory computer-readable medium storing instructions that, when executed by one or more processors of a centralized processor coupled to a network, cause the centralized processor to perform operations comprising:receiving a plurality of data streams intended for a plurality of user equipment (UE) devices located in a coverage area on a surface of a celestial body;obtaining channel state information (CSI) characterizing a radio frequency (RF) channel between each of the plurality of UE devices and at least one antenna of each of a plurality of satellites orbiting above the coverage area;computing precoding weights based on the obtained CSI for the plurality of UE devices; andgenerating a plurality of precoded waveforms by applying the computed precoding weights to the plurality of data streams, wherein the precoded waveforms are configured to be cooperatively transmitted by the plurality of satellites such that they combine coherently at the location of each of the plurality of UE devices to form a plurality of independent RF channels, wherein each independent RF channel delivers a distinct data stream to a corresponding UE device.

16. The non-transitory computer-readable medium of claim 15, wherein the RF channel operates in a Frequency Division Duplex (FDD) mode.

17. The non-transitory computer-readable medium of claim 15, wherein the RF channel operates in a Time Division Duplex (TDD) mode.

18. The non-transitory computer-readable medium of claim 15, wherein obtaining the CSI comprises exploiting uplink / downlink channel reciprocity.

19. The non-transitory computer-readable medium of claim 15, wherein obtaining the CSI comprises receiving an uplink sounding signal from each of the plurality of UE devices.

20. The non-transitory computer-readable medium of claim 15, wherein obtaining the CSI comprises receiving an uplink (UL) sounding signal from each of the plurality of UE devices, wherein the UL sounding signal occupies a bandwidth that is either a full bandwidth of the RF channel or a subband bandwidth that is narrower than the full bandwidth, and the operations further comprise deriving the CSI for the full bandwidth of the RF channel based on the UL sounding signal.

21. The non-transitory computer-readable medium of claim 15, wherein obtaining the CSI comprises receiving an uplink (UL) sounding signal from each of the plurality of UE devices, wherein the UL sounding signal occupies a bandwidth that is either a full bandwidth of the RF channel or a subband bandwidth that is narrower than the full bandwidth, and the operations further comprise deriving the CSI for the full bandwidth of the RF channel based on the UL sounding signal, wherein the UL sounding signal is a 3rd Generation Partnership Project (3GPP) Sounding Reference Signal (SRS).

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