Reciprocity-assisted iterative beam space interference suppression

Abstract

According to some embodiments, a method performed by a network node for interference-aware downlink transmission comprises: estimating a downlink broadband interference covariance matrix from a plurality of received sounding reference signals, and determining a reciprocity assisted interference aware transmission precoder based on a matrix inversion associated with the downlink broadband interference covariance matrix. The matrix inversion is determined based on iterative inverse covariance estimation. The method further includes transmitting the downlink signal using a reciprocity assisted interference aware transmission precoder.

Description

Technical Field

[0001] Embodiments of the present disclosure relate to wireless communications, and more particularly, to reciprocity-assisted iterative beamspace interference suppression. Background Art

[0002] Generally, all terms used in this article should be interpreted according to their ordinary meaning in the relevant technical field, unless different meanings are clearly given and / or implied in the context of its use. Unless otherwise clearly stated, all references to elements, equipment, components, devices, steps, etc. should be openly interpreted as referring to at least one instance of elements, equipment, components, devices, steps, etc. The steps of any method disclosed herein are not necessarily performed in the exact order disclosed, unless a certain step is clearly described as after or before another step, and / or implies that a certain step must be after or before another step. Any feature of any embodiment disclosed herein can be applied to any other embodiment in appropriate circumstances. Similarly, any advantage of any embodiment can be applied to any other embodiment, and vice versa. Through the following description, other purposes, features and advantages of the attached embodiments will become clear.

[0003] Managing inter-cell interference can significantly improve the throughput of cellular systems, especially in dense deployment scenarios. For multiple input multiple output (MIMO) systems, downlink inter-cell interference management can be achieved by designing a downlink precoder so that the transmission power in the spatial direction of users in adjacent cells can be reduced (see P. Cheng, M. Tao, and W. Zhang, "Novel SLNR-based linear precoding for downlink multi-user multi-stream MIMO systems," IEEE Communications Letters, Vol. 14, No. 11, pp. 1008-1010, November 2010).

[0004] However, in massive MIMO systems, MIMO precoding significantly increases the complexity of the wireless transceiver due to the high dimensionality of the spatial signal space (see F. Rusek, D. Persson, B. K. Lau, E. G. Larsson, T. L. Marzetta, O. Edfors, and F. Tufvesson, “Scaling up MIMO: Opportunities and Challenges for Very Large Arrays,” IEEE Signal Processing Magazine, pp. 40–60, 2013). The computational complexity is further increased when interference-aware precoding is implemented due to the additional requirement of processing interference-related information. Fortunately, massive MIMO channels are expected to have low rank, since communication occurs in a low-dimensional subspace of the high-dimensional spatial signal space (see A. M. Sayeed, “Deconstructing Multi-Antenna Fading Channels,” IEEE Transactions on Signal Processing, vol. 50, no. 10, pp. 2563–2579, 2002).

[0005] Beamspace transforms have been proposed to exploit the reduced rank of the signal subspace, where a set of orthogonal beams are used to approximate the channel and reduce the complexity of subsequent signal processing operations for MIMO precoding (see A. Sayeed and J. Brady, "Beamspace MIMO for High-Dimensional Multiuser Communications at Millimeter-Wave Frequencies," IEEE Global Conference on Communications (GLOBECOM), 2013).

[0006] There are some challenges. For example, the traditional implementation of interference-aware downlink precoder calculation requires inverting the interference covariance matrix, whose dimension is equal to the number of base station antennas. For active antenna systems (AAS) with a large number of antennas, such as AIR 6488, the computational complexity of matrix inversion may be too high to be practically implemented. Summary of the invention

[0007] Based on the above description, there are some challenges in beamspace interference suppression. Certain aspects of the present disclosure and embodiments thereof may provide solutions to these or other challenges. For example, certain embodiments include implementations of interference-aware downlink precoder calculations with reduced computational complexity compared to conventional solutions. Rather than explicitly estimating an interference covariance matrix and inverting the estimate to calculate the precoder, certain embodiments iteratively estimate the inverse of the interference covariance matrix with reduced computational complexity.

[0008] Furthermore, in some embodiments, the channel estimate and the inverse covariance matrix are transformed to beam space, and dimensionality reduction is applied based on the diagonal elements of the inverse interference covariance matrix and the power of the channel estimate. The reduced dimensionality channel estimate and / or the reduced dimensionality inverse interference covariance are then used to calculate the precoder.

[0009] In general, certain embodiments include a reduced complexity interference-aware downlink precoding algorithm that uses iterative estimation of the inverse of the interference covariance matrix and beamspace dimensionality reduction to reduce out-of-cell interference leakage to neighboring cells. Certain embodiments include a system and method for downlink interference-aware precoding, which includes the following steps.

[0010] Certain embodiments include estimating an out-of-cell interference residual vector based on sounding measurements, which are used to iteratively update the inverse of the interference covariance matrix via a series of rank-1 updates. Some embodiments include beam reduction of the estimated inverse interference covariance matrix and / or channel estimates for target users. Some embodiments include computing an interference-aware downlink precoding matrix using the computed inverse interference covariance matrix and the channel estimates that may have been beam reduced.

[0011] Test results demonstrate that certain embodiments produce performance substantially close to that of full-dimensional conventional implementations, while significantly reducing the computational complexity of precoder calculations.

[0012] According to some embodiments, a method for interference-aware downlink transmission performed by a network node includes determining a reciprocity-assisted interference-aware transmission precoder based on a downlink wideband interference covariance matrix estimated from a plurality of received sounding reference signals and based on a matrix inversion associated with the downlink wideband interference covariance matrix. The matrix inversion is determined based on iterative inverse covariance estimation. The method also includes transmitting a downlink signal using the reciprocity-assisted interference-aware transmission precoder.

[0013] In a particular embodiment, the matrix inversion associated with the downlink wideband interference covariance matrix includes the matrix inversion of a regularized version of the downlink wideband interference covariance matrix.

[0014] In certain embodiments, the iterative inverse covariance estimation includes iteratively updating the inverse of the wideband interference covariance matrix according to the plurality of channel estimation residual vectors using a series of rank-one updates, each rank-one update corresponding to a residual vector of the plurality of channel estimation residual vectors. The rank-one update may use a Woodbury matrix identity.

[0015] In a particular embodiment, iterative inverse covariance estimation includes adding a cyclic Gaussian noise vector to each of the plurality of channel estimate residual vectors.

[0016] In certain embodiments, iterative inverse covariance estimation includes approximating the instantaneous noise correlation expression by an expected value of the instantaneous noise correlation expression.

[0017] In certain embodiments, the determination of the reciprocity-assisted interference-aware transmission precoder is further based on beamspace dimensionality reduction. The beamspace dimensionality reduction can be applied to the downlink wideband inverse interference covariance matrix, to the downlink channel estimate for determining the reciprocity-assisted interference-aware transmission precoder, or both.

[0018] According to some embodiments, a method performed by a network node includes determining a reciprocity-assisted interference-aware transmission precoder based on a downlink wideband interference covariance matrix estimated from a plurality of received sounding reference signals and based on a matrix inversion associated with the downlink wideband interference covariance matrix. The determination is based on beamspace dimensionality reduction. The method also includes transmitting a downlink signal using the reciprocity-assisted interference-aware transmission precoder.

[0019] In certain embodiments, beamspace dimensionality reduction is applied to a downlink wideband inverse interference covariance matrix, to a downlink channel estimate for determining a reciprocity-aided interference-aware transmit precoder, or both.

[0020] In certain embodiments, the beam space dimensionality reduction is based on spatial discrete Fourier transform basis vectors that are based on antenna array configurations of network nodes.

[0021] In certain embodiments, a set of active beams for beamspace dimensionality reduction is selected based on channel power and / or inverse interference covariance.

[0022] In certain embodiments, the set of active beams includes a fixed number of beams. The set of active beams may include a minimum number of active beams with a total collected power greater than or equal to a predetermined value and / or a plurality of beams with a power per beam above a threshold.

[0023] In certain embodiments, the matrix inversion is determined based on iterative inverse covariance estimation.

[0024] According to some embodiments, a network node comprises a processing circuit operable to perform any of the network node methods described above.

[0025] Another computer program product includes a non-transitory computer readable medium storing computer readable program code, which, when executed by a processing circuit, is operable to perform any of the methods performed by the network node described above.

[0026] Certain embodiments may provide one or more of the following technical advantages. For example, certain embodiments provide a low complexity implementation for downlink interference-aware precoding by avoiding the inversion of the full-dimensional interference covariance matrix. In particular, certain embodiments iteratively estimate the inverse of the interference covariance matrix and apply beamspace reduction to construct a downlink precoder that can suppress downlink inter-cell interference. BRIEF DESCRIPTION OF THE DRAWINGS

[0027] For a more complete understanding of the disclosed embodiments and their features and advantages, reference is now made to the following description taken in conjunction with the accompanying drawings, in which:

[0028] Figure 1 is a block diagram illustrating an example of Reciprocity-Aided Interference Aware Transmission (RAIT) precoder calculation;

[0029] Figure 2 is a block diagram illustrating reduced beam spatial precoder calculation of a user equipment (UE);

[0030] Figure 3 is a graph showing the relationship between the average downlink cell throughput and the number of users.

[0031] Figure 4 is a block diagram illustrating an example wireless network;

[0032] Figure 5 illustrates an example user device according to certain embodiments;

[0033] Fig. 6A is a flow chart illustrating an example method in a network node according to certain embodiments;

[0034] Figure 6B is another flow chart illustrating an example method in a network node according to certain embodiments; and

[0035] Figure 7 A schematic block diagram of a network node in a wireless network according to some embodiments is shown. DETAILED DESCRIPTION

[0036] Based on the above description, there are some challenges in beamspace interference suppression. Certain aspects of the present disclosure and embodiments thereof may provide solutions to these or other challenges. For example, certain embodiments include implementations of interference-aware downlink precoder calculations with reduced computational complexity compared to conventional solutions. Rather than explicitly estimating an interference covariance matrix and inverting the estimate to calculate the precoder, certain embodiments iteratively estimate the inverse of the interference covariance matrix with reduced computational complexity.

[0037] Furthermore, in some embodiments, the channel estimate and the inverse covariance matrix are transformed to beam space, and dimensionality reduction is applied based on the diagonal elements of the inverse interference covariance matrix and the power of the channel estimate. The reduced dimensionality channel estimate and / or the reduced dimensionality inverse interference covariance are then used to calculate the precoder.

[0038] Some embodiments contemplated herein will now be described more fully with reference to the accompanying drawings. However, other embodiments are included within the scope of the subject matter disclosed herein, and the disclosed subject matter should not be construed as being limited to the embodiments set forth herein; rather, these embodiments are provided by way of example to convey the scope of the subject matter to those skilled in the art. Although New Radio (NR) terminology may be used to describe specific problems and solutions, it should be understood that the same solutions also apply to Long Term Evolution (LTE) and other wireless networks, where applicable.

[0039] A specific example is described for a base station employing an M-element antenna array communicating with a user equipment (UE) equipped with N receive antennas. Let the N×M matrix H i (f, t) denotes a matrix containing the downlink channel coefficients from the base station to the i-th UE at frequency f and time t. In a time division duplex system where channel reciprocity can be assumed, channel estimates can be obtained at the base station (e.g., from uplink channel sounding transmissions) and used to calculate precoding coefficients for transmitting downlink data. Channel estimates can also be obtained using quantized feedback from the UE for use by the base station in downlink precoding, such as type 1 and type 2 codebook based beamforming in New Radio (NR).

[0040] The base station uses an M×L precoding matrix Transmit L≤min{M,N} spatial layers (streams) to the i-th UE. Matrix is normalized so that when l = 1, ..., L, in Representation Matrix The lth column of , and () H Represents the Hermitian transpose of a matrix.

[0041] Some examples include reciprocity-assisted transmission. Given the downlink channel estimate for the i-th UE, H i (f, t), the precoding matrix of the i-th UE can be calculated based on the minimum mean square error (MMSE) design criterion The reciprocity aided transmission (RAT) precoder is calculated by the following non-normalized precoder W i,RAT (f, t) to calculate:

[0042]

[0043] where δ 2 is the MMSE regularization factor, IL is the L×L identity matrix, and is the L×M matrix corresponding to the downlink channel of the i-th UE after port mixing / selection.

[0044] matrix The full-dimensional downlink channel H can be selected based on some selection criteria i (f, t) by constructing some rows of (f, t), for example, selecting the row with the highest norm. Alternatively, the selected channel matrix By mixing the full-dimensional channel H i (f, t) is constructed by Among them U i (f,t) is the L×N port mixing matrix of the i-th UE. The rank-LMMSE precoder for each subband is given by Given, and by scaling each of its columns so that its norm is equal to So from the matrix W i,RAT (f, t) is obtained.

[0045] Some examples include wideband reciprocity-assisted interference-aware transmission. In dense deployment scenarios where base stations are located close together, UEs may experience interference from downlink transmissions from neighboring base stations, resulting in significant downlink throughput degradation, especially for UEs located at the cell edge. Interference-aware downlink transmission schemes design the precoding matrix so that the received signal power at the target UE is high enough while limiting the interference caused to UEs in neighboring cells.

[0046] Let the M×M matrix Λ(t) represent the downlink broadband interference covariance matrix, that is, the covariance matrix of the downlink channel vector to users outside the cell. In a time division duplex system, the matrix Λ(t) can be estimated based on the uplink signal received by the base station at the time of the sounding transmission. Let x RS,i,j (f,t RS ) represents the signal from UE i at subcarrier frequency f and time t RS The reference symbol of the uplink transmission from the sounding reference signal (SRS) port j is obtained, and y RS (f,t RS ) represents the corresponding M×1 received signal vector of the base station. Subtracting the expected received signal vector of the sounding sequence transmitted by the UE attached to the cell from the received uplink signal vector can generate the out-of-cell interference vector sample due to the transmission of the out-of-cell user, that is,

[0047]

[0048] where h i,j (f,t RS) is the estimated uplink channel vector of UEi transmitted from port j to the base station, and the summation in the above formula is for the transmission at frequency f and time t RS The down-scheduled uplink SRS transmission is performed by the UE attached to the cell.

[0049] Then, the instantaneous wideband interference covariance matrix is ​​obtained by calculating the second-order statistics of the out-of-cell interference vector samples by averaging different frequencies: Right now

[0050]

[0051] Where N f is the number of frequency carriers used for uplink SRS transmission. The estimated uplink interference covariance matrix Λ(t RS ),Right now

[0052]

[0053] Where 0<β≤1 is the forgetting factor, i.e., β=1 corresponds to no time filtering. The filtered broadband interference covariance matrix Λ(t RS ) is used as an estimate of Λ(t) until a filtered estimate of the next sounding transmission time slot is obtained.

[0054] The reciprocity-assisted interference-aware transmission (RAIT) precoder is the non-normalized precoder W of the i-th UE calculated as follows i,RAIT (f,t) is calculated

[0055]

[0056] And normalize the RAIT precoder By scaling each column so that its norm is equal to From W i,RAIT (f, t) is obtained. A direct implementation of the RAIT beamformer requires estimating the M×M matrix Λ(t) and inverting Λ(t)+δ 2 I M Since regularization interferes with the inversion of the covariance matrix, (Λ(t)+δ 2 I M ) -1 , and matrix multiplication The computational complexity of these operations may be too high for practical implementation of massive MIMO base stations.

[0057] Certain embodiments described herein reduce the complexity of RAIT computations by reducing the complexity of matrix inversion via iterative inverse covariance estimation and / or by reducing the complexity of inverse covariance and channel multiplication via beam reduction.

[0058] A specific embodiment includes iterative inverse interference covariance estimation. Let indicates that it contains RS A set of M×1 SRS channel estimation residual vectors for different subcarriers of . Certain embodiments iteratively update the inverse of the covariance matrix directly from the residual vectors using a series of rank-1 updates (each rank-1 update corresponds to a residual vector). Some embodiments use the Woodbury matrix identity

[0059]

[0060] Where A is an M×M complex matrix, b is an M×1 complex vector, and c is a scalar. Some embodiments repeatedly apply the matrix identity to the inverse of the filter covariance matrix, i.e.,

[0061]

[0062] where Λ -1 The initial value of (-1) is chosen to be And ∈<<1 is a scalar. Update Λ -1 (t RS ) is given by:

[0063] Given a previous estimate Λ -1 (t RS -1). At time t RS ,when When available, do:

[0064] calculate

[0065] At f = 1:N f -1, do:

[0066] calculate

[0067] Ends at

[0068] gather

[0069] Since the RAIT precoder needs to invert the regularized version of the broadband interference covariance matrix, that is, (Λ(t)+δ 2 I M ) -1 , certain embodiments modify the above iterative algorithm to compensate for the diagonal loading factor. In some embodiments, this is accomplished by replacing2 This is achieved by adding the cyclic Gaussian noise vector of I to the detection residual, that is,

[0070]

[0071] where n(f,t RS ) is a covariance δ 2 I M An independent and identically distributed M×1 random cyclic Gaussian vector of . Sample Used to update the inverse covariance as described above.

[0072] Some embodiments directly iteratively update (Λ(t)+δ) by approximating the instantaneous noise correlation expression with the expected value of the instantaneous noise correlation expression. 2 I) -1 , without generating noise samples, that is

[0073] (r H (f,t RS )+n H (f,t RS ))S k-1 (t RS )(r(f,t RS )+n(f,t RS ))≈r H (f,t RS )S k-1 (t RS )r(f,t RS )+δ 2 tr{S k-1 (t RS )}

[0074] S k-1 (t RS )(r(f,t RS )+n(f,t RS ))(r H (f,t RS )+n H (f,t RS ))S k-1 (t RS )≈S k-1 (t RS )(r(f,t RS )r H (f,t RS )+δ 2 I)S k-1 (t RS )

[0075] Using the above approximation, in a particular embodiment, the regularized inverse covariance matrix Γ -1(t)=(Λ(t)+δ 2 I) -1 The iterative algorithm is expressed as

[0076] Given a previous estimate Γ -1 (t RS -1). At time t RS ,when When available, do:

[0077] calculate

[0078] At f = 1:N f -1, do:

[0079] calculate

[0080] Ends at

[0081] set up

[0082] Figure 1 A block diagram of an iterative RAIT precoder calculation method is shown, wherein the inverse covariance matrix is ​​iteratively updated according to the detection residual based on the above process and is used to calculate the precoding matrix

[0083] Some embodiments include beamspace dimensionality reduction. Beamspace transforms have previously been used to exploit the low rank of a signal subspace, where a set of orthogonal basis beams are used to approximate the downlink channel as a linear combination of a reduced subset of orthogonal basis beams, and the reduced beamspace basis subset is selected to provide the best approximation of the channel.

[0084] Certain embodiments described herein use beamspace dimensionality reduction on the downlink channel estimate and / or the inverse of the interference covariance matrix to reduce the computational complexity of calculating the RAIT precoder. In this case, Figure 1 The precoder calculation of UEi block in Figure 2 The downlink channel and inverse interference covariance matrix estimates are transformed to beam space and dimension reduction is applied to the inverse interference covariance matrix and / or beam space channel estimates. The same set of active beams is used for dimension reduction of the channel and inverse covariance matrices, where the criteria for selecting the active beam is based on the channel power and / or the power in the inverse interference covariance. Figure 2 The following algorithms may be used.

[0085] Some embodiments include beamspace transforms. Let the M×M matrix B represent the beamspace basis matrix. The columns of the matrix B may consist of spatial discrete Fourier transform (SDFT) basis vectors based on the base station antenna array configuration. For example, consider a polarized two-dimensional antenna array at a base station, where M V and M H They represent the number of rows and columns of the two-dimensional antenna array at the base station, that is, the total number of antenna elements is M = 2M V M H The M×M matrix containing the basis of the SDFT beam space basis matrix is ​​given by

[0086]

[0087] Among them I 2 is the 2×2 identity matrix, and the two matrices D H and D V It is M H ×M H and M V ×M V The DFT matrix, i.e. D X The (m,k) element of Given, where m, k = 0, ..., M X -1.

[0088] L×M antenna spatial channel of the i-th UE and the broadband regularized interference covariance Γ -1 (t)=(Λ(t)+δ 2 I) -1 The M×M inverse is transformed into beam space

[0089]

[0090] Dimensionality reduction can be applied to beamspace channel estimation as follows

[0091]

[0092] Where D i (t) is a diagonal M×M, containing 1s at the locations of the active beams and 0s at other locations.

[0093] Dimensionality reduction can also be applied to the off-diagonal elements of the beamspace inverse covariance matrix

[0094]

[0095] in And the operator diagMtx{X} constructs a diagonal matrix from the diagonal elements of the matrix X.

[0096] Several options can be chosen for beamspace dimensionality reduction. For example, dimensionality reduction can be applied only to the channel estimate, and the beamspace reduced precoder is calculated as

[0097]

[0098] Alternatively, beam reduction can be applied only to the beamspace inverse covariance matrix, i.e.,

[0099]

[0100] Finally, beam reduction can be applied to the channel estimate and the inverse covariance matrix, where the precoder is given by

[0101]

[0102] The beam space precoder is converted back to antenna space

[0103] Some embodiments include beam selection metric calculation. Several criteria may be used to select active beams for dimensionality reduction of the UE channel and / or inverse covariance matrix. The selection criteria may be based on the UE's channel power and / or the power of the inverse interference covariance, as shown below.

[0104] In some embodiments, the selection criterion is based on filtered channel power. In this case, the broadband instantaneous power of each beam of the i-th UE is first calculated based on the channel estimate obtained from the sounding reception, that is,

[0105]

[0106] where h i,j (f,t RS ) is the time t RS is the M×1 uplink channel vector obtained from SRS reception and transmitted on SRS detection port j at time [x], and b represents the bth component of vector x. Next, the filtered power of each beam is The calculation is as follows

[0107]

[0108] Where 0<γ<1 is the time filter memory parameter used for each beam power calculation. The filtered channel power at the latest detection time Use as until an estimate of the next probe transmission time slot is obtained.

[0109] In some embodiments, the selection criterion is based on the inverse covariance power. In this case, the filtered inverse interference power is obtained directly from the diagonal elements of the filtered wideband beam spatial inverse covariance matrix as follows

[0110]

[0111] where diag{X} represents an M×1 vector obtained by stacking the diagonal elements of the M×M matrix X. Filtered interference power For all UEs.

[0112] In some embodiments, the selection criterion is based on the channel multiplied by the inverse covariance power. and the broadband inverse interference covariance power per beam The channel multiplied by the inverse covariance power for the i-th UE is calculated as follows

[0113]

[0114] Where α<<1 is the regularization factor.

[0115] Some embodiments include active beam selection. Several methods are proposed for active beam selection using any of the metrics described above. Based on the selected metric, active beam selection can be different for different UEs. For example, using filtered channel power or channel multiplied by inverse covariance power may produce different active beams for different UEs. In contrast, using the inverse covariance power metric, the selected beam is the same for all UEs.

[0116] Let A i (t) represents the set of active beams containing the i-th UE, and let p i (b, t) represents the metric for beam selection for the i-th UE. The active beam can be selected using any of the following methods.

[0117] Some embodiments use a fixed number of active beams approach to select active beams. These embodiments select a fixed number of beams that produce the largest metric sum

[0118] Some embodiments use the collected power in the active beam method to select active beams. These embodiments select the minimum number of beams whose total metric is greater than a fraction κ of the total metric in all beams, i.e., the set of active beams is the solution to the following optimization problem

[0119] min|A i (t)|Satisfaction

[0120] Where |A i (t)| represents the set A i (t) cardinality.

[0121] Some embodiments use a threshold-based beam activation method to select active beams. These embodiments select beams whose metric values ​​are greater than a threshold τ of the total metric, i.e., the set of selected active beams is given by

[0122]

[0123] Numerical simulations can be used to illustrate the performance of specific embodiments. A specific example simulates a time division duplex (TDD) system with a bandwidth of 36MHz, a subcarrier spacing of 30KHz, and a carrier frequency of 3.5GHz. The example uses a multi-cell deployment scenario with 3 sites, 3 cells per site, and a site-to-site distance of 200m. Each UE is equipped with 4 antennas and randomly placed in the simulation area. This simulation uses the 5G spatial correlation model urban macro channel model. The antenna configuration of the base station is an active antenna system (AAS) 4x8x2 configuration. The traffic model for the downlink is selected as full buffering. Channel estimation is obtained using a full-band sounding reference symbol, which is transmitted from one antenna port by each UE every 6 milliseconds, and antenna port switching is enabled, that is, complete channel information is obtained from all ports every 24 milliseconds.

[0124] Figure 3 The relationship between the average downlink cell throughput and the number of users for different RAIT precoding algorithms is shown. Figure 3 The downlink cell throughput using the RAT precoder without any out-of-cell interference suppression capability is also shown.The proposed antenna spatial iterative covariance inversion algorithm yields a performance very close to that of the full matrix inverse RAIT algorithm.

[0125] Figure 3 The downlink cell throughput of the proposed beamspace iterative inverse covariance calculation algorithm is also shown, where the active beam is selected based on the channel multiplied by the inverse covariance power metric and dimension reduction is applied only to the channel estimate. Using only 24 reduced beams can still significantly improve the cell throughput compared to RAT beamforming. In particular, the beamspace precoding algorithm retains 85% of the interference cancellation gain, i.e., a throughput gain that is higher than the throughput gain achieved by the RAT precoder.

[0126] Figure 4An example wireless network according to certain embodiments is shown. The wireless network may include and / or be connected to any type of communication, telecommunication, data, cellular and / or radio network or other similar type of system. In some embodiments, the wireless network may be configured to operate according to a specific standard or other type of predefined rules or procedures. Thus, a specific embodiment of the wireless network may implement communication standards such as Global System for Mobile Communications (GSM), Universal Mobile Telecommunications System (UMTS), Long Term Evolution (LTE) and / or other suitable 2G, 3G, 4G or 5G standards; wireless local area network (WLAN) standards such as IEEE 802.11 standards; and / or any other suitable wireless communication standards such as Worldwide Interoperability for Microwave Access (WiMax), Bluetooth, Z-Wave and / or ZigBee standards.

[0127] The network 106 may include one or more backhaul networks, core networks, IP networks, public switched telephone networks (PSTN), packet data networks, optical networks, wide-area networks (WAN), local area networks (LAN), wireless local area networks (WLAN), wired networks, wireless networks, metropolitan area networks, and other networks to enable communication between devices.

[0128] The network node 160 and the WD 110 include various components described in more detail below. These components work together to provide network node and / or wireless device functions, such as providing wireless connections in a wireless network. In different embodiments, the wireless network may include any number of wired or wireless networks, network nodes, base stations, controllers, wireless devices, relay stations, and / or any other components or systems that can facilitate or participate in the communication of data and / or signals, whether via a wired connection or a wireless connection.

[0129] As used herein, a network node refers to a device capable of, configured to, arranged to, and / or operable to communicate directly or indirectly with a wireless device and / or other network nodes or devices in a wireless network to enable and / or provide wireless access to the wireless device and / or perform other functions (e.g., management) in the wireless network.

[0130] Examples of network nodes include, but are not limited to, access points (APs) (e.g., radio access points), base stations (BSs) (e.g., radio base stations, Node Bs, evolved Node Bs (eNBs), and NR Node Bs (gNBs). Base stations can be classified based on the coverage they provide (or in other words, their transmit power levels), and can then also be referred to as femto base stations, pico base stations, micro base stations, or macro base stations.

[0131] A base station may be a relay node or a relay donor node that controls a relay. A network node may also include one or more (or all) parts of a distributed radio base station, such as a centralized digital unit and / or a remote radio unit (RRU), sometimes also referred to as a remote radio head (RRH). Such a remote radio unit may or may not be integrated with an antenna as an antenna-integrated radio. The parts of a distributed radio base station may also be referred to as nodes in a distributed antenna system (DAS). Other examples of network nodes include Multi-Standard Radio (MSR) equipment such as MSR base stations, network controllers such as Radio Network Controller (RNC) or Base Station Controller (BSC), Base Transceiver Station (BTS), transmission points, transmission nodes, Multicast Coordination Entity (MCE), core network nodes (e.g., MSC, MME), O&M nodes, OSS nodes, SON nodes, positioning nodes (e.g., E-SMLC) and / or MDT.

[0132] As another example, a network node may be a virtual network node, as described in more detail below. However, more generally, a network node may represent any suitable device (or group of devices) that is capable of, configured to, arranged to, and / or operable to enable a wireless device to access a wireless network or to provide a wireless device with access to a wireless network, or to provide some service to a wireless device that has accessed a wireless network.

[0133] exist Figure 4 In FIG. 1 , the network node 160 includes a processing circuit 170, a device readable medium 180, an interface 190, an auxiliary device 184, a power supply 186, a power supply circuit 187, and an antenna 162. Figure 4 The network node 160 shown in the example wireless network of FIG. 1 may represent a device including the shown combination of hardware components, but other embodiments may include network nodes having different combinations of components.

[0134] It should be understood that the network node includes any suitable combination of hardware and / or software required to perform the tasks, features, functions, and methods disclosed herein. In addition, although the components of the network node 160 are depicted as a single box within a larger box, or nested within multiple boxes, in reality, the network node may include multiple different physical components that constitute a single illustrated component (e.g., the device readable medium 180 may include multiple separate hard disks and multiple RAM modules).

[0135] Similarly, the network node 160 may be composed of multiple physically separate components (e.g., a Node B component and an RNC component, or a BTS component and a BSC component, etc.), each of which may have its own components. In some scenarios, the network node 160 includes multiple separate components (e.g., BTS and BSC components), one or more of which may be shared by several network nodes. For example, a single RNC may control multiple Node Bs. In this case, each unique Node B and RNC pair may be considered a single separate network node in some cases.

[0136] In some embodiments, the network node 160 may be configured to support multiple radio access technologies (Radio Access Technology, RAT). In such embodiments, some components may be replicated (e.g., separate device readable media 180 for different RATs), and some components may be reused (e.g., the same antenna 162 may be shared by multiple RATs). The network node 160 may also include multiple sets of various illustrated components of different wireless technologies integrated into the network node 160, such as GSM, WCDMA, LTE, NR, WiFi, or Bluetooth wireless technologies. These wireless technologies may be integrated into the same or different chips or chipsets and other components within the network node 160.

[0137] The processing circuit 170 is configured to perform any determination, calculation, or similar operation (e.g., certain acquisition operations) provided by the network node as described herein. These operations performed by the processing circuit 170 may include processing information obtained by the processing circuit 170, for example, by converting the obtained information into other information, comparing the obtained information or the converted information with information stored in the network node, and / or performing one or more operations based on the obtained information or the converted information and making a determination based on the processed results.

[0138] The processing circuit 170 may include a combination of one or more of the following: a microprocessor, a controller, a microcontroller, a central processing unit, a digital signal processor, an application specific integrated circuit, a field programmable gate array, or any other suitable computing device, resource, or combination of hardware, software, and / or encoded logic that is operable to provide network node 160 functionality alone or in combination with other network node 160 components (e.g., device readable medium 180).

[0139] For example, processing circuit 170 may execute instructions stored in device readable medium 180 or in a memory within processing circuit 170. Such functionality may include providing any of the various wireless features, functions, or advantages discussed herein. In some embodiments, processing circuit 170 may include a system on chip (System On Chip, SOC).

[0140] In some embodiments, the processing circuit 170 may include one or more of a radio frequency (RF) transceiver circuit 172 and a baseband processing circuit 174. In some embodiments, the radio frequency (RF) transceiver circuit 172 and the baseband processing circuit 174 may be located on separate chips (or chipsets), boards, or units (e.g., a radio unit and a digital unit). In alternative embodiments, part or all of the RF transceiver circuit 172 and the baseband processing circuit 174 may be located on the same chip or chipset, board, or unit.

[0141] In some embodiments, some or all of the functions provided by a network node, base station, eNB, or other such network device described herein may be performed by a processing circuit 170 executing instructions stored on a device-readable medium 180 or a memory within the processing circuit 170. In alternative embodiments, some or all of the functions may be provided by the processing circuit 170, for example, in a hardwired manner, without executing instructions stored on a separate or discrete device-readable medium. In any of these embodiments, the processing circuit 170 may be configured to perform the functions, regardless of whether instructions stored on a device-readable storage medium are executed. The benefits provided by such functions are not limited to separate processing circuits 170 or other components of the network node 160, but are enjoyed by the network node 160 as a whole and / or by end users and wireless networks in general.

[0142] The device-readable medium 180 may include any form of volatile or non-volatile computer-readable memory, including but not limited to persistent storage, solid-state memory, remotely mounted memory, magnetic media, optical media, random access memory (RAM), read-only memory (ROM), mass storage media (e.g., hard disk), removable storage media (e.g., flash drive, compact disk (CD) or digital video disk (DVD)), and / or any other volatile or non-volatile, non-transitory device-readable and / or computer-executable memory device, storing information, data and / or instructions that can be used by the processing circuit 170. The device-readable medium 180 may store any suitable instructions, data or information, including computer programs, software, applications including one or more of logic, rules, codes, tables, etc., and / or other instructions that can be executed by the processing circuit 170 and utilized by the network node 160. The device-readable medium 180 may be used to store any calculations performed by the processing circuit 170 and / or any data received via the interface 190. In some embodiments, processing circuitry 170 and device readable medium 180 may be considered integral.

[0143] Interface 190 is used for wired or wireless communication of signaling and / or data between network node 160, network 106, and / or WD 110. As shown, interface 190 includes port / terminal 194 for sending data to network 106 and receiving data from network 106, for example, via a wired connection. Interface 190 also includes radio front-end circuitry 192, which may be coupled to antenna 162, or in some embodiments is part of antenna 162.

[0144] The radio front end circuit 192 includes a filter 198 and an amplifier 196. The radio front end circuit 192 can be connected to the antenna 162 and the processing circuit 170. The radio front end circuit can be configured to adjust the signal transmitted between the antenna 162 and the processing circuit 170. The radio front end circuit 192 can receive digital data to be sent out to other network nodes or WDs via a wireless connection. The radio front end circuit 192 can use a combination of filters 198 and / or amplifiers 196 to convert the digital data into a radio signal with appropriate channel and bandwidth parameters. The radio signal can then be transmitted via the antenna 162. Similarly, when receiving data, the antenna 162 can collect the radio signal, which is then converted into digital data by the radio front end circuit 192. The digital data can be passed to the processing circuit 170. In other embodiments, the interface may include different components and / or different combinations of components.

[0145] In some alternative embodiments, the network node 160 may not include a separate radio front end circuit 192, and instead, the processing circuit 170 may include the radio front end circuit and may be connected to the antenna 162 without the separate radio front end circuit 192. Similarly, in some embodiments, all or some of the RF transceiver circuit 172 may be considered part of the interface 190. In other embodiments, the interface 190 may include one or more ports or terminals 194, the radio front end circuit 192, and the RF transceiver circuit 172 as part of a radio unit (not shown), and the interface 190 may communicate with the baseband processing circuit 174 as part of a digital unit (not shown).

[0146] Antenna 162 may include one or more antennas or antenna arrays configured to send and / or receive wireless signals. Antenna 162 may be coupled to radio front-end circuitry 192 and may be any type of antenna capable of wirelessly transmitting and receiving data and / or signals. In some embodiments, antenna 162 may include one or more omnidirectional, sectored, or flat panel antennas operable to transmit / receive radio signals, for example, between 2 GHz and 66 GHz. Omnidirectional antennas may be used to transmit / receive radio signals in any direction, sectored antennas may be used to transmit / receive radio signals from / to devices within a specific area, and flat panel antennas may be line-of-sight antennas for transmitting / receiving radio signals in a relatively straight line. In some cases, the use of more than one antenna may be referred to as MIMO. In some embodiments, antenna 162 may be separated from network node 160 and may be connected to network node 160 via an interface or port.

[0147] Antenna 162, interface 190 and / or processing circuit 170 can be configured to perform any receiving operation and / or certain acquisition operation performed by the network node as described herein. Any information, data and / or signal can be received from a wireless device, another network node and / or any other network device. Similarly, antenna 162, interface 190 and / or processing circuit 170 can be configured to perform any transmission operation performed by the network node as described herein. Any information, data and / or signal can be transmitted to a wireless device, another network node and / or any other network device.

[0148] Power circuit 187 may include or be coupled to power management circuitry and is configured to provide power to components of network node 160 to perform the functions described herein. Power circuit 187 may receive power from power supply 186. Power supply 186 and / or power circuit 187 may be configured to provide power to various components of network node 160 in a form suitable for the various components (e.g., at the voltage and current levels required by the various components). Power supply 186 may be included in power circuit 187 and / or network node 160, or external to power circuit 187 and / or network node 160.

[0149] For example, the network node 160 can be connected to an external power source (e.g., a power outlet) via an input circuit or interface (e.g., a cable), whereby the external power source supplies power to the power circuit 187. As another example, the power supply 186 can include a power source in the form of a battery or a battery pack, which is connected to or integrated in the power circuit 187. If the external power source fails, the battery can provide backup power. Other types of power sources, such as photovoltaic devices, can also be used.

[0150] Alternative embodiments of network node 160 may include Figure 4 , which additional components may be responsible for providing certain aspects of the network node functionality, including any functionality described herein and / or any functionality required to support the subject matter described herein. For example, the network node 160 may include a user interface device to allow information to be input into the network node 160 and to allow information to be output from the network node 160. This may allow a user to perform diagnostics, maintenance, repair, and other management functions with respect to the network node 160.

[0151] As used herein, a wireless device (WD) refers to a device capable of, configured to, arranged to, and / or operable to communicate wirelessly with a network node and / or other wireless devices. Unless otherwise specified, the term WD is used interchangeably with user equipment (UE) herein. Wireless communication may involve the use of electromagnetic waves, radio waves, infrared waves, and / or other types of signals suitable for transmitting information through the air to transmit and / or receive wireless signals.

[0152] In some embodiments, the WD may be configured to transmit and / or receive information without direct human-computer interaction. For example, the WD may be designed to transmit information to the network according to a predetermined schedule when triggered by an internal or external event or in response to a request from the network.

[0153] Examples of WD include, but are not limited to, smartphones, mobile phones, cellular phones, voice over IP (VoIP) phones, wireless local loop phones, desktop computers, personal digital assistants (PDAs), wireless cameras, game consoles or devices, music storage devices, playback devices, wearable terminal devices, wireless endpoints, mobile stations, tablet computers, laptops, laptop-embedded equipment (LEE), laptop-mounted equipment (LME), smart devices, wireless client equipment (CPE), vehicle-mounted wireless terminal devices, etc. WD may support device-to-device (D2D) communication, vehicle-to-vehicle (V2V), vehicle-to-infrastructure (V2I), and vehicle-to-everything (V2X), for example, by implementing the 3GPP standard for sidelink communication, and in this case may be referred to as a D2D communication device.

[0154] As another specific example, in the Internet of Things (IoT) scenario, a WD may represent a machine or other device that performs monitoring and / or measurement and transmits the results of such monitoring and / or measurement to another WD and / or network node. In this case, the WD may be a machine-to-machine (M2M) device, which may be referred to as an MTC device in the 3GPP context. As an example, a WD may be a UE that implements the 3GPP Narrowband Internet of Things (NB-IoT) standard. Examples of such machines or devices include sensors, metering equipment (e.g., power meters), industrial machinery, or household or personal appliances (e.g., refrigerators, televisions, etc.), personal wearable devices (e.g., watches, fitness trackers, etc.).

[0155] In other scenarios, a WD may represent a vehicle or other device capable of monitoring and / or reporting its operating status or other functions associated with its operation. A WD as described above may represent an endpoint of a wireless connection, in which case the device may be referred to as a wireless terminal. In addition, a WD as described above may be mobile, in which case it may also be referred to as a mobile device or a mobile terminal.

[0156] As shown, wireless device 110 includes antenna 111, interface 114, processing circuit 120, device-readable medium 130, user interface device 132, auxiliary device 134, power supply 136, and power supply circuit 137. WD 110 may include one or more of the components shown for multiple sets of different wireless technologies (e.g., GSM, WCDMA, LTE, NR, WiFi, WiMAX, or Bluetooth wireless technologies, to mention just a few) supported by WD 110. These wireless technologies may be integrated into the same or different chips or chipsets as other components within WD 110.

[0157] Antenna 111 may include one or more antennas or antenna arrays configured to send and / or receive wireless signals, and is connected to interface 114. In some alternative embodiments, antenna 111 may be separated from WD 110 and may be connected to WD 110 via an interface or port. Antenna 111, interface 114, and / or processing circuit 120 may be configured to perform any receiving or transmitting operation performed by WD as described herein. Any information, data, and / or signal may be received from a network node and / or another WD. In some embodiments, the radio front-end circuit and / or antenna 111 may be considered an interface.

[0158] As shown, the interface 114 includes a radio front-end circuit 112 and an antenna 111. The radio front-end circuit 112 includes one or more filters 118 and an amplifier 116. The radio front-end circuit 112 is connected to the antenna 111 and the processing circuit 120, and is configured to condition the signals transmitted between the antenna 111 and the processing circuit 120. The radio front-end circuit 112 may be coupled to the antenna 111 or a portion of the antenna 111. In some embodiments, the WD 110 may not include a separate radio front-end circuit 112; instead, the processing circuit 120 may include the radio front-end circuit and may be connected to the antenna 111. Similarly, in some embodiments, some or all of the RF transceiver circuit 122 may be considered part of the interface 114.

[0159] The radio front end circuit 112 can receive digital data to be sent outward to other network nodes or WDs via a wireless connection. The radio front end circuit 112 can use a combination of filters 118 and / or amplifiers 116 to convert the digital data into a radio signal with appropriate channel and bandwidth parameters. The radio signal can then be transmitted via the antenna 111. Similarly, when receiving data, the antenna 111 can collect the radio signal, which is then converted into digital data by the radio front end circuit 112. The digital data can be passed to the processing circuit 120. In other embodiments, the interface may include different components and / or different combinations of components.

[0160] The processing circuit 120 may include a combination of one or more of the following: a microprocessor, a controller, a microcontroller, a central processing unit, a digital signal processor, an application specific integrated circuit, a field programmable gate array, or any other suitable computing device, resource, or combination of hardware, software, and / or encoded logic, which is operable to provide WD 110 functionality alone or in combination with other WD 110 components (e.g., device readable medium 130). Such functionality may include providing any of the various wireless features or advantages discussed herein. For example, the processing circuit 120 may execute instructions stored in the device readable medium 130 or in a memory within the processing circuit 120 to provide the functionality disclosed herein.

[0161] As shown, the processing circuit 120 includes one or more of an RF transceiver circuit 122, a baseband processing circuit 124, and an application processing circuit 126. In other embodiments, the processing circuit may include different components and / or different combinations of components. In some embodiments, the processing circuit 120 of the WD 110 may include a SOC. In some embodiments, the RF transceiver circuit 122, the baseband processing circuit 124, and the application processing circuit 126 may be on a separate chip or chipset.

[0162] In alternative embodiments, part or all of the baseband processing circuitry 124 and the application processing circuitry 126 may be combined into one chip or chipset, and the RF transceiver circuitry 122 may be on a separate chip or chipset. In other alternative embodiments, part or all of the RF transceiver circuitry 122 and the baseband processing circuitry 124 may be on the same chip or chipset, and the application processing circuitry 126 may be on a separate chip or chipset. In other alternative embodiments, part or all of the RF transceiver circuitry 122, the baseband processing circuitry 124, and the application processing circuitry 126 may be combined in the same chip or chipset. In some embodiments, the RF transceiver circuitry 122 may be part of the interface 114. The RF transceiver circuitry 122 may condition RF signals for the processing circuitry 120.

[0163] In some embodiments, some or all of the functions performed by the WD described herein may be provided by processing circuit 120 executing instructions stored on device readable medium 130, which in some embodiments may be a computer readable storage medium. In alternative embodiments, some or all of the functions may be provided by processing circuit 120, for example in a hardwired manner, without executing instructions stored on a separate or discrete device readable storage medium.

[0164] In any of these embodiments, processing circuit 120 may be configured to perform the described functionality, whether or not executing instructions stored on a device-readable storage medium. The benefits provided by such functionality are not limited to processing circuit 120 or other components of WD 110, but are generally enjoyed by WD 110 and / or end users and wireless networks.

[0165] Processing circuit 120 may be configured to perform any determination, calculation, or similar operation (e.g., certain acquisition operations) performed by WD as described herein. Such operations performed by processing circuit 120 may include processing information obtained by processing circuit 120, for example, by converting the obtained information to other information, comparing the obtained information or the converted information to information stored by WD 110, and / or performing one or more operations based on the obtained information or the converted information and making a determination based on the processed results.

[0166] Device-readable medium 130 is operable to store computer programs, software, applications including one or more of logic, rules, codes, tables, etc., and / or other instructions executable by processing circuit 120. Device-readable medium 130 may include computer memory (e.g., random access memory (RAM) or read-only memory (ROM)), mass storage media (e.g., hard disk), removable storage media (e.g., compact disk (CD) or digital video disk (DVD)), and / or any other volatile or non-volatile, non-transitory device-readable and / or computer-executable memory device that stores information, data, and / or instructions that may be used by processing circuit 120. In some embodiments, processing circuit 120 and device-readable medium 130 may be integral.

[0167] The user interface device 132 may provide a component that allows a human user to interact with the WD 110. This interaction may be in a variety of forms, such as visual, auditory, tactile, etc. The user interface device 132 may be operable to generate output to the user and allow the user to provide input to the WD 110. The type of interaction may vary depending on the type of user interface device 132 installed in the WD 110. For example, if the WD 110 is a smart phone, the interaction may be performed via a touch screen; if the WD 110 is a smart meter, the interaction may be performed through a screen that provides usage (e.g., gallons used) or a speaker that provides an audible alarm (e.g., if smoke is detected).

[0168] The user interface device 132 may include an input interface, device and circuit, and an output interface, device and circuit. The user interface device 132 is configured to allow information to be input into the WD 110, and is connected to the processing circuit 120 to allow the processing circuit 120 to process the input information. The user interface device 132 may include, for example, a microphone, a proximity sensor or other sensor, a key / button, a touch display, one or more cameras, a USB port or other input circuit. The user interface device 132 is also configured to allow information to be output from the WD 110, and allows the processing circuit 120 to output information from the WD 110. The user interface device 132 may include, for example, a speaker, a display, a vibration circuit, a USB port, a headphone interface or other output circuit. The WD 110 may use one or more input and output interfaces, devices and circuits of the user interface device 132 to communicate with the end user and / or wireless network, and allow them to benefit from the functions described herein.

[0169] Auxiliary device 134 is operable to provide more specific functions that may not normally be performed by a WD. This may include specialized sensors for measuring for various purposes, interfaces for other types of communications (e.g., wired communications, etc.). The inclusion and type of components of auxiliary device 134 may vary depending on the embodiment and / or scenario.

[0170] In some embodiments, power source 136 may be in the form of a battery or battery pack. Other types of power sources may also be used, such as an external power source (e.g., a power outlet), a photovoltaic device, or a battery. WD 110 may also include a power circuit 137 for delivering power from power source 136 to various parts of WD 110 that require power from power source 136 to perform any functions described or indicated herein. In some embodiments, power circuit 137 may include a power management circuit.

[0171] Additionally or alternatively, the power circuit 137 may be operable to receive power from an external power source; in this case, the WD 110 may be connected to an external power source (e.g., a power outlet) via an input circuit or interface (e.g., a power cable). In some embodiments, the power circuit 137 may also be operable to deliver power from the external power source to the power source 136. For example, this may be used to charge the power source 136. The power circuit 137 may perform any formatting, conversion, or other modification of the power from the power source 136 to make the power suitable for the various components of the WD 110 being powered.

[0172] Although the subject matter described herein may be implemented in any suitable type of system using any suitable components, the embodiments disclosed herein are directed to wireless networks (e.g. Figure 4 For simplicity, Figure 4 The wireless network of FIG. 1 depicts only the network 106, the network nodes 160 and 160b, and the WDs 110, 110b, and 110c. In practice, the wireless network may also include any additional components suitable for supporting communication between wireless devices or between a wireless device and another communication device (e.g., a landline, a service provider, or any other network node or terminal device). In the components shown, the network node 160 and the wireless device (WD) 110 are depicted in more detail. The wireless network may provide communication and other types of services to one or more wireless devices to facilitate wireless devices to access and / or use services provided by or via the wireless network.

[0173] Figure 5 An example user device is shown in accordance with certain embodiments. As used herein, a user equipment or UE may not necessarily have a user in the sense of a human user owning and / or operating the associated device. Rather, a UE may represent a device that is intended to be sold to or operated by a human user, but which may not be, or may not initially be, associated with a particular human user (e.g., a smart sprinkler controller). Alternatively, a UE may represent a device that is not intended to be sold to or operated by an end user, but which may be associated with or operated for the benefit of a user (e.g., a smart meter). UE 200 may be any UE identified by the Third Generation Partnership Project (3GPP), including a NB-IoT UE, a Machine Type Communication (MTC) UE, and / or an enhanced MTC (eMTC) UE. As Figure 5 As shown, UE 200 is an example of a WD configured to communicate according to one or more communication standards promulgated by the Third Generation Partnership Project (3GPP), such as 3GPP's GSM, UMTS, LTE and / or 5G standards. As previously mentioned, the terms WD and UE may be used interchangeably. Therefore, although Figure 5 It is UE, but the components discussed in this article are also applicable to WD and vice versa.

[0174] exist Figure 5 In the embodiment, UE 200 includes a processing circuit 201, which is operatively coupled to an input / output interface 205, a radio frequency (RF) interface 209, a network connection interface 211, a memory 215 (including a random access memory (RAM) 217, a read-only memory (ROM) 219, and a storage medium 221, etc.), a communication subsystem 231, a power supply 213, and / or any other components, or any combination thereof. The storage medium 221 includes an operating system 223, an application 225, and data 227. In other embodiments, the storage medium 221 may include other similar types of information. Some UEs may use Figure 5 All components shown may be used, or only a subset of these components may be used. The degree of integration between components may vary from UE to UE. In addition, some UEs may contain multiple instances of a component, such as multiple processors, memories, transceivers, transmitters, receivers, etc.

[0175] exist Figure 5 , processing circuit 201 may be configured to process computer instructions and data. Processing circuit 201 may be configured to implement any sequential state machine operable to execute machine instructions stored in memory as a machine-readable computer program, such as one or more hardware-implemented state machines (e.g., in discrete logic, FPGA, ASIC, etc.); programmable logic with appropriate firmware; one or more stored-program, general-purpose processors (e.g., microprocessors or digital signal processors (DSPs)) with appropriate software; or any combination of the above. For example, processing circuit 201 may include two central processing units (CPUs). Data may be information in a form suitable for use by a computer.

[0176] In the depicted embodiment, the input / output interface 205 may be configured to provide a communication interface to an input device, an output device, or an input / output device. The UE 200 may be configured to use an output device via the input / output interface 205 .

[0177] The output device may use the same type of interface port as the input device. For example, a USB port may be used to provide input to the UE 200 and provide output from the UE 200. The output device may be a speaker, a sound card, a video card, a display, a monitor, a printer, an actuator, a transmitter, a smart card, another output device, or any combination thereof.

[0178] UE 200 can be configured to use input devices via input / output interface 205 to allow a user to capture information into UE 200. Input devices can include touch-sensitive or presence-sensitive displays, cameras (e.g., digital cameras, digital video cameras, webcams, etc.), microphones, sensors, mice, trackballs, directional keys, trackpads, scroll wheels, smart cards, etc. The presence-sensitive display can include a capacitive or resistive touch sensor to sense input from the user. The sensor can be, for example, an accelerometer, a gyroscope, a tilt sensor, a force sensor, a magnetometer, an optical sensor, a proximity sensor, other similar sensors, or any combination thereof. For example, the input device can be an accelerometer, a magnetometer, a digital camera, a microphone, and an optical sensor.

[0179] exist Figure 5 In the embodiment, the RF interface 209 can be configured to provide a communication interface to the RF components (e.g., transmitters, receivers, and antennas). The network connection interface 211 can be configured to provide a communication interface to the network 243a. The network 243a can include a wired and / or wireless network, such as a local area network (LAN), a wide area network (WAN), a computer network, a wireless network, a telecommunications network, other similar networks, or any combination thereof. For example, the network 243a can include a Wi-Fi network. The network connection interface 211 can be configured to include a receiver and a transmitter interface for communicating with one or more other devices through a communication network according to one or more communication protocols (e.g., Ethernet, TCP / IP, SONET, ATM, etc.). The network connection interface 211 can implement receiver and transmitter functions suitable for communication network links (e.g., optical, electrical, etc.). The transmitter and receiver functions can share circuit elements, software, or firmware, or can alternatively be implemented separately.

[0180] RAM 217 may be configured to connect to processing circuit 201 via bus 202 to provide storage or caching of data or computer instructions during execution of software programs (e.g., operating systems, application programs, and device drivers). ROM 219 may be configured to provide computer instructions or data to processing circuit 201. For example, ROM 219 may be configured to store unchanging low-level system code or data for basic system functions (e.g., basic input and output (I / O) stored in non-volatile memory, booting, or receiving keystrokes from a keyboard).

[0181] The storage medium 221 may be configured to include a memory, such as a RAM, a ROM, a programmable read-only memory (PROM), an erasable programmable read-only memory (EPROM), an electrically erasable programmable read-only memory (EEPROM), a disk, an optical disk, a floppy disk, a hard disk, a removable cartridge disk, or a flash drive. In one example, the storage medium 221 may be configured to include an operating system 223, an application 225 (such as a web browser application, a widget or gadget engine, or other application), and a data file 227. The storage medium 221 may store any one of a variety of operating systems or a combination of operating systems for use by the UE 200.

[0182] The storage medium 221 may be configured to include a plurality of physical drive units, such as a Redundant Array of Independent Disks (RAID), a floppy disk drive, a flash memory, a USB flash drive, an external hard disk drive, a thumb drive, a pen drive, a key drive, a High-Density Digital Versatile Disc (HD-DVD) optical drive, an internal hard disk drive, a Blu-ray optical drive, a Holographic Digital Data Storage (HDDS) optical drive, an external micro Dual In-Line Memory Module (DIMM), a Synchronous Dynamic Random Access Memory (SDRAM), an external micro DIMM SDRAM, a smart card memory (e.g., a Subscriber Identity Module or a Removable User Identity (SIM / RUIM) module), other memories, or any combination thereof. The storage medium 221 may allow the UE 200 to access computer executable instructions, applications, etc. stored on a temporary or non-temporary storage medium to offload data or upload data. An article of manufacture (eg, an article of manufacture utilizing a communication system) may be tangibly embodied in storage media 221, which may include device-readable media.

[0183] exist Figure 5In the embodiment, the processing circuit 201 can be configured to communicate with the network 243b using the communication subsystem 231. The network 243a and the network 243b can be the same network or multiple networks, or different one or more networks. The communication subsystem 231 can be configured to include one or more transceivers for communicating with the network 243b. For example, the communication subsystem 231 can be configured to include one or more transceivers for communicating with the network 243b according to one or more communication protocols (e.g., IEEE802.2, CDMA, WCDMA, GSM, LTE, UTRAN, WiMax, etc.) and one or more remote transceivers of another device capable of wireless communication (e.g., another WD, UE, or a base station of a radio access network (RAN)). Each transceiver can include a transmitter 233 and / or a receiver 235 to respectively implement a transmitter or receiver function suitable for a RAN link (e.g., frequency allocation, etc.). In addition, the transmitter 233 and the receiver 235 of each transceiver can share circuit components, software or firmware, or can alternatively be implemented separately.

[0184] In the illustrated embodiment, the communication functions of the communication subsystem 231 may include data communication, voice communication, multimedia communication, short-range communication (e.g., Bluetooth), near-field communication, location-based communication (e.g., using a global positioning system (GPS) to determine location), other similar communication functions, or any combination thereof. For example, the communication subsystem 231 may include cellular communication, Wi-Fi communication, Bluetooth communication, and GPS communication. The network 243b may include a wired and / or wireless network, such as a local area network (LAN), a wide area network (WAN), a computer network, a wireless network, a telecommunications network, other similar networks, or any combination thereof. For example, the network 243b may be a cellular network, a Wi-Fi network, and / or a near-field network. The power supply 213 may be configured to provide alternating current (AC) or direct current (DC) power to the components of the UE 200.

[0185] The features, advantages and / or functions described herein may be implemented in one of the components of UE 200, or may be divided among multiple components of UE 200. In addition, the features, advantages and / or functions described herein may be implemented by any combination of hardware, software or firmware. In one example, the communication subsystem 231 may be configured to include any component described herein. In addition, the processing circuit 201 may be configured to communicate with any such component via the bus 202. In another example, any such component may be represented by a program instruction stored in a memory, which, when executed by the processing circuit 201, performs the corresponding function described herein. In another example, the function of any such component may be divided between the processing circuit 201 and the communication subsystem 231. In another example, the non-computationally intensive functions of any such component may be implemented in software or firmware, while the computationally intensive functions may be implemented in hardware.

[0186] Fig. 6A is a flow chart illustrating an example method in a network node according to certain embodiments. In certain embodiments, Fig. 6A One or more steps may be performed by Figure 4 The network node 160 described performs.

[0187] The method begins at step 612, where a network node (e.g., network node 160) determines a reciprocity-assisted interference-aware transmission precoder based on a downlink wideband interference covariance matrix estimated from a plurality of received sounding reference signals and based on a matrix inversion associated with the downlink wideband interference covariance matrix. The matrix inversion is determined based on iterative inverse covariance estimation. The reciprocity-assisted interference-aware transmission precoder may be determined according to any of the embodiments and examples described herein.

[0188] For example, in certain embodiments, the matrix inversion associated with the downlink wideband interference covariance matrix includes the matrix inversion of a regularized version of the downlink wideband interference covariance matrix.

[0189] In certain embodiments, the iterative inverse covariance estimation includes iteratively updating the inverse of the wideband interference covariance matrix according to the plurality of channel estimation residual vectors using a series of rank-one updates, each rank-one update corresponding to a residual vector of the plurality of channel estimation residual vectors. The rank-one update may use a Woodbury matrix identity.

[0190] In a particular embodiment, iterative inverse covariance estimation includes adding a cyclic Gaussian noise vector to each of the plurality of channel estimate residual vectors.

[0191] In certain embodiments, iterative inverse covariance estimation includes approximating the instantaneous noise correlation expression by an expected value of the instantaneous noise correlation expression.

[0192] In some embodiments, iterative inverse covariance estimation can be combined with beam space reduction. For example, in certain embodiments, the determination of the reciprocity-assisted interference-aware transmission precoder is also based on beam space dimensionality reduction. The beam space dimensionality reduction can be applied to the downlink wideband inverse interference covariance matrix, to determine the downlink channel estimate of the reciprocity-assisted interference-aware transmission precoder, or both.

[0193] The network node transmits the downlink signal using the reciprocity-assisted interference-aware transmit precoder at step 614. For example, the network node may transmit the downlink signal to the wireless device 110 using the reciprocity-assisted interference-aware transmit precoder.

[0194] Can Fig. 6A The method 600 may be modified, added or omitted. In addition, Fig. 6A One or more steps in the method may be performed in parallel or in any suitable order.

[0195] Figure 6B is a flow chart illustrating another example method in a network node according to certain embodiments. In certain embodiments, Figure 6B One or more steps may be performed by Figure 4 The network node 160 described performs.

[0196] The method begins at step 652, where a network node (e.g., network node 160) determines a reciprocity-assisted interference-aware transmission precoder based on a downlink wideband interference covariance matrix estimated from a plurality of received sounding reference signals and based on a matrix inversion associated with the downlink wideband interference covariance matrix. The determination is based on beamspace dimensionality reduction. The reciprocity-assisted interference-aware transmission precoder may be determined according to any of the embodiments and examples described herein.

[0197] For example, in certain embodiments, beamspace dimensionality reduction is applied to a downlink wideband inverse interference covariance matrix, to a downlink channel estimate for determining a reciprocity-aided interference-aware transmit precoder, or both.

[0198] In certain embodiments, the beam space dimensionality reduction is based on spatial discrete Fourier transform basis vectors that are based on antenna array configurations of network nodes.

[0199] In certain embodiments, a set of active beams for beamspace dimensionality reduction is selected based on channel power and / or inverse interference covariance.

[0200] In certain embodiments, the set of active beams includes a fixed number of beams. The set of active beams may include a minimum number of active beams with a total collected power greater than or equal to a predetermined value and / or a plurality of beams with a power per beam above a threshold.

[0201] In some embodiments, beam space reduction may be combined with iterative inverse covariance estimation.For example, in certain embodiments, matrix inversion is determined based on iterative inverse covariance estimation.

[0202] The network node transmits the downlink signal using the reciprocity-assisted interference-aware transmit precoder at step 654. For example, the network node may transmit the downlink signal to the wireless device 110 using the reciprocity-assisted interference-aware transmit precoder.

[0203] Can Figure 6B Method 650 may be modified, added, or omitted. In addition, Figure 6B One or more steps in the method may be performed in parallel or in any suitable order.

[0204] Figure 7 A wireless network (eg, Figure 4 Schematic block diagram of two devices in a wireless network (shown in FIG. 1 ). The device includes a wireless device and a network node (e.g., Figure 4 1 and 1700 are operative to respectively perform the following steps: Fig. 6A and Figure 6B The example methods described herein may also be performed and any other processes or methods disclosed herein may be performed. It should also be understood that Fig. 6A and Figure 6B The methods are not necessarily performed only by the apparatus 1600 and / or 1700. At least some operations of these methods may be performed by one or more other entities.

[0205] Virtual devices 1600 and 1700 may include processing circuitry, which may include one or more microprocessors or microcontrollers, and other digital hardware, which may include a digital signal processor (DSP), dedicated digital logic, etc. The processing circuitry may be configured to execute program code stored in a memory, which may include one or more types of memory, such as a read-only memory (ROM), a random access memory, a cache memory, a flash memory device, an optical storage device, etc. In several embodiments, the program code stored in the memory includes program instructions for executing one or more telecommunication and / or data communication protocols, and instructions for executing one or more techniques described herein.

[0206] In some embodiments, the processing circuit may be used to enable the determination module 1604, the transmission module 1606, and any other suitable unit of the device 1600 to perform corresponding functions according to one or more embodiments of the present disclosure. Similarly, the processing circuit described above may be used to enable the determination module 1704, the transmission module 1706, and any other suitable unit of the device 1700 to perform corresponding functions according to one or more embodiments of the present disclosure.

[0207] like Figure 5 As shown, the apparatus 1600 includes a determination module 1604, which is configured to determine a reciprocity-assisted interference-aware transmission precoder according to any embodiment and example described herein. The transmission module 1606 is configured to transmit a signal using the reciprocity-assisted interference-aware transmission precoder according to any embodiment and example described herein.

[0208] like Figure 5 As shown, the apparatus 1700 includes a determination module 1704, which is configured to determine a reciprocity-assisted interference-aware transmission precoder according to any embodiment and example described herein. A transmission module 1706 is configured to transmit a signal using the reciprocity-assisted interference-aware transmission precoder according to any embodiment and example described herein.

[0209] The term "unit" may have the conventional meaning in the field of electronics, electrical equipment and / or electronic equipment, and may include, for example, electrical and / or electronic circuits, devices, modules, processors, memories, logical solid-state and / or discrete devices, computer programs or instructions for performing corresponding tasks, procedures, calculations, output and / or display functions, etc. (such as those described in this document).

[0210] Without departing from the scope of the present invention, the systems and devices disclosed herein may be modified, added, or omitted. The components of the systems and devices may be integrated or separated. In addition, the operations of the systems and devices may be performed by more, fewer, or other components. In addition, the operations of the systems and devices may be performed using any suitable logic (including software, hardware, and / or other logic). As used herein, "each" refers to each member of a set or each member of a subset of a set.

[0211] Without departing from the scope of the present invention, the methods disclosed herein may be modified, added or omitted. These methods may include more, less or other steps. In addition, the steps may be performed in any suitable order.

[0212] The foregoing description sets forth many specific details. However, it should be appreciated that embodiments may be practiced without these specific details. In other cases, well-known circuits, structures, and techniques are not shown in detail to avoid obscuring the understanding of this description. One of ordinary skill in the art will be able to implement appropriate functionality based on the included description without undue experimentation.

[0213] References in the specification to "one embodiment", "an embodiment", "example embodiment", etc. indicate that the embodiment described may include specific features, structures, or characteristics, but not every embodiment may include the specific features, structures, or characteristics. In addition, such phrases do not necessarily refer to the same embodiment. In addition, when specific features, structures, or characteristics are described in conjunction with an embodiment, it can be considered that it is within the knowledge of those skilled in the art to implement such features, structures, or characteristics in conjunction with other embodiments, whether or not explicitly described.

[0214] Although the present disclosure has been described according to certain embodiments, changes and substitutions of the embodiments will be clear to those skilled in the art. Therefore, the description of the above embodiments does not limit the present disclosure. Other changes, substitutions and modifications are possible without departing from the scope of the present disclosure defined by the following claims.

Claims

1. A method for interference-aware downlink transmission performed by a network node, the method comprising: determining (612) a reciprocity-assisted interference-aware transmit precoder based on a downlink wideband interference covariance matrix estimated from a plurality of received sounding reference signals and based on a matrix inversion associated with the downlink wideband interference covariance matrix, wherein the matrix inversion is determined based on iterative inverse covariance estimation; and A downlink signal is transmitted (614) using the reciprocity-assisted interference-aware transmit precoder.

2. The method according to claim 1, wherein: The matrix inversion associated with the downlink wideband interference covariance matrix includes a matrix inversion of a regularized version of the downlink wideband interference covariance matrix.

3. The method according to any one of claims 1 to 2, wherein: The iterative inverse covariance estimation includes iteratively updating the inverse of the wideband interference covariance matrix according to a plurality of channel estimation residual vectors using a series of rank-one updates, each rank-one update corresponding to a residual vector of the plurality of channel estimation residual vectors.

4. The method according to claim 3, wherein: The rank-one update uses the Woodbury matrix identity.

5. The method according to any one of claims 3 to 4, wherein: The iterative inverse covariance estimation includes adding a cyclic Gaussian noise vector to each of the plurality of channel estimation residual vectors.

6. The method according to any one of claims 1 to 5, wherein: The iterative inverse covariance estimation includes approximating the instantaneous noise correlation expression by an expected value of the instantaneous noise correlation expression.

7. The method according to any one of claims 1 to 6, wherein: The determination of the reciprocity-assisted interference-aware transmit precoder is also based on beamspace dimensionality reduction.

8. The method according to claim 7, wherein: Beamspace dimensionality reduction is applied to the downlink wideband inverse interference covariance matrix.

9. The method according to any one of claims 7 to 8, wherein: Beamspace dimensionality reduction is applied to determine a downlink channel estimate for the reciprocity-assisted interference-aware transmit precoder.

10. A network node (160) capable of interference-aware downlink transmission, the network node comprising a processing circuit (170), the processing circuit (170) being operable to: determining a reciprocity-assisted interference-aware transmit precoder based on a downlink wideband interference covariance matrix estimated from a plurality of received sounding reference signals and based on a matrix inversion associated with the downlink wideband interference covariance matrix, wherein the matrix inversion is determined based on iterative inverse covariance estimation; and A downlink signal is transmitted using the reciprocity-assisted interference-aware transmit precoder.

11. The network node according to claim 10, wherein: The matrix inversion associated with the downlink wideband interference covariance matrix includes a matrix inversion of a regularized version of the downlink wideband interference covariance matrix.

12. The network node according to any one of claims 10 to 11, wherein: The iterative inverse covariance estimation includes iteratively updating the inverse of the wideband interference covariance matrix according to a plurality of channel estimation residual vectors using a series of rank-one updates, each rank-one update corresponding to a residual vector of the plurality of channel estimation residual vectors.

13. The network node according to claim 12, wherein: The rank-one update uses the Woodbury matrix identity.

14. The network node according to any one of claims 12 to 13, wherein: The iterative inverse covariance estimation includes adding a cyclic Gaussian noise vector to each of the plurality of channel estimation residual vectors.

15. The network node according to any one of claims 10 to 14, wherein: The iterative inverse covariance estimation includes approximating the instantaneous noise correlation expression by an expected value of the instantaneous noise correlation expression.

16. The network node according to any one of claims 10 to 15, wherein: The determination of the reciprocity-assisted interference-aware transmit precoder is also based on beamspace dimensionality reduction.

17. The network node according to claim 16, wherein: Beamspace dimensionality reduction is applied to the downlink wideband inverse interference covariance matrix.

18. The network node according to any one of claims 16 to 17, wherein: Beamspace dimensionality reduction is applied to determine a downlink channel estimate for the reciprocity-assisted interference-aware transmit precoder.

19. A method performed by a network node, the method comprising: determining (652) a reciprocity-assisted interference-aware transmit precoder based on a downlink wideband interference covariance matrix estimated from a plurality of received sounding reference signals and based on a matrix inversion associated with the downlink wideband interference covariance matrix, wherein the determining is based on beamspace dimensionality reduction; and A downlink signal is transmitted (654) using the reciprocity-assisted interference-aware transmit precoder.

20. The method according to claim 19, wherein: Beamspace dimensionality reduction is applied to the downlink wideband inverse interference covariance matrix.

21. The method according to any one of claims 19 to 20, wherein: Beamspace dimensionality reduction is applied to determine a downlink channel estimate for the reciprocity-assisted interference-aware transmit precoder.

22. The method according to any one of claims 19 to 21, wherein: The beam space dimensionality reduction is based on spatial discrete Fourier transform basis vectors, which are based on antenna array configurations of the network nodes.

23. The method according to any one or more of claims 19 to 22, wherein: A set of active beams for the beamspace dimensionality reduction is selected based on channel power.

24. The method according to any one or more of claims 19 to 23, wherein: A set of active beams for beamspace dimensionality reduction is selected based on the inverse interference covariance.

25. The method according to any one of claims 23 to 24, wherein: The set of active beams includes a fixed number of beams.

26. The method according to any one of claims 23 to 24, wherein: The set of active beams includes a minimum number of active beams having a total collected power greater than or equal to a predetermined value.

27. The method according to any one of claims 23 to 24, wherein: The set of active beams includes a plurality of beams, each beam having a power above a threshold.

28. The method according to any one of claims 19 to 27, wherein: The matrix inversion is determined based on iterative inverse covariance estimation.

29. A network node (160) comprising a processing circuit (170) operable to: Determining a reciprocity-assisted interference-aware transmit precoder based on a downlink wideband interference covariance matrix estimated from a plurality of received sounding reference signals and based on a matrix inversion associated with the downlink wideband interference covariance matrix, wherein the determining is based on beamspace dimensionality reduction; and A downlink signal is transmitted using the reciprocity-assisted interference-aware transmit precoder.

30. The network node according to claim 29, wherein: Beamspace dimensionality reduction is applied to the downlink wideband inverse interference covariance matrix.

31. The network node according to any one of claims 29 to 30, wherein: Beamspace dimensionality reduction is applied to determine a downlink channel estimate for the reciprocity-assisted interference-aware transmit precoder.

32. A network node according to any one of claims 29 to 31, wherein: The beam space dimensionality reduction is based on spatial discrete Fourier transform basis vectors, which are based on antenna array configurations of the network nodes.

33. A network node according to any one or more of claims 29 to 32, wherein: A set of active beams for the beamspace dimensionality reduction is selected based on channel power.

34. A network node according to any one or more of claims 29 to 33, wherein: A set of active beams for the beam space dimensionality reduction is selected based on inverse interference covariance.

35. The network node according to any one of claims 33 to 34, wherein: The set of active beams includes a fixed number of beams.

36. The network node according to any one of claims 33 to 34, wherein: The set of active beams includes a minimum number of active beams having a total collected power greater than or equal to a predetermined value.

37. The network node according to any one of claims 33 to 34, wherein: The set of active beams includes a plurality of beams, each beam having a power above a threshold.

38. A network node according to any one of claims 29 to 37, wherein: The matrix inversion is determined based on iterative inverse covariance estimation.

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