Massive Multiple Input Multiple Output (mMIMO) Beam Shaping Estimation

Abstract

According to one example, a massive multiple-input multiple-output (mMIMO) system configured for beamforming control may include an open radio access network (O-RU) radio unit with a processing device configured to: compute one or more predictive channel estimates, beamforming estimates, or antenna calibrations; calculate, based on an objective function having one or more of the predictive channel estimate, beamforming estimate, or antenna calibration as inputs, a power level for a data stream connected to a transmit antenna path, selecting the power level for the data stream to facilitate equal power distribution over a plurality of transmit antenna paths; and set the power level for the data stream connected to the transmit antenna path.

Description

RELATED REGISTRATION

[0001] This application claims the benefits of US Provisional Application No. 63 / 487,257, filed on February 27, 2023, the disclosure of which is incorporated herein by reference in full.

[0002] The examples discussed in the present disclosure relate to the estimation and control for beam shaping. BACKGROUND

[0003] Unless otherwise stated herein, the content described herein is not prior art for the claims of the present application and is not recognized as prior art by its inclusion in this section.

[0004] Beamforming is a signal processing technique used for directed signal transmission. There are various types of beamforming, including analog, digital, and hybrid beamforming; two-dimensional beamforming; three-dimensional beamforming (as used in Multiple Input Multiple Output (MIMO)); and others. Beamforming can be used to achieve spatial selectivity in various wireless communication standards such as 5G and IEEE 802.11ac, and beyond.

[0005] The subject matter claimed in the present disclosure is not limited to examples that overcome any disadvantages or function only in environments such as those described above. Rather, this background is provided only to illustrate an exemplary technological domain in which some of the examples described in the present disclosure can be practiced. SUMMARY OF THE INVENTION

[0006] A massive multiple-input multiple-output (mMIMO) system configured for beamforming control may comprise an open radio access network (O-RU) radio unit with a processing device. The processing device may be configured to compute one or more predictive channel estimates, beamforming estimates, or antenna calibrations. The processing device may be configured to calculate a power level for a data stream connected to a transmit antenna path, based on an objective function that takes one or more of the predictive channel estimates, beamforming estimates, or antenna calibrations as inputs. The power level for the data stream may be chosen to provide a uniform power distribution over a plurality of transmit antenna paths.The processing device can be configured to adjust the power level for the data stream assigned to the transmitting antenna path.

[0007] An mMIMO system with an open radio access network (O-RU) unit may include a processing device configured to compute an initial predictive channel estimate. The processing device may be configured to compute an initial beamforming estimate using the initial predictive channel estimate. The processing device may be configured to compute an initial antenna calibration using a reciprocity measurement received from a reference signal. The processing device may be configured to output a common beamforming estimate based on an objective function that takes the initial predictive channel estimate, the initial beamforming estimate, and the initial antenna calibration as inputs.The processing device can be configured to send the common beam shaping estimate to a beam shaping controller for transmission.

[0008] The objects and advantages of the examples are realized and achieved at least through the elements, features and combinations that are particularly emphasized in the claims.

[0009] Both the preceding general description and the following detailed description are to be understood as examples and serve for clarification and are not limiting to the claimed invention. BRIEF DESCRIPTION OF THE DRAWINGS

[0010] The examples are described and explained in more detail using the attached drawings, in which: Fig. Figure 1 shows a block diagram of an exemplary communication system suitable for performing beamforming; Fig. Figure 2 shows a block diagram of another exemplary communication system suitable for performing beamforming; Fig. Figure 3 illustrates a block diagram of another exemplary communication system suitable for performing beamforming; Fig. Figure 4 shows a block diagram of an exemplary system suitable for performing beam shaping; Fig. Figure 5 illustrates the process of an exemplary beam shaping procedure; Fig. Figure 6 illustrates a process flow of another exemplary beam shaping method; and Fig. Figure 7 shows an example of a computer system that can be used for beam shaping, all of which are set up in accordance with some examples of the present disclosure. DESCRIPTION OF THE EXECUTION FORMS

[0011] Massive Multiple Input Multiple Output (mMIMO) technology uses multiple antennas to improve spectral efficiency, which can lead to increased network coverage, network capacity, and higher user device (UE) throughput. Multiple antennas can increase network coverage and capacity through beamforming, null forming, and spatial multiplexing. Beamforming can improve signal quality by focusing the gain. Spatial multiplexing can increase data throughput by using parallel data streams. Null forming can reduce interference by avoiding certain directions.

[0012] Massive MIMO (mMIMO) encompasses one or more mMIMO radios and features. An mMIMO implementation might employ multiple antenna techniques based on channel knowledge to improve network coverage, capacity, and throughput. Radio parameters (e.g., the number of RF chains, output power, bandwidth, and number of bands) and antenna element parameters (e.g., antenna size and structure) may play a role in mMIMO implementation.

[0013] The implementation of beamshaping in an mMIMO system can depend on several factors, which may differ depending on the beamshaping estimation, channel estimation, and antenna calibration. In a time-division duplex (TDD) network, antenna calibration may be performed using reciprocity, since the frequency bands for the uplink (UL) and downlink (DL) directions can use the same frequency range. Channel estimation may depend on the availability of a suitable reference signal, such as a channel state information reference signal (CSI-RS), a sounding reference signal (SRS), or similar. The (un)estimation of beamshaping may depend on the type of algorithm used for the estimation.

[0014] Balancing these factors can lead to performance results that do not account for other factors. For example, optimizing beamforming estimation, channel estimation, and antenna calibration without considering their interdependencies can reduce network coverage, capacity, and throughput relative to capacity. This means that discrete calculations for beamforming estimation, channel estimation, and antenna calibration may not provide efficient overall performance results (e.g., in terms of power). Therefore, disclosures addressing the interaction between beamforming estimation, channel estimation, and antenna calibration can offer improvements in overall system performance efficiency, which can further enhance network capacity, coverage, and throughput.

[0015] In some examples, an mMIMO system can be used for predictive channel estimation, beamforming estimation, or antenna calibration. The mMIMO system can include an open radio access network (O-RU) with a processing device. The processing device can be operated to compute one or more predictive channel estimates, an antenna calibration, or a beamforming estimation. The processing device can be operated to calculate a power level for a data stream connected to a transmit antenna path, based on an objective function that takes one or more of the predictive channel estimate, antenna calibration, or beamforming estimation as inputs. The power level for the data stream can be chosen to facilitate a uniform power distribution over a multitude of transmit antenna paths.The processing device can be operated to adjust the power level for the data stream assigned to the transmitting antenna path.

[0016] In some examples, an mMIMO beamshaping control system may be configured, comprising an O-RU with a processing device. The processing device may be operable to compute: (i) an initial predictive channel estimate, (ii) an initial beamshaping estimate using the predictive channel estimate, and (iii) an initial antenna calibration using a reciprocity measurement received from a reference signal. The processing device may be configured to output a joint beamshaping estimate based on an objective function that takes the initial predictive channel estimate, the initial beamshaping estimate, and the initial antenna calibration as inputs. The processing device may be configured to send the joint beamshaping estimate to a beamshaping control unit for transmission.

[0017] In some examples, such as in Fig. As shown in Figure 1, a base station (BS) can be operated in an open radio access network (O-RAN). The BS can comprise one massive multiple-input multiple-output (mMIMO) O-RAN radio unit (O-RU) 100 and one mMIMO O-RAN distributed unit (O-DU) 120. The mMIMO O-RU 100 can contain one or more logic blocks, including: Channel Estimator 102, Beamforming 104 with Downlink / Uplink (DL / UL) Beamforming 106 and Beamforming Weight Estimator 108, LowPHY 110, Digital Front End (DFE) 112, Digital Pre-distortion Component (DPD) 114, Transmit / Receive (TRx) 116, Radio Frequency Front End (RFFE) 118, or similar. The O-RU 100 can be operated in such a way that it can be connected to the O-DU 120.

[0018] In some examples, a predictive channel estimate can be calculated in the Channel Estimation block 102 and a beamforming estimate in the Beamforming block 104. The predictive channel estimate and the beamforming estimate 104 can be used as inputs for an objective function, which may be constrained by a power constraint. The power constraint can enable a substantially equal power distribution over a multitude of transmission paths. The power distribution over the multitude of transmission paths can be substantially equal if the power variance for the transmission paths is below a selected threshold. The selected threshold can be below one or more of the following values: 10%, 5%, 4%, 3%, 1%, etc.

[0019] In some examples, a power constraint can be used to control the power level by maximizing one or more signal ratios (e.g., signal-to-noise ratio (SNR), signal-to-noise-plus-noise ratio (SINR), or a combination thereof) for an i th UE and a j th Adjust the layer using the objective function: maximize∑i≤klog(SINRi+1) subject to the following conditions: DiHi∑Wj=I ∀i≤k |∑ei'Wj|2≤1n∀i≤n where W is the precoding matrix, D is the decoding matrix, H is the channel, I is the identity matrix, W is the decoding matrix, e k Let be a unit row basis vector and n be the number of transmitting antenna paths. That is, the third term may be adapted for the power constraint. In an example, a solution can be computed using local maxima found by gradient descent.

[0020] In some examples, the objective function, dependent on the power constraint, can be used to calculate power levels for data streams connected to the transmit antenna paths. In one example, a processing device can be operated to set a power level for data streams connected to the transmit antenna paths. In another example, the power levels can be calculated using an iterative operation. Using iterative operations can increase the speed of the calculation and reduce its complexity. In one example, iteration can reduce the computation time by more than one of the following: 10%, 20%, 30%, 40%, 50%, 60%, 70%, or 80% compared to the computation time when no iteration is used.

[0021] In some examples, predictive channel estimation can be calculated using data compression to reduce the data bandwidth and signal processing time below a specified threshold. In one example, data compression might reduce the data bandwidth by more than one or more of the following: 10%, 20%, 30%, 40%, 50%, 60%, 70%, or 80% compared to the data bandwidth without compression. Similarly, data compression might reduce the signal processing time by more than one or more of the following: 10%, 20%, 30%, 40%, 50%, 60%, 70%, 80%, or 90% compared to the signal processing time without compression.

[0022] In some examples, the processing device may be configured to compute the beam shaping estimate based on the predictive channel estimate. In some examples, the predictive channel estimate may be compressed before calculating the beam shaping estimate to reduce the computation time for the beam shaping estimate. In one example, the compression may reduce the computation time for the beam shaping estimate by more than one or more of the following: 10%, 20%, 30%, 40%, 50%, 60%, 70%, or 80%, or 90%, compared to the computation time for the beam shaping estimate when no data compression is used.

[0023] In some examples, the transmit antenna path may include one or more of the following: a LowPHY layer 110, a DFE 112, a DFE DPD 114, a TRx 116, or an RFFE 118. The transmit antenna path may also include a power amplifier (not shown). In some examples, the transmit antenna path may have a power efficiency greater than a selected power efficiency threshold. In some examples, the majority of transmit antenna paths may have an overall power efficiency greater than an overall power efficiency threshold.

[0024] In some examples, the mMIMO system can include a distributed open radio access network (O-DU) unit that can be split by the O-RU based on an O-RU 6-split or an O-RU 7-split. In some examples, the mMIMO system can include a distributed open radio access network (O-DU) unit that can be split by the O-RU based on an O-RU 7.2-split, as in Fig. Figure 1 shows that in some examples, the mMIMO system may include a distributed Open Radio Access Network (O-DU) unit that can be split by the O-RU based on an O-RU 7.2C split, as shown in Figure 1. Fig. 2 and Fig. 3 shown.

[0025] In some examples, such as in Fig. As shown in Figure 2, a BS can be operated in an O-RAN. The BS can comprise an O-RU 200 and an O-DU 222. The mMIMO O-RU 200 can contain one or more modules, including: Beamforming Estimator 202, Channel Estimator 204, Antenna / Reciprocity Calibration 206, O-RAN Fronthaul 7.2C 208, IQ Decomposition 210, Beamforming Drive 212 (BF Drive), lowPHY 214, DFE 216, TRx 218, RFFE 220, or similar. The O-RU 200 can be operated in conjunction with the O-DU 222 (e.g., as shown in Figure 2). Fig. 3 described, O-DU 322) can be connected.

[0026] In some examples, the mMIMO system may include an O-RU 200, which may contain a processing device. The processing device may be used for a beamforming estimator 202, a channel estimator 204, and an antenna / reciprocity calibration 206. The channel estimator 204 may be operated to calculate an initial predictive channel estimate. The beamforming estimator 202 may be used to calculate an initial beamforming estimate using the initial predictive channel estimate. The antenna / reciprocity calibration 206 may be operated to calculate an initial antenna calibration using a reciprocity measurement received from a reference signal.The beamforming estimator 202 can be operated to output a joint beamforming estimate based on an objective function that takes the initial predictive channel estimate, the initial beamforming estimate, and the initial antenna calibration as inputs. The joint beamforming estimate can be sent to the beamforming controller 212 for further processing and subsequent transmission.

[0027] In some examples, the processing device can be operated to subject the objective function to a performance constraint, as elsewhere disclosed herein. In one example, the processing device can be operated to compute the joint beamforming estimate using one iteration to reduce computation time, as elsewhere disclosed herein. In another example, the processing device can be operated to compress the initial predictive channel estimate before computing the initial beamforming estimate, as elsewhere disclosed herein.

[0028] In some examples, the processing device may be configured to compute an antenna / reciprocity calibration 206. In one example, the antenna / reciprocity calibration 206 may be computed using a reciprocity measurement received from a reference signal. The reference signal may be any suitable reference signal, including one or more of the following: a CSI-RS, an SRS, a demodulation reference signal (DM-RS), a phase-tracking reference signal (PTRS), or similar. In some examples, the antenna / reciprocity calibration 206 may be used as input for the objective function and the performance constraints.

[0029] In some examples, such as in Fig. As shown in Figure 3, a BS can be operated in an O-RAN. The BS can comprise an O-RU 300 and an O-DU 322. The mMIMO O-DU 322 can contain one or more modules, including: Scrambling 324, Modulation 326, Layer Mapping 328, Resource Element (RE) Mapping 330, IQ Compression 332, O-RAN Fronthaul (FH) 7.2C 334, Scheduler 336, or similar. The O-DU 322 can serve as an interface to the O-RU 300 (e.g., as shown in Figure 3). Fig. 2, O-RU 200 described).

[0030] Fig. Figure 4 shows a block diagram of an exemplary communication system 400 that can be operated for beamforming estimation and triggering in accordance with at least one example described in the present disclosure. The communication system 400 can comprise a digital transmitter 402, a radio frequency circuit 404, a device 410, a digital receiver 406, and a processing device 408. The digital receiver 406 and the processing device can be configured to receive a baseband signal via the link 410. A transceiver 416 can include the digital transmitter 402 and the radio frequency circuit 404.

[0031] In some examples, the Communication System 400 may comprise a system of devices capable of communicating with each other via a wired connection. A wired connection in the Communication System 400 may, for example, include one or more Ethernet cables, one or more fiber optic cables, and / or other similar wired communication media. Alternatively or additionally, the Communication System 400 may comprise a system of devices capable of communicating via one or more wireless connections. For example, the Communication System 400 may comprise one or more devices configured to transmit and / or receive radio waves, microwaves, ultrasonic waves, optical waves, electromagnetic induction, and / or similar wireless communication. Alternatively or additionally, the Communication System 400 may also comprise combinations of wireless and / or wired connections.In these and other examples, the Communication System 400 can include one or more devices that can be operated to receive a baseband signal, perform one or more operations on the baseband signal to generate a modified baseband signal, and transmit the modified baseband signal, e.g., to one or more loads.

[0032] In some examples, the communication system 400 may contain one or more communication channels that can communicatively couple systems and / or devices included in the communication system 400. For example, the transceiver 416 may be communicatively coupled with the device 410.

[0033] In some examples, the transceiver 416 can be operated to receive a baseband signal. As described herein, the transceiver 416 can, for example, generate a baseband signal and / or receive a baseband signal from another device. In some examples, the transceiver 416 can be configured to transmit the baseband signal. For example, after receiving the baseband signal, the transceiver 416 can be operated to transmit the baseband signal to a separate device, such as the device 410. Alternatively or additionally, the transceiver 416 can be operated to modify, condition, and / or transform the baseband signal before transmitting it. For example, the transceiver 416 can include a quadrature boost converter and / or a digital-to-analog converter (DAC) that can modify the baseband signal.Alternatively or additionally, the 416 transceiver can include a direct radio frequency sampling converter that can modify the baseband signal.

[0034] In some examples, the digital transmitter 402 can be operated to receive a baseband signal via connection 410. In some examples, the digital transmitter 402 can be operated to upconvert the baseband signal. For example, the digital transmitter 402 can include a quadrature upconverter applied to the baseband signal. In some examples, the digital transmitter 402 can include an integrated digital-to-analog converter (DAC). The DAC can convert the baseband signal into an analog signal or a continuous-time signal. In some examples, the DAC architecture can include a direct RF sampling DAC. In some examples, the DAC can be a separate element from the digital transmitter 402.

[0035] In some examples, the Transceiver 416 may include one or more subcomponents that can be used in preparing and / or transmitting the baseband signal. For example, the Transceiver 416 may include an RF front end (e.g., in a wireless environment) that may include a power amplifier (PA), a digital transmitter (e.g., 402), a digital front end, an IEEE 1588v2 (Institute of Electrical and Electronics Engineers) device, an LTE physical layer (L-PHY), an S-plane device, an M-plane (management plane) device, an Ethernet media access control (MAC) / personal communications service (PCS), a resource controller / scheduler, and the like. In some examples, a radio device (e.g., a radio frequency circuit 404) of the transceiver 416 can be synchronized with the resource controller via the S-plane device, which can contribute to highly accurate timing with respect to a reference clock.

[0036] In some examples, the Transceiver 416 can be operated to receive the baseband signal for transmission. For example, the Transceiver 416 can receive the baseband signal from a separate device, such as a signal generator. The baseband signal might originate from a converter that transforms a variable into an electrical signal, such as an audio signal output by a microphone picking up a speaker's voice. Alternatively or additionally, the Transceiver 416 can generate a baseband signal for transmission. In these and other examples, the Transceiver 416 can be operated to transmit the baseband signal to another device, such as the Device 410.

[0037] In some examples, the device 410 can be operated to receive a transmission from the transceiver 416. For example, the transceiver 416 can be operated to send a baseband signal to the device 410.

[0038] In some examples, the radio frequency circuit 404 can be operated to transmit the digital signal received from the digital transmitter 402. In some examples, the radio frequency circuit 404 can be operated to transmit the digital signal to the device 410 and / or the digital receiver 406. In some examples, the digital receiver 418 can be operated to receive a digital signal from the RF circuit and / or to transmit a digital signal to the processing device 408.

[0039] In some examples, the processing device 408, as shown, can be a standalone device or system. Alternatively or additionally, the processing device 408 can be a component of another device and / or system. In some examples, for instance, the processing device 408 can be integrated into the transceiver 416. In cases where the processing device 408 is a standalone device or system, it can be operated to communicate with additional devices and / or systems located remotely from the processing device 408, such as the transceiver 416 and / or the device 410. For example, the processing device 408 can be operated to send and / or receive transmissions from the transceiver 416 and / or the device 410.In some examples, the processing device 408 can be combined with other elements of the communication system 400.

[0040] Fig. Figure 5 illustrates a process flow of an exemplary method 500 for beam shaping control according to at least one example described in the present disclosure. The method 500 can be carried out in accordance with at least one example described in the present disclosure.

[0041] The method 500 can be performed by a processing logic that may include hardware (circuits, dedicated logic, etc.), software (such as that executed on a computer system or a dedicated computer), or a combination of both, the processing logic being located in the processing device 408. Fig. 4, the communication device 700 of Fig. 7 or any other device, combination of devices or systems.

[0042] Procedure 500 can begin in block 505, where the processing logic can compute one or more predictive channel estimates, a beamforming estimate, or an antenna calibration.

[0043] In Block 510, the processing logic can, based on an objective function that has one or more of the predictive channel estimation, beamforming estimation, or antenna calibration as inputs, compute a power level for a data stream connected to a transmit antenna path, selecting the power level for the data stream to facilitate a DC power distribution over a plurality of transmit antenna paths.

[0044] In block 515, the processing logic can set the power level for the data stream connected to the transmit antenna path.

[0045] Method 500 may be modified, supplemented, or omitted without exceeding the scope of this disclosure. For example, in some examples, Method 500 may include any number of other components that may not be explicitly shown or described.

[0046] Fig. Figure 6 illustrates the execution of an exemplary method 600 of the functionality for a massive multiple-input multiple-output (mMIMO) system comprising an open radio access network (O-RU) radio unit, in accordance with at least one example described in the present disclosure. Method 600 can be carried out in accordance with at least one example described in the present disclosure.

[0047] The method 600 can be performed by a processing logic that may include hardware (circuits, dedicated logic, etc.), software (such as that executed on a computer system or dedicated machine), or a combination of both, the processing logic being located in the processing device 408. Fig. 4, the communication device 700 of Fig. 7 or any other device, combination of devices or systems.

[0048] Procedure 600 can begin in block 605, where the processing logic can compute an initial predictive channel estimate.

[0049] In block 610, the processing logic can compute an initial beamforming estimate using the initial predictive channel estimate.

[0050] In block 615, the processing logic can calculate an initial antenna calibration using a reciprocity measurement received from a reference signal.

[0051] In block 620, the processing logic can output a common beamforming estimate based on an objective function that takes the initial predictive channel estimate, the initial beamforming estimate, and the initial antenna calibration as inputs.

[0052] In block 625, the processing logic can send the common beamforming estimate to a beamforming controller for transmission.

[0053] Method 600 may be modified, supplemented, or omitted without exceeding the scope of this disclosure. In some examples, for instance, Method 600 may include any number of other components that are not explicitly shown or described.

[0054] For the sake of simplicity, the methods and / or processes described herein are presented and described as a series of actions. However, the actions according to this disclosure can be performed in different sequences and / or simultaneously, as well as in conjunction with other actions not presented or described here. Furthermore, not all of the actions presented may be used to carry out the methods according to the disclosed subject matter. In addition, the person skilled in the art will understand and recognize that the methods can alternatively be represented as a series of interconnected states via a state diagram or events. Moreover, the methods disclosed in this description can be stored on a manufacturing item, such as a non-transient computer-readable medium, to facilitate the transport and transfer of such methods to computer equipment.The term "product" as used here refers to a computer program accessible from any computer-readable device or storage medium. Although represented as discrete blocks, various blocks may be subdivided into additional blocks, combined into fewer blocks, or eliminated, depending on the desired implementation.

[0055] Fig.Figure 7 shows a schematic representation of a computer in the exemplary form of Computer Device 700, in which a set of instructions can be executed to cause the computer to perform one or more of the procedures discussed herein. Computer Device 700 can be a rackmount server, a router computer, a server computer, a mainframe, a laptop computer, a tablet computer, a desktop computer, or any computer with at least one processor, etc., in which a set of instructions can be executed that causes the computer to perform one or more of the procedures described herein. In alternative examples, the machine can be connected (e.g., networked) to other machines in a local area network (LAN), an intranet, an extranet, or the Internet. The computer can operate in the function of a server in a client-server network environment.Even if only a single computer is depicted, the term "computer" can also encompass any collection of computers that, individually or collectively, execute a set (or multiple sets) of instructions to perform one or more of the procedures discussed herein.

[0056] The exemplary computer device 700 comprises a processing device (e.g. a processor) 702, a main memory 704 (e.g. read-only memory (ROM), flash memory, dynamic random access memory (DRAM) such as synchronous DRAM (SDRAM)), a static memory 706 (e.g. flash memory, static random access memory (SRAM)) and a data storage device 716, which communicate with each other via a bus 708.

[0057] The processing device 702 is one or more general-purpose processing devices such as a microprocessor, a central processing unit, or the like. Specifically, the processing device 702 may include a CISC (Complex Instruction Set Computing) microprocessor, a RISC (Reduced Instruction Set Computing) microprocessor, a VLIW (Very Long Instruction Word) microprocessor, or a processor implementing other instruction sets, or processors implementing a combination of instruction sets. The processing device 702 may also include one or more specialized processing devices, such as an application-specific integrated circuit (ASIC), a field-programmable gate array (FPGA), a digital signal processor (DSP), a network processor, or the like. The processing device 702 is configured to execute instructions 726 to perform the operations and steps discussed herein.

[0058] The computer device 700 may further include a network interface device 722 that can communicate with a network 718. The computer device 700 may also include a display device 710 (e.g., a liquid crystal display (LCD) or a cathode ray tube (CRT)), an alphanumeric input device 712 (e.g., a keyboard), a cursor control device 714 (e.g., a mouse), and a signal generation device 720 (e.g., a loudspeaker). In at least one example, the display device 710, the alphanumeric input device 712, and the cursor control device 714 may be combined into a single component or device (e.g., an LCD touchscreen).

[0059] The data storage device 716 may contain a computer-readable storage medium 724 on which one or more sets of instructions 726 are stored, embodying one or more of the procedures or functions described herein. The instructions 726 may also reside wholly or at least partially in the main memory 704 and / or in the processing device 702 while being executed by the computer device 700, the main memory 704 and the processing device 702 also being computer-readable media. The instructions may furthermore be transmitted or received over a network 718 via the network interface device 722.

[0060] While the computer-readable storage medium 724 is represented in an example as a single medium, the term "computer-readable storage medium" can encompass a single medium or multiple media (e.g., a centralized or distributed database and / or associated caches and servers) that store one or more sets of instructions. The term "computer-readable storage medium" can also encompass any medium configured to store, encode, or carry a set of instructions for execution by the computer, and which causes the computer to perform one or more of the methods disclosed herein. Accordingly, the term "computer-readable storage medium" can be understood to include, but is not limited to, solid-state storage, optical media, and magnetic media.

[0061] Some sections of the detailed description refer to different modules that can be used to perform operations. One or more of the modules may contain code and routines that enable a computer system to perform one or more of the operations described therein. Additionally or alternatively, one or more of the modules may be implemented using hardware, including any number of processors, microprocessors (e.g., to perform or control one or more operations), DSPs, FPGAs, ASICs, or a suitable combination of two or more of these. Alternatively or additionally, one or more of the modules may be implemented using a combination of hardware and software.In this disclosure, operations described as being performed by a particular module may also include operations that the particular module prescribes to a corresponding system (e.g., a corresponding computer system) for execution. The distinction between the various modules is intended to facilitate the explanation of the concepts described in this disclosure and is not restrictive. Furthermore, one or more of the modules may be operated in such a way as to perform more, fewer, and / or different operations than those described, so that the modules may be combined or delimited differently than described.

[0062] Some parts of the detailed description are presented in the form of algorithms and symbolic representations of operations within a computer. These algorithmic descriptions and symbolic representations are used by data processing professionals to communicate the essence of their innovations to other professionals. An algorithm is a series of executable operations that lead to a desired final state or result. In exemplary implementations, the operations performed require physical manipulations of tangible quantities to achieve a tangible result.

[0063] Unless expressly stated otherwise, as is evident from the discussion, it is understood that throughout the description discussions using terms such as detecting, determining, analyzing, identifying, scanning, or similar may include the actions and processes of a computer system or other information processing device that manipulate and convert data represented as physical (electronic) quantities in the registers and memories of the computer system into other data represented in a similar manner as physical quantities in the memories or registers of the computer system or in other devices for storing, transmitting, or displaying information.

[0064] Exemplary implementations may also refer to a device for performing the operations described herein. This device may be specifically designed for the required purposes or may comprise one or more general-purpose computers that are selectively activated or retrained by one or more computer programs. Such computer programs may be stored on a computer-readable medium, such as a computer-readable storage medium or a computer-readable signaling medium. Computer-executable instructions may, for example, contain instructions and data that cause a general-purpose computer, a special-purpose computer, or a special-purpose processing device (such as one or more processors) to perform or control the execution of a particular function or group of functions.

[0065] Although the subject matter was described in language specific to structural features and / or methodological actions, it should be understood that the subject matter developed in the attached claims is not necessarily limited to the specific features or actions described above. Rather, the specific features and actions described above are disclosed as exemplary forms of implementation of the claims.

[0066] Provided that the specific arrangements described herein are not mutually exclusive, the various implementations described herein can be combined in whole or in part to improve system functionality and / or to generate complementary functions. Likewise, aspects of the implementations can be implemented in independent arrangements. The above description is therefore only exemplary and can be modified in detail within the scope of the present invention.

[0067] Regarding the use of terms in the plural or singular, a person skilled in the art may translate from the plural to the singular or vice versa, depending on the context or application. The various singular / plural permutations are explicitly stated here for clarity. A reference to an element in the singular should not mean "one and only one," unless explicitly stated, but rather "one or more." Furthermore, nothing disclosed herein is intended to be made available to the public, regardless of whether such disclosure is explicitly mentioned in the description above.

[0068] In general, the terms used here, and in particular in the appended claims (e.g., in the parts of the appended claims), are to be understood as "open" terms (e.g., the term "including" should be interpreted as "including but not limited to", the term "with" as "with at least", the term "comprises" as "comprises but not limited to", etc.). Furthermore, in cases where a convention is used analogously to "at least one of A, B, and C, etc.", such a construction is generally meant in the sense in which a person skilled in the art would understand the convention (e.g., "a system with at least one of A, B, and C" would include, but is not limited to, systems comprising A alone, B alone, C alone, A and B together, A and C together, B and C together, or A, B, and C together, etc.).A sentence containing two or more alternative terms in the description, claims, or drawings is to be understood as including exactly one of the terms, only one of the two terms, or both terms. For example, the phrase "A or B" includes the possibilities "A" or "B" or "A and B".

[0069] Furthermore, the terms "first," "second," "third," etc., are not necessarily used here to denote a specific order or number of elements. Generally, the terms "first," "second," "third," etc., are used as generic terms to distinguish between different elements. Unless it is proven that the terms "first," "second," "third," etc., denote a specific order, these terms should not be understood as denoting a specific order. Similarly, unless it is proven that the terms "first," "second," "third," etc., denote a specific number of elements, these terms should also not be understood as denoting a specific number of elements.

[0070] The present invention can be embodied in other specific forms without departing from its spirit or essential features. The described embodiments are in every respect for illustrative purposes only and are not to be considered limiting. The scope of the invention is therefore defined more by the appended claims than by the foregoing description. All modifications that fall within the scope and equivalence of the claims are to be included within their scope. QUOTES INCLUDED IN THE DESCRIPTION

[0000] This list of documents cited by the applicant was automatically generated and is included solely for the reader's convenience. The list is not part of the German patent or utility model application. The DPMA accepts no liability for any errors or omissions. Cited patent literature

[0000] US 63 / 487,257

[0001]

Claims

[1] A Massive MIMO system (mMIMO system) (MIMO = Multiple Input Multiple Output) configured for beamforming control, comprising an open radio access network radio unit (O-RU) with a processing device configured to: Calculating one or more of a predictive channel estimate, a beamforming estimate, or an antenna calibration; Calculate, based on an objective function with one or more of the predictive channel estimation, the beamforming estimation, or the antenna calibration as inputs, a power level for a data stream associated with a transmit antenna path, wherein the power level for the data stream is selected to facilitate a DC power distribution over a plurality of transmit antenna paths; and Setting the power level for the data stream assigned to the transmit antenna path. [2] The mMIMO system according to claim 1, wherein the processing device is further configured to calculate the power level using one iteration. [3] The mMIMO system according to claim 1, wherein the predictive channel estimation is calculated using data compression to reduce a data bandwidth below a data bandwidth threshold and to reduce a signal processing time below a signal processing time threshold. [4] The mMIMO system according to claim 1, wherein the processing device is further configured to calculate the antenna calibration, wherein the antenna calibration is calculated using a reciprocity measurement received from a reference signal. [5] The mMIMO system according to claim 4, wherein the reference signal is a sounding reference signal (SRS). [6] The mMIMO system according to claim 1, wherein the processing device is further configured to calculate the predictive channel estimation and the beam shaping estimation, wherein the beam shaping estimation is based on the predictive channel estimation and the predictive channel estimation is compressed before calculating the beam shaping estimation. [7] The mMIMO system according to claim 1, wherein the transmit antenna path comprises one or more of the following elements: a LowPHY layer, a digital front end (DFE; English digital front end), a digital pre-distortion component (DPD component; English: digital pre-distortion component) a transmitting antenna, a radio frequency front end (RFFE), or a power amplifier (PA). [8] The mMIMO system according to claim 1, wherein the transmit antenna path has a power efficiency greater than a power efficiency threshold. [9] The mMIMO system according to claim 1, wherein the plurality of transmitting antenna paths have an overall power efficiency that is greater than a threshold for overall power efficiency. [10] The mMIMO system according to claim 1, wherein the mMIMO system comprises a distributed unit of the open radio access network (O-DU) which is split by the O-RU based on an O-RU 6-split or an O-RU 7-split. [11] The mMIMO system according to claim 1, wherein the mMIMO system comprises a distributed Open Radio Access Network (O-DU) unit that is separated from the O-RU based on an O-RAN 7.2 split. [12] The mMIMO system according to claim 11, wherein the O-RAN 7.2 split is an O-RAN 7.2C split. [13] A Massive MIMO system (mMIMO system) (MIMO = Multiple Input Multiple Output) comprising an open radio access network radio unit (O-RU) comprising a processing device configured to: Calculating an initial predictive channel estimate; Calculating an initial beamforming estimate using the initial predictive channel estimate; Calculating an initial antenna calibration using a reciprocity measurement received from a reference signal; Output a joint beamforming estimate based on an objective function with the initial predictive channel estimate, the initial beamforming estimate, and the initial antenna calibration as inputs; and Sending the joint beam shaping estimate to a beam shaping controller for transmission. [14] The mMIMO system according to claim 13, wherein the processing device is further configured such that the objective function depends on a performance constraint. [15] The mMIMO system according to claim 13, wherein the processing device is further configured to calculate the joint beam shaping estimate using one iteration. [16] The mMIMO system according to claim 13, wherein the processing device is further configured to compress the initial predictive channel estimate before the initial beam shaping estimate is calculated. [17] The mMIMO system according to claim 13, wherein the reference signal is a sounding reference signal (SRS). [18] The mMIMO system according to claim 13, wherein the mMIMO system comprises a distributed unit of the open radio access network (O-DU) which is divided by the O-RU on the basis of an O-RU 6 split or an O-RU 7 split. [19] The mMIMO system according to claim 13, wherein the mMIMO system comprises a distributed Open Radio Access Network (O-DU) unit that is separated from the O-RU on the basis of an O-RAN 7.2 split. [20] The mMIMO system according to claim 19, wherein the O-RAN 7.2 split is an O-RAN 7.2C split.

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