Method and apparatus for beamforming for uplink reception in a wireless communication system

Abstract

The present disclosure generally relates to wireless communication systems, more particularly, to methods and apparatus for beamforming for receiving data in uplink. The method comprises: receiving configuration data for CSI; determining at least one channel matrix, based on measurements on CSI-RSs; calculating a quality metric for each DFT vector, based on the determined at least one channel matrix; selecting a subset of DFT vectors by using a threshold quantization parameter, based on the calculated quality metrics; and transmitting CSI including at least information about the subset of DFT vectors, wherein a beamforming (BF) matrix for uplink (UL) reception is generated based on the CSI.

Description

METHOD AND APPARATUS FOR BEAMFORMING FOR UPLINK RECEPTION IN A WIRELESS COMMUNICATION SYSTEM

[0001] The present disclosure generally relates to wireless communication systems, more particularly, to methods and apparatus for beamforming for receiving data in uplink.

[0002] Considering the development of wireless communication from generation to generation, the technologies have been developed mainly for services targeting humans, such as voice calls, multimedia services, and data services. Following the commercialization of 5G (5th generation) communication systems, it is expected that the number of connected devices will exponentially grow. Increasingly, these will be connected to communication networks. Examples of connected things may include vehicles, robots, drones, home appliances, displays, smart sensors connected to various infrastructures, construction machines, and factory equipment. Mobile devices are expected to evolve in various form-factors, such as augmented reality glasses, virtual reality headsets, and hologram devices. In order to provide various services by connecting hundreds of billions of devices and things in the 6G (6th generation) era, there have been ongoing efforts to develop improved 6G communication systems. For these reasons, 6G communication systems are referred to as beyond-5G systems.

[0003] 6G communication systems, which are expected to be commercialized around 2030, will have a peak data rate of tera (1,000 giga)-level bit per second (bps) and a radio latency less than 100μsec, and thus will be 50 times as fast as 5G communication systems and have the 1 / 10 radio latency thereof.

[0004] In order to accomplish such a high data rate and an ultra-low latency, it has been considered to implement 6G communication systems in a terahertz (THz) band (for example, 95 gigahertz (GHz) to 3THz bands). It is expected that, due to severer path loss and atmospheric absorption in the terahertz bands than those in mmWave bands introduced in 5G, technologies capable of securing the signal transmission distance (that is, coverage) will become more crucial. It is necessary to develop, as major technologies for securing the coverage, Radio Frequency (RF) elements, antennas, novel waveforms having a better coverage than Orthogonal Frequency Division Multiplexing (OFDM), beamforming and massive Multiple-input Multiple-Output (MIMO), Full Dimensional MIMO (FD-MIMO), array antennas, and multiantenna transmission technologies such as large-scale antennas. In addition, there has been ongoing discussion on new technologies for improving the coverage of terahertz-band signals, such as metamaterial-based lenses and antennas, Orbital Angular Momentum (OAM), and Reconfigurable Intelligent Surface (RIS).

[0005] Moreover, in order to improve the spectral efficiency and the overall network performances, the following technologies have been developed for 6G communication systems: a full-duplex technology for enabling an uplink transmission and a downlink transmission to simultaneously use the same frequency resource at the same time; a network technology for utilizing satellites, High-Altitude Platform Stations (HAPS), and the like in an integrated manner; an improved network structure for supporting mobile base stations and the like and enabling network operation optimization and automation and the like; a dynamic spectrum sharing technology via collision avoidance based on a prediction of spectrum usage; an use of Artificial Intelligence (AI) in wireless communication for improvement of overall network operation by utilizing AI from a designing phase for developing 6G and internalizing end-to-end AI support functions; and a next-generation distributed computing technology for overcoming the limit of UE computing ability through reachable super-high-performance communication and computing resources (such as Mobile Edge Computing (MEC), clouds, and the like) over the network. In addition, through designing new protocols to be used in 6G communication systems, developing mechanisms for implementing a hardware-based security environment and safe use of data, and developing technologies for maintaining privacy, attempts to strengthen the connectivity between devices, optimize the network, promote softwarization of network entities, and increase the openness of wireless communications are continuing.

[0006] It is expected that research and development of 6G communication systems in hyper-connectivity, including person to machine (P2M) as well as machine to machine (M2M), will allow the next hyper-connected experience. Particularly, it is expected that services such as truly immersive eXtended Reality (XR), high-fidelity mobile hologram, and digital replica could be provided through 6G communication systems. In addition, services such as remote surgery for security and reliability enhancement, industrial automation, and emergency response will be provided through the 6G communication system such that the technologies could be applied in various fields such as industry, medical care, automobiles, and home appliances.

[0007] The present disclosure relates to a method and apparatus for beamforming for uplink reception in a wireless communication system.

[0008] According to an aspect of an exemplary embodiment, there is provided a communication method in a wireless communication.

[0009] Aspects of the present disclosure provide efficient communication methods in a wireless communication system.

[0010] Figure 1 illustrates a two-dimensional antenna subarray of a base station in accordance with an embodiment of the present disclosure.

[0011] Figure 2 illustrates a diagram of a wireless communication system in accordance with an embodiment of the present disclosure.

[0012] Figure 3 illustrates a diagram of an O-RAN 7-2x base station in accordance with an embodiment of the present disclosure.

[0013] Figure 4 illustrates a generalized scheme of interaction between a wireless communication network and a user equipment for UL beamforming according to 5G NR in accordance with an embodiment of the present disclosure.

[0014] Figure 5 illustrates a block diagram of functional modules of the radio unit and the distributed unit of the O-RAN 7-2x base station according to 5G NR in accordance with an embodiment of the present disclosure.

[0015] Figure 6 illustrates a representation of a code book in accordance with an embodiment of the present disclosure.

[0016] Figure 7 illustrates a flowchart of a method of beamforming for UL reception in accordance with an embodiment of the present disclosure.

[0017] Figures 8a, 8b illustrate quantization and ordering of DFT vectors in the grid of DFT vectors of the code book in accordance with an embodiment of the present disclosure.

[0018] Figure 9 illustrates a compact arrangement of information about a subset of DFT vectors for transmission within CSI, in accordance with an embodiment of the present disclosure.

[0019] Figure 10 illustrates a compact arrangement of information about an ordered subset of DFT vectors for transmission within CSI, in accordance with an embodiment of the present disclosure.

[0020] Figure 11 illustrates a generalized scheme of interaction between a wireless communication network and a user equipment for UL in accordance with an embodiment of the present disclosure.

[0021] Figure 12 illustrates a block diagram of functional modules of the radio unit and the distributed unit of an O-RAN 7-2x base station in accordance with an embodiment of the present disclosure.

[0022] Figure 13 illustrates an UL beamforming by the base station when interacting with multiple user equipments in accordance with an embodiment of the present disclosure.

[0023] Figure 14 is a block diagram of an internal configuration of a UE, according to an embodiment.

[0024] Figure 15 is a block diagram of an internal configuration of a base station or a network entity, according to an embodiment.

[0025] In view of the prior art drawbacks discussed above, the object of the present disclosure is to provide accurate determination of UL beamforming matrix in wireless communication systems where extremely large antenna arrays are used, with due account for losses in UL.

[0026] In the context of addressing the object, according to the first aspect of the present disclosure, a method of beamforming for UL reception in a wireless communication system is provided. The method provided hereby comprises, in a base station of the wireless communication system: defining a number (L) of streams of UL reception. Then, the method comprises, in the base station: generating configuration data for CSI, the configuration data comprising at least parameters of a code book, wherein the code book is formed by a set of DFT vectors; and transmitting the configuration data to a user equipment.

[0027] The method comprises, in the user equipment: based on measurements of CSI-RSs received from the base station, determining at least one channel matrix.

[0028] Then, the method provided herein comprises, in the user equipment: based on the determined at least one channel matrix, calculating a quality metric for each DFT vector from at least part of the set of DFT vectors; based on the calculated quality metrics, selecting a subset of DFT vectors by using a threshold quantization parameter; generating CSI, wherein the CSI includes at least information about the subset of DFT vectors; and transmitting the generated CSI to the base station.

[0029] The method provided herein comprises, in the base station: generating a beamforming (BF) matrix (Wbf) for the UL reception, wherein the BF matrix is generated based on the information about the subset of DFT vectors from the CSI received from the user equipment, wherein a number of beamforming vectors which the BF matrix is comprised of is set based onL.

[0030] According to the second aspect of the present disclosure, a method is provided for beamforming for UL reception in a wireless communication system in which a base station comprises a remote unit (RU) and a distributed unit (DU) interconnected via a fronthaul (FH) interface. The method provided hereby comprises, in the base station: defining a number (L) of streams of UL reception. Then, the method comprises, in the base station: generating configuration data for CSI, the configuration data comprising at least parameters of a code book, wherein the code book is formed by a set of DFT vectors; and transmitting, through the radio unit, the configuration data to a user equipment.

[0031] The method comprises, in the user equipment: based on measurements of CSI-RSs received from the base station, determining at least one channel matrix.

[0032] Then, the method provided herein comprises, in the user equipment: based on the determined at least one channel matrix, calculating a quality metric for each DFT vector from at least part of the set of DFT vectors; based on the calculated quality metrics, selecting a subset of DFT vectors by using a threshold quantization parameter; generating CSI, wherein the CSI includes at least information about the subset of DFT vectors; and transmitting the generated CSI to the base station.

[0033] The method provided herein comprises, in the base station: in the distributed unit, generating a BF matrix based on the information about the subset of DFT vectors from the CSI received from the user equipment, wherein a number of beamforming vectors which the BF matrix is comprised of is set based onL; and transmitting the generated BF matrix from the distributed unit to the remote unit for applying the BF matrix in the remote unit to the UL reception.

[0034] Brief disclosure of embodiments of the method according to the first and / or second aspects of the present disclosure is provided hereinafter.

[0035] In accordance with a preferred embodiment, the number of beamforming vectors of the BF matrix is equal toL.

[0036] According to an embodiment, the quality metric is a relative received power γ calculated as

[0037]

[0038] where

[0039]

[0040] iis ani-th DFT vector from the at least part of the set of DFT vectors;Hkis a channel matrix for ak-th subcarrier, where a dimension of the matrixHkis a number of CSI-RS ports of the base station by a number of receive antenna ports of the user equipment; Nscis a number of subcarriers;pmaxis maximum of calculated received powers {pi}.

[0041] In accordance with an embodiment, the method further comprises, in the base station: setting the threshold quantization parameter; and including the set threshold quantization parameter into the configuration data. As an alternative, the method can further comprise, in the user equipment: presetting the threshold quantization parameter.

[0042] According to an embodiment, the setting the threshold quantization parameter comprises: setting a target number of DFT vectors as the threshold quantization parameter, and the selecting a subset of DFT vectors comprises: selecting the target number of DFT vectors having larger respective relative received powers.

[0043] According to an embodiment, the setting the threshold quantization parameter comprises: setting a relative power threshold as the threshold quantization parameter, and the selecting a subset of DFT vectors comprises: selecting DFT vectors having respective relative received powers greater than or equal to the relative power threshold.

[0044] In accordance with an embodiment, the generating configuration data further comprises: includingLinto the configuration data. The method can further comprise, prior to the generating CSI: in the user equipment, reducing the selected subset of DFT vectors toLDFT vectors with larger respective relative received powers. In particular, in the context of the one embodiment,Lcan be further included into the configuration data as the target number of DFT vectors.

[0045] According to an embodiment, the method further comprises, prior to the generating CSI: in the user equipment, sorting DFT vectors in the subset of DFT vectors according to respective relative received powers.

[0046] In accordance with a preferred embodiment, the generating CSI comprises: including, into the information about the subset of DFT vectors, a respective relative received power for each DFT vector of the subset of DFT vectors.

[0047] According to an embodiment, the generating CSI comprises: including, into the information about the subset of DFT vectors, indices of the DFT vectors of the subset of DFT vectors encoded by the combinatorial encoding, wherein the indices of the DFT vectors are from a common plurality of indices of DFT vectors in the code book along both spatial dimensions.

[0048] According to an embodiment, the generating CSI comprises: including, into the information about the subset of DFT vectors, indices of the DFT vectors of the subset of DFT vectors, wherein the indices are determined by: indicating a preselection of DFT vectors by using a first bitmap along the first spatial dimension of the code book and a second bitmap along the second spatial dimension of the code book; and indexing to indicate the DFT vectors of the subset of DFT vectors in the preselection of DFT vectors.

[0049] In accordance with an embodiment, the selecting a subset of DFT vectors comprises: selecting orthogonal DFT vectors.

[0050] According to a preferred embodiment, the BF matrix is generated further based on information about a subset of DFT vectors from CSI received from each of one or more other user equipments in communication with the base station, wherein the generated BF matrix is applied for UL reception from the user equipment and from the other user equipments.

[0051] According to the third aspect of the present disclosure, a wireless communication system is provided, the wireless communication system comprising at least a base station, the base station comprising, at least: transceiving units; data processing units; and data storage units. The base station is configured to communicate with at least one user equipment comprising, at least: transceiving units; data processing units; and data storage units. The data storage units of the base station have computer-executable codes stored therein, and the data storage units of the user equipment have computer-executable codes stored therein. The computer-executable codes, when executed by the data processing units of the base station and the user equipment, cause the method according to any embodiment of the first or second aspects of the present disclosure to be performed.

[0052] The technical result achievable by the present disclosure is, in general, in providing high quality of UL reception at the base station side; more specifically, in providing beamforming for UL reception with required accuracy and maintenance of low complexity of the LMMSE-IRC receiver, with extension to support of communication systems where extremely large antenna arrays are used.

[0053] Nowadays more and more active deployment of 5th Generation (5G) New Radio (NR) networks takes place, whose advantages and capabilities are broadly known.

[0054] Base stations (BSs) in a 5G NR system use massive antenna arrays containing multiple transceiver antenna elements which enable efficient implementation of multiple-input multiple-output (MIMO) technology, where a number of simultaneously transmitted spatial MIMO layers are generated to transmit data (e.g. physical downlink shared channel (PDSCH)) to one or more user equipments (UEs). In a similar way, one or more MIMO layers are generated for receiving data (for example, physical uplink shared channel (PUSCH)) from each of the user equipments. This architecture is known as Massive MIMO (mMIMO).

[0055] Generally speaking, a digital signal is transmitted or received using one or more digital ports connected to antenna elements of the base station, by means of a radio frequency unit that performs the function of converting the digital signal into an analog one and vice versa. For instance, for the 3.5 GHz frequency range, up to 64 digital antenna ports can be used which enable to use, in base stations, various precoding schemes. For example, the spatial multiplexing (SM) technology enables to reuse the same frequency-time resources for DL transmission of multiple signals (MIMO layers) to one or more user equipments, and the adaptive beamforming (BF) technology enables to dynamically steer power of a transmitted signal to one or more predefined directions. Advanced modulation techniques, such as orthogonal frequency-division multiplexing (OFDM), provide efficient broadband signal transmission

[0056] To illustrate the aforesaid, Figure 1 shows an example of part of a two-dimensional antenna array of a base station, wherein antenna elements (symbolically denoted as × in this figure) are virtualized into N1=4 antenna ports along horizontal and N2=2 antenna ports along vertical. As seen from the illustration, each antenna port in this case corresponds to a subset of three adjacent antenna elements. It is also taken into account that each port is capable of emitting a signal with one of two different, orthogonal polarizations (P=2). These orthogonal polarizations can be linear (vertical and horizontal) polarizations, as well as circular (right and left) polarizations. As a result, the considered antenna subarray supports N1×N2×P=16 digital antenna ports. N1substantially corresponds to the dimension in one (here, horizontal) spatial direction, N2corresponds to the dimension in another (here, vertical) spatial direction, and P corresponds to the polarization dimension. Naturally, similar considerations apply to subarrays with other required dimensions (N1, N2).

[0057] In 5G NR, beamforming is also carried out when receiving uplink (UL) transmissions performed from user equipments to the base station.

[0058] A brief explanation of UL beamforming techniques in accordance with 5G NR is given hereinbelow, for the sake of understanding the technical context of the present disclosure.

[0059] First of all, Figure 2 generally illustrates a wireless communication system which can be a 5G NR communication system. As shown in Figure 2, user equipments (UEs) 201 communicate with base station (BS) 202 in a radio access network (RAN) 200. UE 201 (e.g. UE 201-1, 201-2, 201-3, 201-4, 201-5, 201-6, 201-7, 201-8, 201-9, 201-10, 201-11) are distributed over the RAN 200, and each of the UEs 201 can be fixed or mobile. Broadly known examples of UEs are smartphones, tablets, modems, etc.

[0060] The base stations 202 (e.g. BSs 202-1, 202-2, 202-3) can provide coverage for a specific geographic area commonly referred to as 'cell'. The base stations 202 basically have fixed structure, but they can have mobile implementation as well. In general, the base stations can represent macro-BSs (as illustrated by the BSs 202-1, 202-2, 202-3 in Figure 2), as well as pico-BSs for pico-cells or femto-BSs for femto-cells. Cells in turn can be divided into sectors.

[0061] Coordination and management of operating the base stations 202 can be provided by a network controller which is in communication therewith (for instance, via a backhaul connection). The RAN 200 may communicate with a core network (CN) (for example, via the network controller) which provides various network functions, such as e.g. access and mobility management, session management, authentication server function, application function, etc. Moreover, the base stations 202 in the RAN 200 can also connect to each other, for instance, via a direct physical connection, which is preferably a high-speed connection.

[0062] When a user equipment is moving within the RAN 200, handover of the user equipment from one BS to another BS can be performed. For example, the UE 201-3 can be handed over from the BS 202-2 to the BS 202-1. While performing this, respective operating parameters of the user equipment are reconfigured for operation with the new base station. The user equipment can be also handed over between sectors of one base station.

[0063] Figure 3 illustrates an OpenRAN (O-RAN) architecture in a base station, in accordance with an embodiment.

[0064] The OpenRAN (O-RAN) architecture is implemented in 5G NR - in particular, O-RAN 7-2x - which comprises dividing the base station into two parts and using a fronthaul (FH) interface defined for exchanging information between these functional parts. More specifically, according to this architecture, the base station is divided into a radio unit (RU) and a distributed unit (DU) that are connected to each other via the FH interface (see Figure 3). The functionality implemented by the radio unit (RU) and the distributed unit (DU) in the considered technical context will be described in more detail below.

[0065] Support for the O-RAN architecture is expected in next generation wireless networks.

[0066] Each of the BSs 202 shown in Figure 2 includes hardware and logical means to implement respective functions in the base station. The hardware means refer to, in particular, an antenna array comprised of transceiving antenna elements which have been discussed above, various specially configured processors, controllers, data storage devices, other circuit elements, as well as buses connecting them. The logical means refer to software which is stored in respective memory devices and configures respective circuit elements. Firmware directly hardwired in processors and controllers also refers to the software. The abovementioned hardware means are configuredinter aliato perform various processing with respect to transmitted and received signals, including (de)modulation, (de)multiplexing, (de)coding, amplifying, filtering, digitizing, (de)interleaving, resource allocation, reception / transmission scheduling.

[0067] In a similar way, each of the UEs 201 shown in Figure 2 includes hardware and logical means to implement respective functions in the user equipment. The hardware means refer to, in particular, transceiving devices with respective antenna elements, various specially configured processor(s), controllers, data storage devices, other circuit elements, as well as buses connecting them. The logical means refer to software which is stored in respective memory devices and configures respective circuit elements. Firmware directly hardwired in controllers also refers to the software. The indicated hardware means are configured inter alia to perform various processing with respect to transmitted and received signals, including (de)modulation, (de)multiplexing, (de)coding, amplifying, filtering, digitizing, (de)interleaving. Moreover, the user equipment comprises means to interact with a user, including a touch screen, speakers / microphone, buttons, as well as user applications which are stored in the memory of the user equipment and executed by the processor of the user equipment in a respective operating system.

[0068] Examples of the abovementioned processors / controllers include microprocessors, microcontrollers, digital signal processors (DSPs), field programmable gate arrays (FPGAs), discrete hardware integrated circuits, etc. Firmware / software executed by the processors / controllers should be understood broadly, as referring to computer-executable instructions, instruction sets, program code, code segments, subroutines, program modules, objects, procedures, etc. The software is stored in respective computer-readable media which can be implemented e.g. in the form of random-access memory (RAM), read-only memory (ROM), electrically erasable programmable (EEPROM), solid state storage devices, magnetic storage devices, optical storage devices, etc. which can be recorded with respective program codes and data structures that can be accessed by respective processors / controllers.

[0069] In 5G NR, the following expression is used in the base station to calculate MIMO demodulation weights for received UL signals:

[0070]

[0071] The matrix WRXin equation 1 is referred to as 'LMMSE-IRC receiver'. Thereafter in the text of the specification, for the sake of simplicity, this matrix can be referred to as the LMMSE-IRC receiver or simply the receiver.

[0072] In equation 1,HBSis the channel matrix obtained in the base station, the dimension of said matrix is the number of base station receive digital antenna ports × the number of spatial streams (i.e. MIMO layers) to be received by the base station from one or more user equipments. Let, as one example, the base station have 32 receive digital antenna ports and let it receive one MIMO layer from one user equipment, i.e. single-user MIMO (SU-MIMO) is taking place - in this case, the dimension of the channel matrixHBSwill be 32Х1. Let, as another example, the base station have 64 receive digital antenna ports and let it receive two MIMO layers from each of five user equipments, i.e. multi-user MIMO (MU-MIMO) is taking place - in this case, the dimension of the channel matrixHBSwill be 64×10.

[0073] Furthermore, in equation 1,Ris the covariance matrix by which interference and noise is suppressed at the base station receiver; the dimension of said matrix is the number of receive digital antenna ports × the number of receive digital antenna ports. That is, in the two examples considered in the preceding paragraph, the dimension of the covariance matrixRwill be 32×32 and 64×64, respectively.

[0074] Finally, in equation 1,Iis the identity matrix,Hdenotes Hermitian conjugate.

[0075] For 5G mMIMO, where, as noted earlier, the number of digital antenna ports is large, the receiver in the base station according to equation 1 will be rather complex - first, inversion of matrices of a sufficiently large size regularly occurs; second, if the base station has the O-RAN architecture, undesirably high load onto the FH interface takes place.

[0076] Standard approaches used in 5G NR to reduce receiver complexity are based on uplink beamforming (BF). In general, the task of beamforming is to weight, to a maximally efficient extent, a received UL signal on different receive digital antenna ports of the base station. The weights are selected in a (sub)optimal manner, and signals from the receive digital antenna ports, after applying respective weights thereto, are summed, with obtaining so-called virtual ports the number of which is less than the number of base station digital antenna ports. In other words, beamforming in the considered context is applied in the base station to virtualize a large number of receive digital antenna ports into a smaller number of virtual ports.

[0077] More specifically, beamforming can be reflected by the following equations:

[0078]

[0079]

[0080] In equations 2, 3

[0081]

[0082] is the beamforming matrix,wiis ani-th weight or beamforming vector (BF vector), i=1, ...,L, its size is the number of base station receive digital antenna ports;Heffis the equivalent channel matrix after beamforming;Reffis the equivalent noise and interference covariance matrix after beamforming;Tdenotes transposition.

[0083] The parameterLdefines the number of streams after applying UL beamforming, i.e. the number of virtual ports, and it is chosen in the base station depending on implementation thereof. For instance, the parameterLcan be chosen based on admissible receiver complexity; also, for the O-RAN architecture, this parameter is chosen based on the FH interface constraints. The smaller the value ofL, the less information needs to be transmitted from the RU to the DU for further processing; on the other hand, usage of a larger number of BF vectors is preferable for more efficient, in the sense of interference resistance, subsequent processing of the UL signal. In a typical case,Lis chosen to be less than the number of receive digital antenna ports and not less than the number NMIMOof received MIMO layers.

[0084] As a result, the dimension of the equivalent channel matrixHeffafter beamforming will beL×NMIMO, and the dimension of the equivalent covariance matrixReffafter beamforming will beL×L. Namely, these equivalent matricesHeff,Reffof the smaller dimensions are to be used in equation 1, providing reduction in receiver complexity and reduction in load onto the FH interface.

[0085] It should be noted herein that equations 1-4 have been considered not taking the polarization dimension into account, without loss of generality.

[0086] Thereafter, with references to Figures 4, 5, the description of applying the abovementioned beamforming in a 5G NR wireless communication network (NW) with a base station having the O-RAN 7-2x architecture is provided. The 5G NR approach described here is based on sounding reference signals (SRSs) received in the base station from one or more user equipments.

[0087] Figure 4 illustratively shows a generalized scheme of interaction between the NW and a user equipment (UE), for beamforming in the base station which is part of the NW, for reception of UL transmission from the user equipment. Figure 5 illustratively shows a block diagram of functional modules of the radio unit and the distributed unit of the base station in the context of interaction according to Figure 4.

[0088] Upon reception of an SRS transmission request (SRS Tx indication) (action 410) from the base station, the user equipment transmits SRSs to the base station (action 420). Based on SRSs received from user equipments, the base station performs channel measurements (action 430) and performs calculations for UL beamforming in accordance with equations 2, 3, and 4 (action 440). Next, the base station allocates UL transmission resources to the user equipment and notifies the user equipment about this allocation (UL grant) in downlink control information (DCI) (action 450). The user equipment performs scheduled transmission of PUSCH to the base station (action 460). The base station applies the calculated beamforming matrix and the receiver built accordingly (see equations 1-4) to receive PUSCH (action 470) and performs demodulation of PUSCH (action 480).

[0089] The radio unit of the base station according to Figure 5 receives the UL signal and performs low-level processing thereof (in particular, digitization, fast Fourier transform (FFT)). In this case, the SRSs are extracted as is from the received UL signal, and the extracted SRSs are transmitted to the distributed unit where, based on the SRSs received from the radio unit, the beamforming matrixWbfis calculated, and the generated matrixWbfis transmitted back to the radio unit so that the matrix is applied therein for reducing the number of ports by means of the virtualization described above (see equations 2-4). Then, the distributed unit accordingly generates the receiver (see equation 1) and applies it for demodulating the UL signal, and also performs other standard operations during UL reception (in particular, LDPC decoding of data).

[0090] It should be noted herein that approaches to calculating the beamforming matrixWbfare known in the technical field which the present disclosure relates to. Such approaches are disclosed, in particular, in publications Y. Huang, W. Lei, C. Lu, M. Berg, "Fronthaul Functional Split of IRC-Based Beamforming for Massive MIMO Systems", 2019 IEEE 90th Vehicular Technology Conference (VTC2019-Fall), Honolulu, HI, USA, 2019, pp. 1-5, doi: 10.1109 / VTCFall.2019.8891191 and Y. Huang, C. Lu, M. Berg, P. Odling, "Functional Split of Zero-Forcing Based Massive MIMO for Fronthaul Load Reduction", IEEE Access, vol. 6, pp. 6350-6359, 2018, doi: 10.1109 / ACCESS.2017.2788451, which are both entirely incorporated into the present specification by reference. For example,Wbfcan be calculated based on principal eigenvectors of channel matrices obtained by using measured SRSs received from one or more user equipments.

[0091] Though deployment of 5G NR systems in the world is only spinning up, nevertheless active research is being already carried out now in different directions for standardization of next generation wireless communication systems, so called 6G, which will have characteristics superior to 5G NR.

[0092] In particular, for the 6G operating range of 9-13 GHz (UPPER MID BAND), it is planned to support, at base stations, extremely large antenna arrays (for instance, comprised of 3072 antenna elements), with hybrid analog and digital beamforming with a large number of antenna ports (≤256). Therefore, by supporting, in particular, up to 64 simultaneously transmitted spatial MIMO layers in UPPER MID BAND communication systems, the concept of radio interface with extremely large antenna array (xMIMO) will be rendered to a principally new level. Moreover, support of a set of reference signals similar to the one used in 5G NR, such as DMRS, CSI-RS, SRS, PT-RS, PSS / SSS, is planned in 6G.

[0093] At the same time, approaches used in 5G NR may not be always directly extended to next generation communication systems.

[0094] For instance, direct application of the above approach to UL beamforming, which has proven itself for 5G mMIMO, will generally not be so efficient for the case of 6G xMIMO. As noted earlier, the next generation wireless communication system provides support of up to 256 digital antenna ports and 16 MIMO layers per UE; accordingly, the dimensions of the channel matrices and covariance matrices at the base station side will be significantly larger than in the case of 5G NR. At the same time, usage of SRSs in the context of xMIMO for channel estimation and beamforming becomes difficult for the following reasons. In the 6G operating range of 9-13 GHz, due to wideband signal transmission and transmission power limitations at user equipments, power spectral density significantly decreases, while losses increase, and, accordingly, quality of SRS reception in the base station degrades noticeably. This is especially fair for user equipments located closer to the boundary of the cell served by the base station. Therefore, accuracy of calculating BF vectors in the base station, which the UL beamforming matrix is comprised of, also decreases, thereby causing general degradation of reception quality.

[0095] Hereinafter reference is made to exemplary embodiments of the present disclosure which are illustrated in the accompanying drawings where the same reference numerals denote similar elements. It should be appreciated that the embodiments of the disclosure can have various forms and should not be considered to be limited by the descriptions given herein. Therefore, the exemplary embodiments are described hereinbelow with reference to the drawings to elucidate the essence of the aspects of the present disclosure.

[0096] It should be noted that the diagram according to Figure 2 can also serve as a general illustration of a wireless communication system in which various aspects of the present disclosure can be implemented. It is necessary to emphasize that the description according to Figure 2 and this figure itself have solely illustrative, non-limiting nature for the purpose of outlining the general operating environment of the present disclosure. Although Figure 2 illustrates only known basic components of the communication system, it should be appreciated that the communication system can additionally include a plurality of other elements.

[0097] The hardware and software elements of the base station and the user equipment, as listed above, are configured to provide execution, in the base station and in the user equipment, of the methods according to the present application which are described below. Implementation of the component hardware of the base station and user equipment and specialized configuring thereof, including by respective logical means, are known in the technical field which the present application relates to. Moreover, various functions according to the methods of the present application can be performed in multiple separate elements or in one or more integral elements, which is defined by design structural characteristics.

[0098] The present disclosure is underlain by the concept which, in general, comprises using for UL beamforming in the base station - instead of SRSs - feedback information from user equipments which is obtained by measurements of the downlink channel in the user equipments. More specifically, each of the user equipments performs measurements of channel state information (CSI) reference signals (RSs), i.e. CSI-RSs, transmitted from the base station, and performs quantization of obtained information about the signal space of the channel; thereafter the quantized information is reported to the base station within CSI transmitted from the user equipment. The base station, in turn, uses the quantized information received from the user equipments to obtain the beamforming matrix.

[0099] It should be explained herein that in existing communication systems, including 5G NR, CSI-RSs are transmitted from a base station to user equipments for estimation of the state of channels corresponding to digital antenna ports of the base station. Depending on implementation, each CSI-RS can correspond to one digital antenna port, or additional virtualization is performed in such a way that each CSI-RS can correspond to more than one (for example, two) digital antenna ports. In other words, in view of this additional virtualization, the virtualized representation of antenna elements of the base station antenna array in the form of CSI-RS antenna ports is ultimately used. It should be noted that when communicating with the base station, a user equipment should not be aware of the actual structure of the base station antenna array - this communication is basically carried out in the level of CSI-RS antenna ports of the base station, i.e. each CSI-RS antenna port is considered as a single emitting element, regardless of antenna elements encompassed thereby.

[0100] Since transmission power of the base station isa priorisufficient to provide coverage of the entire cell being served thereby, then quality of reception and, accordingly, accuracy of measurements of CSI-RSs received by each of served user equipments is high.

[0101] The detailed disclosure of this approach to UL beamforming according to the present disclosure is provided hereinbelow.

[0102] The abovementioned quantization according to the present disclosure is based on usage, in the user equipment, of a code book which is formed by a set of discrete Fourier transform (DFT) vectors.

[0103] Figure 6 illustrates a representation of the code book with reference to the subarray discussed above with reference to Figure 1.

[0104] Referring to Figure 6, The code book is basically illustrated in Figure 6 by the two-dimensional (along a first spatial dimension and along a second spatial dimension) grid of DFT vectors. Each DFT vector is shown as a circle in the grid. Light grey circles symbolically show DFT vectors that directly correspond to N1×N2= 8 (i.e., in this case, four in the horizontal direction, two in the vertical direction) antenna ports illustrated in Figure 1. These DFT vectors are mutually orthogonal. In addition, by using oversampling coefficients (O1, O2), a sequential linear phase shift is provided for each DFT vector in the directions N1, N2, respectively. As a result, the dimension of the code book is N1·O1in the horizontal direction and N2· O2in the vertical direction, i.e. the total number of DFT vectors in the code book is N1· O1· N2· O2. DFT vectors in the code book are indexed in the horizontal direction by index l, l = 0, . . ., N1· O1- 1, and in the vertical direction by index m, m = 0, . . ., N2· O2- 1. In the case considered in Figure 6, O1= O2= 4. For illustrative purposes, a specific DFT vector selected from the code book is symbolically shown as the black circle in Figure 6.

[0105] Each DFT vector is the Kronecker product of a column vector , where

[0106]

[0107] by a column vectoru, where

[0108]

[0109] i.e.

[0110]

[0111] In equations 5, 6 j is imaginary unit.

[0112] The number of elements in the vector is equal to the number of antenna ports in the first spatial dimension (in this case, horizontal), i.e.N1, and the number of elements in the vectoruis equal to the number of antenna ports in the second spatial dimension (in this case, vertical), i.e.N2. Accordingly, the number of elements in any DFT vector will beN1·N2.

[0113] According to an embodiment, the code book illustrated in Figure 6 can be a code book based on 5G NR Type 1 code book which is basically used in 5G NR for DL precoding. Possible supported Type 1 code book configurations can be identified according to Table 5.2.2.2.1-2 from specification TS 38.214, v.17.4.0 which is entirely incorporated into the present application by reference:

[0114]

[0115] Therefore, possible values of the parametersN1,O1,N2,O2, which are used in equations 5-7, can be set in accordance with Table 5.2.2.2.1-2.

[0116] According to another embodiment, 5G NR Type 2 / eType 2 code book can be used in the considered context.

[0117] Then, with reference to the block diagram in Figure 7, the description of a method 700 of beamforming for UL reception in a wireless communication system, which can be e.g. a next-generation wireless communication system, is provided.

[0118] In step 710, a base station (e.g. such as BS 202-1, 202-2, 202-3 according to Figure 2) defines a numberLof streams of UL reception, or, in other words, a number of virtual ports. The defining is carried out, in general, in a way similar to the one described above in relation to 5G NR.

[0119] In step 720, the base station generates configuration data for CSI, where the data is required for a user equipment (e.g. such as UE 201-1, 201-2, . . ., 201-11 according to Figure 2) to report the CSI to the base station. The configuration data includes, at least, parameters of the code book. As stated above, the code book parameters can comprise the numberN1of base station antenna ports in the first spatial dimension (e.g. horizontal) and the respective oversampling parameterO1, and the numberN2of base station antenna ports in the second spatial dimension (e.g. vertical) and the respective oversampling parameterO2. Then, in this step, the generated configuration data is transmitted by the base station to the user equipment. This DL transmission can be performed by using DCI, MAC, RRC signaling, or a combination thereof.

[0120] In step 730, the user equipment performs measurements of CSI-RSs received from the base station, and, based on these measurements, determines one or more channel matrices. According to an embodiment of the present disclosure, the user equipment can determine a channel matrixHfor each of downlink subcarriers, wherein a technique similar to the one used according to 5G NR for determining the channel matrixHBSin the base station (see equation 1 above and the accompanying disclosure) can be used to determine the channel matrix in this case. For example, the channel estimation at the user equipment side to obtain the channel matrices can be performed by using a known algorithm, such as MMSE, upon demodulation of the received CSI-RSs.

[0121] It should be obvious to a skilled artisan that step 730 does not necessarily have to follow step 720, as indicated above: for example, step 730 can be performed in parallel with step 720 or even precede it.

[0122] In step 740, the user equipment calculates a quality metric for each DFT vector from the set of DFT vectors of the code book. According to a preferred embodiment of the present disclosure, the quality metric for ani-th DFT vector is a relative received power γicalculated by normalizing a received powerpicorresponding to this DFT vector by the received power maximum valuepmax:

[0123]

[0124] where

[0125]

[0126] iis an i-th DFT vector from the set of DFT vectors;Hkis a channel matrix for a k-th DL subcarrier, the dimension of the matrixHkis the number of base station CSI-RS antenna ports × the number of user equipment receive antenna ports;Nscis the number of DL subcarriers. Naturally,pmaxis the maximum of all the calculated received power values {pi}, i.e.pmax=max({pi}). The relative received power substantially shows the contribution made by a respective DFT vector to the signal space.

[0127] It should be noted that, according to another embodiment(s), non-normalized received power values, i.e.p, can be used as the quality metrics, or a different way of normalizing thereof can be used to obtain relative received powers.

[0128] It should be obvious to a skilled artisan that, in the context of the present disclosure, the quality metrics may be calculated not for all DFT vectors of the code book, but for some predetermined part thereof. For example, it may be known in advance regarding some DFT vectors that a quality indicator corresponding thereto will be low, and these vectors are excluded from the analysis according to the method 700.

[0129] In step 750, the user equipment performs quantization based on the quality metrics calculated in step 740 by selecting a respective subsetJof DFT vectors. This selection is performed by using a threshold quantization parameter.

[0130] According to the first embodiment of the present disclosure, a threshold value ε of relative power can be used as the threshold quantization parameter. Accordingly, the quantized subset J of DFT vectors will include DFT vectors iwhich have respective calculated relative received powers γithat are not less than the threshold value ε:

[0131]

[0132] where is the set of indices (k) of DFT vectors for which relative received powers are calculated as the quality metric. For example, ={0,…,N1·O1·N2·O2-1}.

[0133] In accordance with one non-limiting example, the threshold value ε can be set in the base station and signaled to the user equipment in the configuration data which is generated in step 720. According to an illustrative implementation, the value ε can be chosen in the base station as follows. For user equipments with limited power (typically, such user equipments are located near the cell boundary), the value ε is chosen to be close to 0.05 to minimize losses in the received signal power. For user equipments without such power limitations (typically, such user equipments are located closer to the base station), the value ε is chosen to be close to 0.5 to reduce the number of DFT vectors to be selected.

[0134] According to another non-limiting example, the threshold value ε can be preconfigured in the user equipment - for instance, this value can be signaled by the base station to the user equipment in advance, before execution of the method 700 starts. This aspect does not impose limitations onto the present disclosure.

[0135] In accordance with the second embodiment of the present disclosure, a target numberNtargetof DFT vectors in the quantized subset thereof can be used as the threshold quantization parameter. In this case,NtargetDFT vectors with larger respective relative received powers are selected into the subsetJ, that is, with relative received powers that are greater than or equal to relative received powers corresponding to the remaining DFT vectors of the DFT vector set or a predetermined part thereof. Those DFT vectors that are filtered out from the quantized subsetJof DFT vectors according to the criterion can be referred to as 'weaker' DFT vectors throughout the text of the present application.

[0136] Similarly to the first embodiment,Ntargetcan be set in the base station and signaled to the user equipment in the configuration data generated in step 720, orNtargetcan be preconfigured in the user equipment.

[0137] According to one possible implementation, the numberLof virtual ports defined by the base station in step 710 can be included into the configuration data generated in step 720. For this implementation, in the first embodiment according to step 750 discussed above, the resulting subsetJof DFT vectors can be reduced to a subset ofLDFT vectors with larger respective relative received powers - in other words, 'weaker' DFT vectors are excluded from the subsetJ, while maintainingLDFT vectors that form the subset . For the considered implementation, in the second embodiment discussed above,Lcan act asNtarget, i.e.Ntarget=L.

[0138] For illustrative purposes, in Figure 8a, the DFT vectors selected into the final quantized subset of DFT vectors are shown as grey circles in the grid of DFT vectors of the code book, and the respective relative received powers are also shown.

[0139] It should also be noted that, in accordance with an embodiment of the present disclosure, the selection of the subset of DFT vectors may be additionally limited by the condition of orthogonality of the DFT vectors in the selected subset.

[0140] According to another possible implementation, DFT vectors in the resulting quantized subset of DFT vectors can be sorted in the user equipment according to respective relative received powers. For illustrative purposes, in Figure 8b, the sorted DFT vectors of the quantized subset are shown as grey circles in the grid of DFT vectors of the code book, where a DFT vector with a lower index corresponds to larger relative received power. This sorting can be reflected by the following expression of equation 11, similarly to equation 10:

[0141]

[0142] In step 760, the user equipment generates CSI, wherein the CSI includes, at least, information about the subset of DFT vectors generated in step 750. The generated CSI is transmitted from the user equipment to the base station.

[0143] It should be explained herein that in wireless communication systems, in general (and in 5G NR, in particular), there are special procedures for UL transmission of various control information, such as the precoding matrix indicator (PMI), rank indication (RI) (by which a user equipment indicates a recommended number of MIMO layers that the user equipment is ready to receive), channel quality indicator (CQI), within CSI, and CSI transmissions are possible with various combinations of the reported control parameters (e.g., PMI+RI+CQI, RI+CQI). In particular, the standard combination (PMI+RI+CQI) is used for adaptation of DL transmission. In the case of the present disclosure, it is implied that the information about the quantized subset of DFT vectors can be transmitted via CSI by using such standard procedures, and the information can be transmitted separately from or together with various combinations of PMI, RI, CQI, and other control parameters.

[0144] According to one implementation, a single bitmap for both spatial dimensions with a single indexing can be used to represent the information about the subset of DFT vectors within the CSI. In this case, the encoded representation of the selected subset of DFT vectors can have the following form:

[0145]

[0146] wherebitakes the value 1 for a selected DFT vector and 0 for a non-unselected (e.g. 'weaker') DFT vector. This implementation is characterized, on one hand, by high flexibility, i.e. it enables to encode any combination of indices of the selected DFT vectors, but, on the other hand, it is also characterized by high bit overhead.

[0147] In accordance with a preferred embodiment of the present disclosure, in step 760, a respective relative received power calculated in step 740 is additionally included into the information about the subset of DFT vectors for each DFT vector of the subset. This inclusion enables to directly inform the base station about the contribution made by each DFT vector to the reported signal space.

[0148] According to another embodiment, for the case of ordering DFT vectors in the quantized subset of DFT vectors, as reflected in the description of step 750 with reference to Figure 8b and equation 11, relative received powers may not be included in the CSI. This embodiment assumes that the base station will be implicitly informed by the ordering about the relative contribution made by each DFT vector of the subset to the reported signal space.

[0149] Thereafter, implementations of compact arrangement of the information about the subset of DFT vectors to reduce the bit overhead associated with reporting the information within the CSI are described hereinbelow.

[0150] According to the first implementation, the combinatorial encoding is used. In this case, under assumption that the subset of DFT vectors comprisesLDFT vectors (see step 750), indices xi, i=0,…,L-1, of DFT vectors from the overall plurality of indices in the amount ofN1·O1·N2·O2over both spatial dimensions of the code book (see Figure 6 for illustration), i.e. {x_i }: 1≤x0<x1…<xL-1≤N1·O1·N2·O2, are encoded in the form of a code point p:

[0151]

[0152] In equation 13

[0153]

[0154] According to the second implementation, representation of indices of DFT vectors of the subset of selected DFT vectors by means of bitmaps is used, where two stages are involved. In the first stage, a separate bitmap is used for each of the spatial dimensions, with its own indexing, to indicate a preliminary selection of DFT vectors. Similarly to equation 12, the preliminary selection carried out by using two bitmaps can have the following form:

[0155]

[0156] wherekis equal to 1 for the first spatial dimension and 2 for the second spatial dimension, and takes the value 1 for a preliminarily selected DFT vector and 0 for a non-selected DFT vector. In the second stage, based on the generated bitmaps x(1), x(2), the selected subset of DFT vectors is encoded into the final representation p by means of internal indexing over the preliminarily selected DFT vectors.

[0157] The considered second implementation is illustrated in Figure 9. The upper part of this figure shows the preliminary selection of DFT vectors, respectively represented by the bitmaps x(1)=(0,1,1,0,0,0,1,0) and x(2)=(0,1,0,1) (see equation 14). The preliminarily selected DFT vectors are shown as hatched grey squares. As illustrated in the lower part of Figure 9, the DFT vectors selected into the subset of DFT vectors are represented by indexing over the preliminary selection of DFT vectors based on the bitmaps, namely as p=(1,4,5,6). These selected DFT vectors are shown in Figure 9 as black squares.

[0158] The third implementation corresponds to an embodiment of step 750 of the method 700 according to the present disclosure, when, before generating the CSI in step 760, ordering of DFT vectors in the subset of DFT vectors is performed. This implementation is illustrated in Figure 10, where the representation p of the selected DFT vectors is expressed as a combination of two sets of indices

[0159]

[0160] where are indices of selected DFT vectors in the first spatial dimension of the code book (horizontal in Figure 10), and are indices of selected DFT vectors in the second spatial dimension of the code book (vertical in Figure 10). Therefore, according to the illustration of Figure 10, the selected subset of DFT vectors (black squares) is represented as x(1)=(2,1,6,6), x(2)=(3,1,3,1), where the first DFT vector indicated by indices {2,3} corresponds to the largest relative received power, the second DFT vector indicated by indices {1,1} corresponds to the second largest relative received power, and so on.

[0161] It should be noted that in the implementations of representing information about the subset of DFT vectors, as considered above, other options of indexing and / or other values of bits in the bitmaps can be used in a way obvious to a skilled artisan (for example, 0 can indicate a selected DFT vector, and 1 can indicate a non-selected DFT vector).

[0162] In step 770, the base station generates a beamforming matrixWbffor the UL reception, the matrix being comprised of beamforming vectors (see equation 4). According to the present disclosure, the beamforming matrix is generated based on the information about the quantized subset of DFT vectors from the CSI received from the user equipment. As noted earlier, the number of beamforming vectorsw, which the matrixWbfis comprised of, is set based onLchosen in step 710.

[0163] It should be explained herein that in the case of consideration of operating base station antenna ports with one polarization, which has been discussed above, the number of beamforming vectors of the beamforming matrix will be equal toL. At the same time, if operation of base station antenna ports with two orthogonal polarizations is taken into account, then the parameterLwill represent the number of UL reception streams, after beamforming, per each of the two polarizations. That is, the total number of UL reception streams (and, accordingly, the total number of BF vectors) will be 2·L, while the subset of DFT vectors selected in step 750 and reported in step 760 will be the same for both polarizations. The case when the number of vectors w in the matrixWbfisLwill be considered hereinbelow, without loss of generality.

[0164] It should be noted herein that the generating itself of the beamforming matrix in the base station does not directly relate to the subject of the present disclosure. As an example, algorithms similar to those used in 5G NR to generate a beamforming matrix based on SRSs can be used to generate the matrixWbfin a way obvious to a skilled artisan.

[0165] Then, the generated matrixWbfis applied in the base station to the channel matrixHBSand covariance matrixRaccording to equations 2, 3, respectively, and the resulting equivalent channel matrixHeffafter beamforming and equivalent covariance matrixReffafter beamforming are used to build the receiver in accordance with equation 1.

[0166] It should be noted that the generating itself of the matricesHBSandRin the base station does not directly relate to the subject of the present disclosure. As an example, respective 5G NR algorithms can be used to estimate the matrices.

[0167] Furthermore, similarly to the discussion of Figures 4, 5 above, application of UL beamforming according to the present disclosure in a wireless communication network (NW) with a base station having architecture similar to the O-RAN 7-2x is described with references to Figures 11, 12. The wireless communication network can be a next-generation communication network, for example, 6G.

[0168] In Figure 11, similarly to Figure 4, a generalized scheme is shown, the scheme illustrating interaction between the NW and a user equipment for carrying out, in the base station which is part of the NW, beamforming for reception of UL transmission from the user equipment. In Figure 12, similarly to Figure 5, a block diagram of functional modules of the radio unit and the distributed unit of the base station is illustratively shown in the context of the interaction according to Figure 11.

[0169] The base station transmits CSI-RSs (action 1101). The user equipment performs measurements of the received CSI-RSs and generates one or more channel matrices based on the measurements (action 1102, step 730). Then, a quantized subset of DFT vectors is generated in the user equipment according to the present disclosure (action 1103, steps 740, 750), and the quantized subset is reported to the base station within CSI (action 1104, step 760). Based on the received CSI, the base station calculates a beamforming matrix to be applied for the UL reception (action 1105, step 770).

[0170] Thereafter, the description of the considered interaction scheme is given for a preferred embodiment.

[0171] Upon reception of an SRS transmission request from the base station (action 1106), the user equipment transmits SRSs to the base station (action 1107). Unlike 5G NR, UL beamforming according to the present disclosure will be applied to the received SRSs (action 1108), and accuracy of measurements of the SRSs in the base station can be increased thereby. Next, the base station allocates resources for UL transmission to the user equipment and notifies the user equipment about the allocation in DCI (action 1109). The user equipment performs the scheduled transmission of PUSCH to the base station (action 1110). The base station applies the generated beamforming matrix and the receiver built accordingly (see equations 1-4) to receive PUSCH (action 1111), and performs demodulation of PUSCH (action 1112).

[0172] Functional modules of the radio unit and distributed unit of the base station according to Figure 12, in general, can be implemented in a similar way and perform functions similar to those of the radio unit and distributed unit of 5G NR shown in Figure 5, except for the part designated by the dashed frame in Figure 12. In particular, in order to calculate the beamforming matrixWbf, unlike Figure 5, it is not required to preliminarily extract, in the radio unit, SRSs received from the user equipment and provide them to the distributed unit - in view of the aforesaid, according to the present disclosure, the matrixWbfis calculated in a respective module of the distributed unit based on the quantized subset of DFT vectors previously reported by the user equipment within the CSI, and the generated matrixWbfis transmitted to the radio unit for being applied to reduce the number of ports by the virtualization, as described above with reference to equations 2-4. Then, the distributed unit accordingly generates the receiver (see equation 1) and applies it for demodulating the UL signal, and also performs other standard operations during UL reception. It should be again emphasized herein that, unlike 5G NR, beamforming according to the present disclosure can be applied to SRSs within the UL signal received in the radio unit, and then the SRSs after beamforming are used in the distributed unit for, in particular, scheduling and allocating resources for UL transmission.

[0173] The generating of the beamforming matrix has been described above for the case when the CSI with the quantized subset of DFT vectors is provided to the base station by one user equipment. At the same time, the present disclosure provides for a scenario where such sets are provided by each user equipment from some plurality of user equipments served by the base station. That is, each of these user equipments performs steps 730-760 of the method 700, actions 1102-1104 of Figure 11. At the same time, based on CSI received from user equipments, the base station generates one beamforming matrixWbfand one receiver for being applied to UL transmissions from the entire plurality of user equipments. This scenario is illustrated in Figure 13.

[0174] A way in whichWbfis specifically generated at the base station side based on the subsets of selected DFT vectors and associated relative powers from different user equipments depends on implementation of the base station, and there may be various embodiments.

[0175] In accordance with an illustrative example, a scheduler of the base station generates, for group A of user equipments, a common matrix characterizing the signal space of this group of user equipments, i.e.

[0176]

[0177] Then, the base station calculates, for the generated matrix U,Lprincipal eigenvectors, i.e. vectors corresponding toLlargest eigenvalues. These eigenvectors are used as beamforming vectorswwhich the matrixWbffor the group of user equipments is comprised of.

[0178] The following should also be noted regarding the considered scenario with reference to Figures 11, 13. The beamforming matrix applied in the base station to receive PUSCH according to action 1111 does not necessarily have to be exactly the same as the one calculated in the base station according to action 1105. For example, afterWbfhas been generated according to action 1105 and before performing action 1111, the base station can receive, from one of the user equipments of group A, CSI with a quantized subset of DFT vectors and associated relative received powers, and the base station can accordingly update the beamforming matrix by using the received CSI, before performing action 1111. That is, generally speaking, actions 1102-1104 can be performed at the side of the user equipment in the considered interval between execution of actions 1105 and 1111 in the base station.

[0179] This aspect of updating is, in general, also fair in relation to Figure 11 itself, i.e. for the case of the base station interacting with one user equipment.

[0180] Figure 14 is a block diagram of an internal configuration of a UE, according to an embodiment. Furthermore, the UE of Figure 14 corresponds to the UE of Figure 2.

[0181] As shown in Figure 14, the UE according to an embodiment may include a transceiver 1410, a memory 1420, and a processor 1430. The transceiver 1410, the memory 1420, and the processor 1430 of the UE may operate according to a communication method of the UE described above. However, the components of the UE are not limited thereto. For example, the UE may include more or fewer components than those described above. In addition, the processor 1430, the transceiver 1410, and the memory 1420 may be implemented as a single chip. Also, the processor 1430 may include at least one processor.

[0182] The transceiver 1410 collectively refers to a UE receiver and a UE transmitter, and may transmit / receive a signal to / from a base station or a network entity. The signal transmitted or received to or from the base station or a network entity may include control information and data. The transceiver 1410 may include a RF transmitter for up-converting and amplifying a frequency of a transmitted signal, and a RF receiver for amplifying low-noise and down-converting a frequency of a received signal. However, this is only an example of the transceiver 1410 and components of the transceiver 1410 are not limited to the RF transmitter and the RF receiver.

[0183] Also, the transceiver 1410 may receive and output, to the processor 1430, a signal through a wireless channel, and transmit a signal output from the processor 1430 through the wireless channel.

[0184] The memory 1420 may store a program and data required for operations of the UE. Also, the memory 1420 may store control information or data included in a signal obtained by the UE. The memory 1420 may be a storage medium, such as read-only memory (ROM), random access memory (RAM), a hard disk, a CD-ROM, and a DVD, or a combination of storage media.

[0185] The processor 1430 may control a series of processes such that the UE operates as described above. For example, the transceiver 1410 may receive a data signal including a control signal transmitted by the base station or the network entity, and the processor 1430 may determine a result of receiving the control signal and the data signal transmitted by the base station or the network entity.

[0186] Figure 15 is a block diagram of an internal configuration of a base station or a network entity, according to an embodiment. Furthermore, the base station or the network entity of the Figure 15 corresponds to the BS of Figure 2 and Figure 3.

[0187] As shown in Figure 15, the base station or the network entity according to an embodiment may include a transceiver 1510, a memory 1520, and a processor 1530. The transceiver 1510, the memory 1520, and the processor 1530 of the base station or the network entity may operate according to a communication method of the base station or the network entity described above. However, the components of the base station or the network entity are not limited thereto. For example, the base station or the network entity may include more or fewer components than those described above. In addition, the processor 1530, the transceiver 1510, and the memory 1520 may be implemented as a single chip. Also, the processor 1530 may include at least one processor.

[0188] The transceiver 1510 collectively refers to the base station(or the network entity receiver) and a base station(or the network entity) transmitter, and may transmit / receive a signal to / from a terminal or a network entity or a base station. The signal transmitted or received to or from the terminal or a network entity or the base station may include control information and data. The transceiver 1510 may include a RF transmitter for up-converting and amplifying a frequency of a transmitted signal, and a RF receiver for amplifying low-noise and down-converting a frequency of a received signal. However, this is only an example of the transceiver 1510 and components of the transceiver 1510 are not limited to the RF transmitter and the RF receiver.

[0189] Also, the transceiver 1510 may receive and output, to the processor 1530, a signal through a wireless channel, and transmit a signal output from the processor 1530 through the wireless channel.

[0190] The memory 1520 may store a program and data required for operations of the base station or the network entity. Also, the memory 1520 may store control information or data included in a signal obtained by the base station or the network entity. The memory 1520 may be a storage medium, such as read-only memory (ROM), random access memory (RAM), a hard disk, a CD-ROM, and a DVD, or a combination of storage media.

[0191] The processor 1530 may control a series of processes such that the base station or the network entity operates as described above. For example, the transceiver 1510 may receive a data signal including a control signal transmitted by the terminal or the network entity or the base station, and the processor 1530 may determine a result of receiving the control signal and the data signal transmitted by the terminal or the network entity or the base station.

[0192] As follows from the aforesaid, the present disclosure provides beamforming in the base station for UL reception with required accuracy and maintenance of low complexity of the LMMSE-IRC receiver, along with extension to support of communication systems where extremely large antenna arrays are used, thereby, in turn, providing high quality of UL reception at the base station side.

[0193] It should also be appreciated that the illustrated exemplary embodiments are only preferred, but not the only possible implementations of the disclosure. Specifically, the scope of the present disclosure is defined by the claims and equivalents thereof.

Claims

1.A method performed by a user equipment (UE) in a wireless communication system, the method comprising:receiving, from a base station (BS), configuration data for channel state information (CSI), wherein the configuration data comprises at least parameters of a code book formed by a set of digital Fourier transform (DFT) vectors;receiving, from the BS, CSI reference signals (CSI-RSs);determining at least one channel matrix, based on measurements of the CSI-RSs;calculating a quality metric for each DFT vector from at least part of the set of DFT vectors, based on the determined at least one channel matrix;selecting a subset of DFT vectors by using a threshold quantization parameter, based on the calculated quality metrics; andtransmitting, to the BS, CSI, wherein the CSI includes at least information about the subset of DFT vectors; andwherein a beamforming (BF) matrix for uplink (UL) reception is generated based on the CSI.2.The method of claim　1,wherein the BF matrix is generated based on the information about the subset of DFT vectors from the CSI, andwherein a number of beamforming vectors which the BF matrix is comprised of is set based on a number(L) of streams of UL reception.3.The method of claim　2, wherein the number of beamforming vectors of the BF matrix is equal toL.4.The method of claim　1, wherein the parameters of the code book comprise at least a number (N1) of antenna ports of the BS along a first spatial dimension and a respective oversampling parameter (O1), and a number (N2) of antenna ports of the BS along a second spatial dimension and a respective oversampling parameter (O2), wherein a number of DFT vectors of the code book is equal toN1·O1·N2·O2.5.A method performed by a base station (BS), the method comprising:transmitting, to a user equipment (UE), configuration data for channel state information (CSI), wherein the configuration data comprises at least parameters of a code book formed by a set of digital Fourier transform (DFT) vectors;transmitting, to the UE, CSI reference signals (CSI-RSs);receiving, from the UE, CSI, wherein the CSI includes at least information about a subset of DFT vectors; andgenerating a beamforming (BF) matrix for uplink (UL) reception based on the CSI; andwherein the subset of DFT vectors is selected by using a threshold quantization parameter based on quality metrics, andwherein each of quality metrics for each DFT vector is calculated from at least part of the set of DFT vectors, based on at least one channel matrix determined based on measurements of the CSI-RSs.6.The method of claim　5,wherein the BF matrix is generated based on the information about the subset of DFT vectors from the CSI received from the user equipment, andwherein a number of beamforming vectors which the BF matrix is comprised of is set based on a number(L) of streams of UL reception.7.The method of claim　6, wherein the number of beamforming vectors of the BF matrix is equal toL.8.The method of claim 1, wherein the parameters of the code book comprise at least a number (N1) of antenna ports of the BS along a first spatial dimension and a respective oversampling parameter (O1), and a number (N2) of antenna ports of the BS along a second spatial dimension and a respective oversampling parameter (O2), wherein a number of DFT vectors of the code book is equal toN1·O1·N2·O2.9.A user equipment (UE) in a wireless communication, comprising:a transceiver; anda controller coupled with the transceiver, wherein the at least one controller is configured to:receive, from a base station (BS), configuration data for channel state information (CSI), wherein the configuration data comprises at least parameters of a code book formed by a set of digital Fourier transform (DFT) vectors;receive, from the BS, CSI reference signals (CSI-RSs);determine at least one channel matrix, based on measurements of the CSI-RSs;calculate a quality metric for each DFT vector from at least part of the set of DFT vectors, based on the determined at least one channel matrix;select a subset of DFT vectors by using a threshold quantization parameter, based on the calculated quality metrics; andtransmit, to the BS, CSI, wherein the CSI includes at least information about the subset of DFT vectors; andwherein a beamforming (BF) matrix for uplink (UL) reception is generated based on the CSI.10.The UE of claim　9,wherein the BF matrix is generated based on the information about the subset of DFT vectors from the CSI, andwherein a number of beamforming vectors which the BF matrix is comprised of is set based on a number(L) of streams of UL reception.11.The UE of claim　10, wherein the number of beamforming vectors of the BF matrix is equal toL.12.The UE of claim 9, wherein the parameters of the code book comprise at least a number (N1) of antenna ports of the BS along a first spatial dimension and a respective oversampling parameter (O1), and a number (N2) of antenna ports of the BS along a second spatial dimension and a respective oversampling parameter (O2), wherein a number of DFT vectors of the code book is equal toN1·O1·N2·O2.13.A base station (BS) in a wireless communication system, the BS comprising:a transceiver; anda controller coupled with the transceiver, wherein the at least one controller is configured to:transmit, to a user equipment (UE), configuration data for channel state information (CSI), wherein the configuration data comprises at least parameters of a code book formed by a set of digital Fourier transform (DFT) vectors;transmit, to the UE, CSI reference signals (CSI-RSs);receive, from the UE, CSI, wherein the CSI includes at least information about a subset of DFT vectors; andgenerate a beamforming (BF) matrix for uplink (UL) reception based on the CSI; andwherein the subset of DFT vectors is selected by using a threshold quantization parameter based on quality metrics,wherein each of quality metrics for each DFT vector is calculated from at least part of the set of DFT vectors, based on at least one channel matrix determined based on measurements of the CSI-RSs.14.The BS of claim　13,wherein the BF matrix is generated based on the information about the subset of DFT vectors from the CSI received from the user equipment, andwherein a number of beamforming vectors which the BF matrix is comprised of is set based on a number(L) of streams of UL reception.15.The method of claim　14, wherein the number of beamforming vectors of the BF matrix is equal toL.

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