Beamforming

Abstract

The embodiment of the invention relates to equipment, a method and a device for beam forming and a computer readable storage medium. The first device determines a first set of candidate horizontal beams by continuously transforming an initial horizontal beam vector by a horizontal channel covariance matrix. The first device determines a second set of candidate vertical beams by continuously transforming the initial vertical beam vector by a vertical channel covariance matrix. The first device determines a beamforming matrix for communicating with the second device based on a first subset of the first set and a second subset of the second set.

Description

Technical Field

[0001] Embodiments of the present disclosure generally relate to the field of telecommunications, and more particularly to devices, methods, apparatuses, and computer-readable storage media for beamforming. Background Art

[0002] Multiple-Input Multiple-Output (MIMO) technology is considered a powerful scheme for achieving high data throughput in communication systems. MIMO refers to a type of wireless transmission and reception scheme in which both the transmitter and the receiver employ more than one antenna.

[0003] Massive MIMO is a MIMO system with a large number of antennas (e.g., larger than an 8×8 array). In addition, massive MIMO combined with beamforming can provide high spatial multiplexing gain and large beamforming gain, which is considered a key feature of fifth generation (5G) new radio (NR) to enhance system spectral efficiency. Sixth generation (6G) radio can provide even higher capacity to support a large number of users. Mid-band spectrum (e.g., 7 GHz to 20 GHz) will be combined with extremely massive MIMO antenna arrays at network equipment and larger antenna arrays at terminal devices to provide approximately 20 times the capacity compared to 5G.

[0004] In a massive MIMO system, a transmitter may use a beamforming matrix to perform related transmission or reception. However, currently, the amount of computation required to generate the beamforming matrix is ​​high. Summary of the invention

[0005] Example embodiments of the present disclosure provide a solution for beamforming.

[0006] In a first aspect, a first device is provided. The first device includes: at least one processor; at least one memory including computer program code. The at least one memory and the computer program code are configured to, together with the at least one processor, enable the first device to: continuously transform an initial horizontal beam vector by a horizontal channel covariance matrix to determine a first set of candidate horizontal beams; continuously transform an initial vertical beam vector by a vertical channel covariance matrix to determine a second set of candidate vertical beams; and determine a beamforming matrix for communicating with a second device based on a first subset of the first set and a second subset of the second set.

[0007] In a second aspect, a method is provided. The method includes: at a first device, continuously transforming an initial horizontal beam vector by a horizontal channel covariance matrix to determine a first set of candidate horizontal beams; continuously transforming the initial vertical beam vector by a vertical channel covariance matrix to determine a second set of candidate vertical beams; and determining a beamforming matrix for communicating with a second device based on a first subset of the first set and a second subset of the second set.

[0008] In a third aspect, an apparatus is provided. The apparatus includes: a component for determining a first set of candidate horizontal beams by continuously transforming an initial horizontal beam vector by a horizontal channel covariance matrix at a first device; a component for determining a second set of candidate vertical beams by continuously transforming an initial vertical beam vector by a vertical channel covariance matrix; and a component for determining a beamforming matrix for communicating with a second device based on a first subset of the first set and a second subset of the second set.

[0009] In a fourth aspect, a computer readable medium is provided, wherein the non-transitory computer readable medium comprises program instructions for causing a device to execute the method according to the second aspect.

[0010] It should be understood that the invention summary is not intended to necessarily identify the key or essential features of the embodiments of the present disclosure, nor is it intended to be used to limit the scope of the present disclosure. Other features of the present disclosure will become readily understood through the following description. BRIEF DESCRIPTION OF THE DRAWINGS

[0011] Some example implementations will now be described with reference to the accompanying drawings, in which:

[0012] Figure 1 illustrates an example distribution of antenna elements in a uniform planar array with cross-polarization according to some example implementations of the present disclosure;

[0013] Figure 2 The figure shows the signaling flow of the independent eigenbeamforming (I-EBF) process;

[0014] Figure 3 illustrates an example communication environment in which embodiments of the present disclosure may be implemented;

[0015] Figure 4 illustrates a flow chart of an example method implemented at a first device according to some example embodiments of the present disclosure;

[0016] Figure 5 illustrates a block diagram of a clustering module based on machine learning (ML) according to some example embodiments of the present disclosure;

[0017] Figure 6 , 7 and 8 illustrate signaling diagrams illustrating a process for determining initial horizontal and vertical beam vectors, respectively;

[0018] Fig. 9 A frame structure is illustrated to illustrate an example implementation of a beamforming process according to some example implementations of the present disclosure;

[0019] Fig. 10A and 10BThe spectral efficiency performance of various schemes for beamforming are respectively illustrated;

[0020] Fig.11A , 11B and 11C illustrate the computational complexity of different schemes using matrices of different sizes, respectively;

[0021] Fig.12 illustrates a simplified block diagram of an apparatus suitable for implementing an example implementation of the present disclosure; and

[0022] Fig.13 A block diagram of an example computer-readable medium according to an example implementation of the present disclosure is illustrated.

[0023] Throughout the drawings, the same or similar reference numerals refer to the same or similar elements unless otherwise specified. DETAILED DESCRIPTION

[0024] The principle of the present disclosure will now be described with reference to some example implementations. It should be understood that these implementations are described only to illustrate and help those skilled in the art understand and implement the present disclosure, and do not imply any limitation on the scope of the present disclosure. The disclosure described herein can be implemented in various other ways except the way described below.

[0025] In the following description and claims, unless defined otherwise, all technical and scientific terms used herein have the same meaning as commonly understood by one of ordinary skill in the art to which this disclosure belongs.

[0026] In this disclosure, references to "one embodiment," "an embodiment," and "an example embodiment" indicate that the described embodiment may include a particular feature, structure, or characteristic, but not every embodiment must include the particular feature, structure, or characteristic. Furthermore, such phrases do not necessarily refer to the same embodiment. Furthermore, when a particular feature, structure, or characteristic is described in conjunction with an example embodiment, those skilled in the art recognize that it is within the knowledge of those skilled in the art to affect such feature, structure, or characteristic in conjunction with other embodiments, whether or not explicitly described.

[0027] It should be understood that although the terms "first" and "second" etc. can be used to describe various elements in this article, these elements should not be limited by these terms. These terms are only used to distinguish one element from another element. For example, without departing from the scope of the example implementation, the first element can be referred to as the second element, and similarly, the second element can be referred to as the first element. As used herein, the term "and / or" includes any and all combinations of one or more of the listed terms.

[0028] The terms used herein are only used to describe specific implementations and are not intended to limit example implementations. The singular forms "a", "an", and "the" used herein also include the plural forms, unless the context clearly indicates otherwise. It will be further understood that the terms "include", "comprise", "include", "have", "have", "contain", and / or "comprises" when used herein specify the presence of the features, elements, and / or components, etc., but do not exclude the presence or addition of one or more other features, elements, components, and / or combinations thereof.

[0029] As used in this application, the term "circuitry" may refer to one, more, or all of the following:

[0030] (a) a pure hardware circuit implementation (such as an implementation using only analog and / or digital circuitry), and

[0031] (b) a combination of hardware circuitry and software such as (where applicable):

[0032] (i) a combination of analog and / or digital hardware circuits and software / firmware, and

[0033] (ii) any portion of hardware processor(s) (including digital signal processor(s)) with software, software and memory(s) that work together to enable a device (such as a mobile phone or server) to perform various functions),

[0034] as well as

[0035] (c) Hardware circuit(s) and / or processor(s), such as microprocessor(s) or portion(s) of microprocessor(s), that require software (e.g., firmware) to operate, but which may not be present when the software is not required for operation.

[0036] This definition of circuitry applies to all uses of the term in this application, including in any claims. As another example, as used in this application, the term circuitry also covers an implementation of only a hardware circuit or processor (or multiple processors) or a portion of a hardware circuit or processor and its accompanying software and / or firmware. For example, if applicable to a particular claim element, the term circuitry also covers a baseband integrated circuit or processor integrated circuit for a mobile device, or a similar integrated circuit in a server, cellular network device, or other computing or network device.

[0037] As used herein, the term "communication network" refers to a network that complies with any suitable communication standard, such as but not limited to the fifth generation (5G) system, long term evolution (LTE), advanced LTE (LTE-A), wideband code division multiple access (WCDMA), high speed packet access (HSPA), narrowband Internet of Things (NB-IoT), WiFi, etc. In addition, the communication between the terminal device and the network device in the communication network can be performed according to any suitable generation of communication protocols, including but not limited to the first generation (1G), second generation (2G), 2.5G, 2.75G, third generation (3G), fourth generation (4G), 4.5G, fifth generation (5G) new radio (NR) communication protocol, and / or any other protocol currently known or to be developed in the future. The embodiments of the present disclosure can be applied to various communication systems. In view of the rapid development of communication, there will certainly be future types of communication technologies and systems that can be used to embody the present disclosure. It should not be regarded as limiting the scope of the present disclosure to the above-mentioned systems.

[0038] As used herein, the term "network device" refers to a node in a communication network, via which a terminal device accesses the network and receives services from the network. Depending on the terminology and technology applied, a network device may refer to a base station (BS) or an access point (AP), for example, a Node B (Node B or NB), an evolved Node B (eNodeB or eNB), an NRNB (also known as a gNB), a remote radio unit (RRU), a radio head (RH), a remote radio head (RRH), a relay, a low-power node (such as a femto, a pico). The RAN split architecture includes a gNB-CU (centralized unit, hosting RRC, SDAP, and PDCP) that controls multiple gNB-DUs (distributed units, hosting RLC, MAC, and PHY). A relay node may correspond to the DU portion of an IAB node.

[0039] The term "terminal device" refers to any terminal device capable of wireless communication. As an example and not limitation, the terminal device may also be referred to as a communication device, a user equipment (UE), a subscriber station (SS), a portable subscriber station, a mobile station (MS) or an access terminal (AT). The terminal device may include, but is not limited to, a mobile phone, a cellular phone, a smart phone, a voice over IP (VoIP) phone, a wireless local loop phone, a tablet computer, a wearable terminal device, a personal digital assistant (PDA), a portable computer, a desktop computer, an image capture terminal device (such as a digital camera), a game terminal device, a music storage and playback device, a vehicle-mounted wireless terminal device, a wireless endpoint, a mobile station, a laptop embedded device (LEE), a laptop mounted device (LME), a USB dongle, a smart device, a wireless customer premises equipment (CPE), an Internet of Things (IoT) device, a watch or other wearable device, a head mounted display (HMD), a vehicle, a drone, medical equipment and applications (e.g., remote surgery), industrial equipment and applications (e.g., robots and / or other wireless devices operating in industrial and / or automated processing chain environments), consumer electronic devices, equipment operating on commercial and / or industrial wireless networks, etc. The terminal device may also correspond to the mobile terminal (MT) part of an integrated access and backhaul (IAB) node (also known as a relay node). In the following description, the terms "terminal device", "communication device", "terminal", "user equipment", and "UE" may be used interchangeably.

[0040] Network equipment may be configured with extremely massive MIMO antenna arrays. Figure 1 1 illustrates an example distribution of antenna elements in a uniform planar array 100 with cross-polarization for a network device according to some example implementations of the present disclosure. Figure 1 As shown in FIG. 1 , the uniform planar array 100 includes N h antenna elements and N in the vertical domain v antenna elements. For example, N h can be equal to 8, and N v Can be equal to 4.

[0041] As described above, the transmitter of the network device can use the beamforming matrix to perform related transmission or reception. However, the current calculation amount for generating the beamforming matrix is ​​very high. This will refer to Figure 2 Give a description.

[0042] Figure 2 FIG. 2 shows a signaling diagram illustrating a process 200 of an I-EBF process. Figure 2As shown in , the UE sends 210SRS to the gNB, and the gNB performs 120I-EBF process based on the received SRS. Specifically, the gNB determines the horizontal channel covariance matrix and the vertical channel covariance matrix based on the received SRS, respectively. Then, the gNB obtains horizontal and vertical independent eigenbeams by applying eigenvalue decomposition (EVD) to the horizontal channel covariance matrix and the vertical channel covariance matrix, respectively. The gNB constructs a full eigenbeam by selecting and combining independent eigenbeams.

[0043] The implementation of the I-EBF process may have some limitations. For example, the I-EBF process can only be based on the uplink SRS. In addition, the I-EBF process based on the iterative power method can outperform the pure EVD implementation, but the computational complexity is still high due to the iteration and orthogonalization process.

[0044] In order to solve the above and other potential problems, an embodiment of the present disclosure provides a solution for beamforming. In this solution, a first device determines a first set of candidate horizontal beams by continuously transforming an initial horizontal beam vector through a horizontal channel covariance matrix, and determines a second set of candidate vertical beams by continuously transforming an initial vertical beam vector through a vertical channel covariance matrix. Furthermore, the first device determines a beamforming matrix for communicating with a second device based on a first subset of the first set and a second subset of the second set. In this way, a beamforming process with lower computational complexity is achieved.

[0045] Some exemplary embodiments of the present disclosure will now be described in detail with reference to the accompanying drawings. However, those skilled in the art will readily appreciate that the detailed description given herein with respect to these drawings is for illustrative purposes, as the present disclosure extends beyond these limited embodiments.

[0046] Figure 3 An example communication environment 300 is illustrated in which example embodiments of the present disclosure may be implemented. In the communication environment 300, a first device 310 may communicate with a second device 320 via a physical communication channel or link. In addition, the first device 310 may communicate with the second device 320 via different beams to enable directional communication. Figure 3 In the example of , beams 330 - 1 to 330 - 3 are illustrated by way of example. In addition, although not shown, the second device 320 also supports communication with the first device 310 using a plurality of beams.

[0047] In this example, the first device 310 is illustrated as a gNB, and the second device 320 is illustrated as a UE. In the following, some embodiments will be described by taking the gNB and the UE as examples. However, in other embodiments, the first device 310 may be implemented as a device other than the gNB. For example, the first device 310 may be implemented as a relay, an AP, or an RRH. In other embodiments, the second device 320 may be implemented as a device other than the UE. For example, the second device 320 may be implemented as a station, a tablet, or a wearable device.

[0048] In an embodiment where the first device 310 is implemented as a gNB, the service area of ​​the first device 310 is referred to as a cell 312. It should be understood that the number of gNBs and UEs is for illustration only and does not imply any limitation. The environment 300 may include any suitable number of gNBs and UEs suitable for implementing embodiments of the present disclosure. Although not shown, it should be understood that one or more UEs may be located in the cell 312 and served by the first device 310.

[0049] In this example, the link from the second device 320 to the first device 310 is referred to as an uplink (UL), and the link from the first device 310 to the second device 320 is referred to as a downlink (DL). In the DL, the first device 310 is a transmitting (TX) device (or transmitter), and the second device 320 is a receiving (RX) device (or receiver). The first device 310 can send a DL transmission to the second device 320 via one or more beams. Figure 3 As shown, the first device 310 can send a DL transmission to the second device 320 via beams 330-1 to 330-3. In the UL, the first device 310 is an RX device (or receiver) and the second device 320 is a TX device (or transmitter).

[0050] Communications in environment 300 may conform to any suitable standard, including but not limited to Long Term Evolution (LTE), LTE Evolution, Advanced LTE (LTE-A), Wideband Code Division Multiple Access (WCDMA), Code Division Multiple Access (CDMA), and Global System for Mobile Communications (GSM). In addition, communications may be performed according to any generation of communications protocols currently known or to be developed in the future. Examples of communications protocols include but are not limited to first generation (1G), second generation (2G), 2.5G, 2.75G, third generation (3G), fourth generation (4G), 4.5G, 5G, and 6G communications protocols.

[0051] It should be understood that the number of connections of the first device, the second device, the beam, and the cell is only for illustration and does not imply any limitation. The communication environment 300 may include any suitable number of first devices, second devices, beams, and cells suitable for implementing the embodiments of the present disclosure. Although not shown, it should be understood that one or more additional first devices and second devices may be located in the corresponding cells. It should also be understood that in some examples, only homogeneous network deployments or only heterogeneous network deployments may be included in the environment 300.

[0052] Figure 4 A flowchart of an example method 400 implemented at a first device according to some example embodiments of the present disclosure is illustrated. For ease of discussion, reference will be made to Figure 3 The method 400 is described from the perspective of the first device 310. It should be understood that the method 300 may also be implemented in Figure 1 is implemented at the second device 320 in .

[0053] At block 410, the first device 310 determines a first set of candidate horizontal beams by continuously transforming an initial horizontal beam vector by a horizontal channel covariance matrix.

[0054] At block 420, the first device 310 continuously transforms the initial vertical beam vector by a vertical channel covariance matrix to determine a second set of candidate vertical beams.

[0055] At block 430 , the first device 310 determines a beamforming matrix for communicating with the second device 320 based on the first subset of the first set and the second subset of the second set.

[0056] Through the method 400 , a beamforming process with lower computational complexity can be implemented.

[0057] For illustration, Table 1 shows an algorithmic implementation of the beamforming process according to some example embodiments of the present disclosure.

[0058] Table 1

[0059]

[0060] In Table 1, a v represents the initial vertical beam vector, a h represents the initial horizontal beam vector, R v represents the vertical channel covariance matrix, R h represents the horizontal channel covariance matrix, W D，v represents the second set of candidate vertical beams, W D，h represents the first set of candidate horizontal beams, w v，j represents the candidate vertical beams in the second subset, w h，irepresents the candidate horizontal beams in the first subset, and w n represents the beamforming vector in the beamforming matrix.

[0061] In some embodiments, after determining the beamforming matrix, the first device 310 may transmit a reference signal (RS) or data to the second device 320 by using the beamforming matrix. For example, the first device 310 may process the RS or data using the beamforming matrix and transmit the processed RS or processed data to the second device 320.

[0062] Alternatively, when determining the beamforming matrix, the first device 310 may process the RS or data received from the second device 320 by using the beamforming matrix to improve a success rate of decoding the received RS or data.

[0063] Triggering of the beamforming process of the present disclosure

[0064] In some embodiments, the beamforming process of the present disclosure may be referred to as a first beamforming process. Figure 4 , 6 Any beamforming process described in , 7 and 8 may be referred to as a first beamforming process.

[0065] In some embodiments, to determine whether to apply the first beamforming process to the second device 320, the first device 310 may determine a first association between uplink channel information previously received from the third plurality of devices and a predetermined beamforming process to be applied to the third plurality of devices. The predetermined beamforming process includes the first beamforming process.

[0066] For example, the first device 310 may apply a machine learning (ML) algorithm to cluster a third plurality of devices (e.g., UEs) in a dynamic and low-complexity manner. When the second device 320 requests initial access to the first device 310, the first device 310 may determine a first beamforming process among predetermined beamforming processes to be applied to the second device 320 based on the first association and uplink channel information received from the second device 320, rather than recalculating new metrics for all UEs. Furthermore, the first device 310 may determine at least one of a first set of candidate horizontal beams and a second set of candidate vertical beams by performing the first beamforming process. This will refer to Figure 5 Give a description.

[0067] Figure 5 FIG. 5 shows a block diagram of an ML-based clustering module 500. Figure 5As shown in , the first device 310 can apply the ML-based clustering module 500. During the training of the ML-based clustering module 500, the input of the ML-based clustering module 500 is the uplink channel information received from the plurality of UEs, and the output of the ML-based clustering module 500 is the UE label. Each UE label is associated with one of the predetermined beamforming processes. The ML-based clustering module 500 can be trained according to a loss function that minimizes the total square error of all clusters.

[0068] After training or UE marking, the first device 310 selects a serving UE (such as a 5G or 6G UE, a high data rate required) to implement the first beamforming process. When the second device 320 requests initial access, the first device 310 can apply the ML-based clustering module 500 to dynamically cluster the second device 320 without recalculating and re-clustering all existing UEs, which reduces complexity and latency.

[0069] Determination of initial horizontal and vertical beam vectors

[0070] Figure 6 A signaling diagram of a process 600 for determining initial horizontal and vertical beam vectors is illustrated. Figure 3 The process 600 is described with reference to the communication environment 300 of FIG. 6. However, the process can also be applied to other communication situations.

[0071] like Figure 6 As shown in , the first device 310 receives 610 RS from the second device 320. For example, the RS may include a sounding reference signal (SRS). The SRS may be periodically sent or triggered based on channel quality.

[0072] Accordingly, the first device 310 determines 620 a horizontal channel covariance matrix based on the received RS. In addition, the first device 310 determines 622 an initial horizontal beam vector based on the received RS. Then, the first device 624 determines a first set of candidate horizontal beams by continuously transforming the initial horizontal beam vector through the horizontal channel covariance matrix.

[0073] On the other hand, the first device 310 determines 630 a vertical channel covariance matrix based on the received RS. In addition, the first device 310 determines 632 an initial vertical beam vector based on the received RS. Then, the first device 310 continuously transforms the initial vertical beam vector by the vertical channel covariance matrix to determine 634 a second set of candidate vertical beams.

[0074] The first device 310 then determines 640 a beamforming matrix for communicating with the second device 320 based on the first subset of the first set and the second subset of the second set.

[0075] Accordingly, the first device 310 processes the RS or the data using the beamforming matrix and transmits 650 the processed RS or the processed data to the second device 320 .

[0076] Because the process 600 does not require feedback from the second device 320, overhead will be reduced.

[0077] Figure 7 A signaling diagram illustrating a process 700 for determining initial horizontal and vertical beam vectors is illustrated. Figure 3 The process 700 is described with reference to the communication environment 300 of FIG. 700. However, the process can also be applied to other communication situations.

[0078] like Figure 7 As shown in , process 700 differs from process 600 in that initial horizontal and vertical beam vectors are determined based on beam feedback from the second device 320.

[0079] Specifically, the first device 310 performs 710 horizontal beam scanning and vertical beam scanning on the second device 320. The first device 310 may perform the horizontal beam scanning and the vertical beam scanning by transmitting a plurality of horizontal beams and a plurality of vertical beams to the second device 320, respectively.

[0080] The second device 320 may select an optimal horizontal beam from the plurality of horizontal beams as an initial horizontal beam, and select an optimal vertical beam from the plurality of vertical beams as an initial vertical beam. The second device 320 then sends 720 beam feedback to the first device 310. The beam feedback includes a first index of the initial horizontal beam vector and a second index of the initial vertical beam vector.

[0081] After receiving the first index of the initial horizontal beam vector and the second index of the initial vertical beam vector, the first device 310 determines the initial horizontal beam vector based on the first index at block 730 and determines the initial vertical beam vector based on the second index at block 740 .

[0082] The actions at blocks 610, 620, 624, 630, 634, 640, and 650 in process 700 are the same as the actions in process 600. Details of these actions are omitted for brevity.

[0083] Figure 8 A signaling diagram illustrating a process 800 for determining initial horizontal and vertical beam vectors is illustrated. Figure 3 The process 800 is described with reference to the communication environment 300 of FIG. 800. However, the process can also be applied to other communication situations.

[0084] like Figure 8As shown in , process 800 differs from process 700 in that an initial horizontal beam vector is determined based on beam feedback from the second device 320 , and an initial vertical beam vector is determined based on an SRS received from the second device 320 .

[0085] Specifically, the first device 310 performs 810 horizontal beam scanning to the second device 320. The first device 310 may perform the horizontal beam scanning by transmitting a plurality of horizontal beams to the second device 320.

[0086] The second device 320 may select an optimal horizontal beam from the plurality of horizontal beams as an initial horizontal beam. Then, the second device 320 sends 820 beam feedback to the first device 310. The beam feedback includes a first index of the initial horizontal beam vector.

[0087] After receiving the first index of the initial horizontal beam vector, the first device 310 determines the initial horizontal beam vector based on the first index at block 830 .

[0088] The actions at blocks 610, 620, 624, 630, 632, 634, 640, and 650 in process 800 are the same as the actions in process 600. Details of these actions are omitted for brevity.

[0089] Process 800 may balance performance and complexity.

[0090] In some embodiments, in order to determine the initial vertical beam vector, the first device 310 may perform vertical beam scanning on the second device 320. Accordingly, the first device 310 may receive a second index of the initial vertical beam vector from the second device 320. Then, the first device 310 may determine the initial vertical beam vector based on the second index. In such an embodiment, the first device 310 may determine the initial horizontal beam vector based on the SRS received from the second device 320.

[0091] In some embodiments, the first device 310 may select one of the processes 600 , 700 , and 800 to implement based on at least one of the following: subframe timing, computational complexity, RS resources, and performance requirements.

[0092] In process 700 or 800, beam scanning may be implemented through a synchronization signal block (SSB) in initial access or through an aperiodic channel state information reference signal (CSI-RS) process triggered based on channel quality.

[0093] It should be noted that the processes 600, 700 and 800 of the present disclosure differ from the process 200 for the I-EBF process in that not only the horizontal and vertical channel covariance matrices but also the initial horizontal and vertical beam vectors are required.

[0094] Furthermore, the processes 700 and 800 of the present disclosure differ from the process 200 of the I-EBF process in that beam feedback from the second device 320 is used to assist the beamforming process.

[0095] Determination of horizontal and vertical channel covariance matrices

[0096] As reference Figures 6 to 8 As described above, in some embodiments, the horizontal and vertical channel covariance matrices may be determined based on the SRS received from the second device 320. Figure 1 Details of the determination of the horizontal and vertical channel covariance matrices are described.

[0097] As mentioned above, Figure 1 An example distribution of antenna elements in a uniform planar array 100 with cross-polarization for a network device is illustrated. In some embodiments, the first device 310 may be configured with a uniform planar array 100 with cross-polarization.

[0098] We denote the channel vector for each PRB as Where N h 、N v and N pol Corresponding to the number of columns, rows and polarizations in the array 100, respectively. f The horizontal channel covariance matrix averaged over PRBs is given by:

[0099]

[0100] The vertical channel covariance matrix is ​​given by:

[0101]

[0102] in

[0103]

[0104] The long-term average of the channel covariance matrix with weighting factor α can be calculated as follows:

[0105]

[0106]

[0107] in represents the long-term average of the horizontal channel covariance matrix, and and represents the vertical channel covariance matrix long-term average.

[0108] In some embodiments, in process 600, the first device 310 may determine an initial horizontal beam vector based on:

[0109]

[0110] in represents the initial horizontal beam vector, and C h represents the codebook in the horizontal domain.

[0111] In process 600 or 800, the first device 310 may determine an initial vertical beam vector based on:

[0112]

[0113] in represents the initial vertical beam vector, and C h represents the codebook in the vertical domain.

[0114] In some embodiments, in order to further reduce computational complexity and improve estimation accuracy, the first device 310 may determine a second association between the RS previously received from the second device 320 and the horizontal channel covariance matrix and the vertical channel covariance matrix. The RS includes the first RS, instead of the regular average calculation and vector multiplication given by the above equations (1) to (4). In response to receiving the RS from the second device 320, the first device 310 may determine the horizontal channel covariance matrix and the vertical channel covariance matrix based on the second association and the first reference signal.

[0115] In such an embodiment, ML-based channel covariance calculation and prediction may be performed. The function of the ML module is joint channel estimation and covariance calculation / prediction. The input of the ML module may be SRS received from multiple UEs, and the output of the ML module may be the predicted horizontal and vertical channel covariance matrices (regression-type output).

[0116] Determination of a first set of candidate horizontal beams and a second set of candidate vertical beams

[0117] As reference Figure 4 As described above, the first device 310 determines a first set of candidate horizontal beams by continuously transforming the initial horizontal beam vectors through the horizontal channel covariance matrix. For example, for simplicity, we respectively transform the initial horizontal beam vectors and the horizontal channel covariance matrix Represented as a h and R h Then, the first set of candidate horizontal beams can be expressed as:

[0118]

[0119] where r h Index representing the power of the horizontal channel covariance matrix.

[0120] In addition, the first device 310 continuously transforms the initial vertical beam vector by the vertical channel covariance matrix to determine a second set of candidate vertical beams. and the vertical channel covariance matrix Represented as a v and R v Then, the second set of candidate vertical beams can be expressed as:

[0121]

[0122] where r v The index representing the power of the vertical channel covariance matrix.

[0123] In some embodiments, the first device 310 may determine a first set of candidate horizontal beams by determining an index of the power of the horizontal channel covariance matrix to be zero and performing the following a predetermined number of times: determining the product of the power of the horizontal channel covariance matrix and the initial horizontal beam vector; including the product into the first set of candidate horizontal beams; and increasing the power index by 1. In some embodiments, the first device 310 may determine a second set of candidate vertical beams in a similar manner.

[0124] In some embodiments, the predetermined number is equal to or greater than the number of beamforming vectors in the beamforming matrix.

[0125] Determination of the first subset and the second subset

[0126] In some embodiments, the first device 310 may determine a first subset of the first set of candidate horizontal beams by selecting a first number of candidate horizontal beams from the first set. A power index of the first number of candidate horizontal beams is greater than a threshold.

[0127] In some embodiments, a parallel beam selection method may be applied. According to the parallel beam selection method, the first device 310 may be configured to: A first number of candidate horizontal beams are selected from a first set with higher power indices, where D≤min{r v , r h} represents the number of beamforming vectors required for each polarization, Represents the first subset.

[0128] Consider the first set W h An example of six candidate horizontal beams is included, namely In this example, the threshold is equal to 1 and the first number is equal to 4. The first device 310 can select from the first set W h Select candidate horizontal beams The power indices of the four selected candidate horizontal beams are 2, 3, 4 and 5, respectively, which are greater than the threshold 1.

[0129] In some embodiments, the first device 310 may determine a second subset of the second set of candidate vertical beams in a similar manner. For example, the first device 310 may determine a second subset of the second set of candidate vertical beams by, for example, A first number of candidate vertical beams are selected from the second set with higher power indices, where D≤min{r v , r h} denotes the required number of beamforming vectors for each polarization, and represents the second subset.

[0130] In other embodiments, a cross-beam selection method may be applied. According to the cross-beam selection method, the first device 310 may select a first number D from the first set having a higher power index. h , 1≤D h ≤r h and select a second number D from the second set with a higher power index v , 1≤D v ≤r v Candidate vertical beams, where D h ≠D v For example, the first set W h There are six candidate horizontal beams, namely The first quantity D h =4, which indicates that the first device 310 can select from the first set W h Select candidate horizontal beams The second set W v There are three candidate horizontal beams, namely The second quantity D v =1, which indicates that the first device 310 can select from the second set W v Select a candidate vertical beam from

[0131] It should be understood that other beam selection methods are possible.

[0132] In some embodiments, after determining the first and second subsets, the first device 310 may determine the beamforming vector by the Kronecker product of the first subset and the second subset. For example, the first device 310 may determine the beamforming vector based on the following items:

[0133]

[0134] or

[0135]

[0136] Accordingly, the first device 310 may determine the first beamforming matrix based on the beamforming vector. For example, the first device 310 may determine the first beamforming matrix based on the following items:

[0137]

[0138] in represents the first beamforming matrix.

[0139] In some embodiments, the first device 310 can be configured to perform To determine the final beamforming matrix W D For example, the Gram-Schmidt orthogonalization procedure may be used.

[0140] Fig. 9 The frame architecture is illustrated to illustrate an example implementation of the beamforming process according to some example implementations of the present disclosure. Figure 3 The example implementations are described with reference to the communication environment 300 of FIG. However, the example implementations can be equally applied to other communication scenarios.

[0141] In initial access, the process 700 may be considered to be performed. The first device 310 performs beam scanning in the horizontal and vertical dimensions via SSB (block 710), and the second device 320 measures the received signal quality and feeds back the index of its best horizontal and vertical beams (i.e., initial horizontal and vertical beam vectors) to the first device 310 (block 720). The first device 310 receives the initial horizontal vector and vertical beam vector , and determine initial horizontal and vertical beam vectors based on the index (blocks 730 and 740).

[0142] At the same time, the first device 310 determines the horizontal channel covariance matrix R based on the received SRS h and the vertical channel covariance matrix R v (Blocks 620 and 630). Initial horizontal beam vector and vertical beam vector And the channel covariance matrix R h and R v is used to determine the beamforming matrix. RS or data can then be sent via the beamforming matrix.

[0143] Due to time aging, the first device 310 needs to update the beam. In this case, the process 600 and the process 800 can be applied. For example, in the middle stage of the frame illustration (process 600), the first device 310 can trigger an additional SRS so that the initial horizontal beam vector and the vertical beam vector and the channel covariance matrix can be updated. As a result, the first device 310 determines the updated initial horizontal beam vector and vertical beam vector and the updated channel covariance matrix R h and R v .

[0144] A recalculation of the beamforming matrix may be performed for the next RS or data transmission. In the event that additional beam scanning is required for CSI update, the first device 310 may use a horizontal and / or vertical beam scanning process to trigger the CSI-RS. Fig. 9 In stage 3 (implementation of process 800), only horizontal beam scanning is considered as an example. The initial vertical beam vector is updated from the uplink SRS. Similarly, the recalculation of the beamforming matrix is ​​also implemented for new RS or data transmission.

[0145] Simulation Results

[0146] We evaluate the performance of the beamforming process according to some example implementations of the present disclosure and compare it with different standard approaches, considering zero-forcing precoding for all cases. Fig. 10A and 10B The spectral efficiency performance of various schemes for beamforming is illustrated. Fig. 10A For Uma case, Fig. 10B For Umi situations. Fig. 10A and 10B In the example above, SNR=10dB.

[0147] As shown, the "best EBF" is an upper bound solution that uses a standard full version of EVD with power iterations, namely the full Gram-Schmidt eigenvalue decomposition (full GSEVD), to directly compute the full eigenbeams, which are shown by 1010, 1020, 1030, 1040, 1050, 1060, 1070, and 1080. A horizontal-vertical EBF "I-EBF" is also considered, which is shown by 1012, 1022, 1032, 1042, 1052, 1062, 1072, and 1082. For the full EBF and I-EBF, an iteration number of 4 is selected. "I-KSB" refers to the beamforming process implemented according to some examples of the present disclosure, which is shown by 1014, 1024, 1034, 1044, 1054, 1064, 1074, and 1084. In “I-KSB”, the initial horizontal and vertical beam vectors are obtained from the DFT codebook with an oversampling factor of 4 by equations (5) and (6). The channel parameters used as well as the array geometry are listed in Table 2.

[0148] Table 2

[0149]

[0150] from Fig. 10A and 10B It can be observed that in both Uma and Umi cases, the proposed horizontal-vertical beamforming algorithm (I-KSB) performs close to the full EBF solution (less than 2% loss) and has almost the same performance as I-EBF, with only ~1% performance loss at the geometric mean, and may outperform I-EBF at the cell edge.

[0151] Computational complexity analysis

[0152] The computational complexity of the beamforming process implemented according to some examples of the present disclosure is compared with the computational complexity of the horizontal-vertical EBF counterpart.

[0153] The computational complexity of the subspace method proposed in this disclosure comes from the construction and orthogonalization of the beamforming matrix in equation (1). The computational complexity refers to the number of complex multiplications, while the number of complex additions is negligible and is therefore ignored. We denote the number of beamforming vectors for horizontal and vertical as r h , r v , the matrix dimension is expressed as N = N h N v , and denote the number of iterations for power-iterative-based EVD as J.

[0154] Table 3 shows the computational complexity of two different schemes.

[0155] Table 3

[0156]

[0157] Fig.11A The computational complexity of different schemes for the above simulation setup is illustrated.

[0158] Fig. 11B and 11C The computational complexity of different schemes using matrices of different sizes is shown in the figure. Fig. 11B In , array sizes of (8×16), (16×32), and (32×32) (more squares) are used. Fig. 11C In , array sizes of (4×32), (8×64), and (16×64) (higher aspect ratio) are used. Fig. 11B and 11C In , the computational complexity curves are shown as a function of the number of full beamforming vectors, where the number of EVD iterations is fixed to 4. It can be observed that I-KSB has only <50% of the complexity compared to I-EBF. Fig. 11B and 11C For larger arrays shown, I-KSB is more beneficial for arrays with higher aspect ratios, where a 20% to 50% complexity reduction can be achieved with I-KSB.

[0159] Therefore, it can be concluded that the proposed beamforming algorithm has similar performance to I-EBF with approximately 1% performance loss while having a much lower implementation complexity (i.e., approximately 50% complexity reduction) compared to the low-complexity EBF variant.

[0160] In some example implementations, a device (e.g., first device 310) capable of performing any of method 400 may include components for performing the various steps of method 400. The device may be implemented in any suitable form. For example, the device may be implemented in a circuit system or a software module.

[0161] In some example implementations, the apparatus includes: means for determining, at a first device, a first set of candidate horizontal beams by continuously transforming an initial horizontal beam vector with a horizontal channel covariance matrix; means for determining a second set of candidate vertical beams by continuously transforming the initial vertical beam vector with a vertical channel covariance matrix; and means for determining a beamforming matrix for communicating with a second device based on a first subset of the first set and a second subset of the second set.

[0162] In some example implementations, the apparatus further includes: means for receiving a reference signal from the second device; and means for determining an initial horizontal beam vector and an initial vertical beam vector based on the reference signal.

[0163] In some example implementations, the apparatus further includes: a component for determining an initial horizontal beam vector and an initial vertical beam vector by: performing horizontal beam scanning and vertical beam scanning on a second device; receiving a first index of the initial horizontal beam vector and a second index of the initial vertical beam vector from the second device; and determining the initial horizontal beam vector and the initial vertical beam vector based on the first index and the second index, respectively.

[0164] In some example implementations, the apparatus further includes: a component for determining an initial horizontal beam vector by: performing a horizontal beam scan on a second device; receiving a first index of the initial horizontal beam vector from the second device; determining the initial horizontal beam vector based on the first index; and a component for determining an initial vertical beam vector by: receiving a reference signal from the second device; and determining the initial vertical beam vector based on the reference signal.

[0165] In some example implementations, the apparatus further includes: a component for determining an initial vertical beam vector by: performing a vertical beam scan on a second device; receiving a second index of the initial vertical beam vector from the second device; determining the initial vertical beam vector based on the second index; and a component for determining an initial horizontal beam vector by: receiving a reference signal from the second device; and determining the initial horizontal beam vector based on the reference signal.

[0166] In some example implementations, the means for determining the first set of candidate horizontal beams includes: means for determining an index of a power of a horizontal channel covariance matrix to be zero; and means for performing the following a predetermined number of times: determining a product of the power of the horizontal channel covariance matrix and an initial horizontal beam vector; including the product into the first set of candidate horizontal beams; and increasing the index of the power by 1. In such example implementations, the apparatus further includes means for determining a first subset of the first set of candidate horizontal beams by: selecting a first number of candidate horizontal beams from the first set, the index of the power of the first number of candidate horizontal beams being greater than a threshold.

[0167] In some example implementations, the predetermined number is equal to or greater than the number of beamforming vectors in the beamforming matrix.

[0168] In some example implementations, components for determining at least one of a first set of candidate horizontal beams and a second set of candidate vertical beams include: components for determining a first association between uplink channel information previously received from a third plurality of devices and a predetermined beamforming process to be applied to the third plurality of devices; components for determining a first beamforming process to be used in the predetermined beamforming process for the second device based on the first association and the uplink channel information received from the second device; and components for determining at least one of the first set of candidate horizontal beams and the second set of candidate vertical beams by performing the first beamforming process.

[0169] In some example implementations, the apparatus further includes: a component for determining a second association between a reference signal previously received from a second device and the horizontal channel covariance matrix and the vertical channel covariance matrix; a component for receiving a first reference signal from the second device, the reference signal including the first reference signal; and a component for determining the horizontal channel covariance matrix and the vertical channel covariance matrix based on the second association and the first reference signal.

[0170] Fig.12 1 is a simplified block diagram of a device 1200 suitable for implementing embodiments of the present disclosure. The device 1200 may be provided to implement a communication device, such as Figure 3 The first device 310 or the second device 320 is shown. As shown in the figure, the device 1200 includes one or more processors 1210, one or more memories 1220 coupled to the processors 1210, and one or more communication modules 1240 coupled to the processors 1210.

[0171] The communication module 1240 is used for two-way communication. The communication module 1240 has at least one antenna to facilitate communication. The communication interface may represent any interface required for communication with other network elements.

[0172] Processor 1210 may be of any type suitable for the local technology network and may include one or more of the following: as non-limiting examples, a general purpose computer, a special purpose computer, a microprocessor, a digital signal processor (DSP), and a processor based on a multi-core processor architecture. Device 1200 may have multiple processors, such as application specific integrated circuit chips that are time slaved to a clock that synchronizes a main processor.

[0173] The memory 1220 may include one or more non-volatile memories and one or more volatile memories. Examples of non-volatile memories include, but are not limited to, read-only memory (ROM) 1224, electrically programmable read-only memory (EPROM), flash memory, hard disk, compact disk (CD), digital video disk (DVD), and other magnetic and / or optical memories. Examples of volatile memories include, but are not limited to, random access memory (RAM) 1222 and other volatile memories that do not persist during the duration of a power outage.

[0174] Computer program 1230 includes computer executable instructions executed by associated processor 1210. Program 1230 may be stored in ROM 1224. Processor 1210 may perform any suitable actions and processes by loading program 1230 into RAM 1222.

[0175] The embodiments of the present disclosure may be implemented by the program 1230 so that the device 1200 may execute the following steps: Figure 1 to 1 1. The embodiments of the present disclosure may also be implemented by hardware or a combination of software and hardware.

[0176] In some example embodiments, the program 1230 may be tangibly embodied in a computer-readable medium, which may be included in the device 1200 (e.g., in the memory 1220) or in other storage devices accessible by the device 1200. The device 1200 may load the program 1230 from the computer-readable medium to the RAM 1222 for execution. The computer-readable medium may include any type of tangible non-volatile memory, such as ROM, EPROM, flash memory, hard disk, CD, DVD, etc. Fig.13 An example of a computer readable medium 1300 in the form of a CD or DVD is shown. The computer readable medium has a program 1230 stored thereon.

[0177] Generally, various embodiments of the present disclosure may be implemented using hardware or dedicated circuits, software, logic, or any combination thereof. Some aspects may be implemented using hardware, while other aspects may be implemented using firmware or software that may be executed by a controller, microprocessor, or other computing device. Although various aspects of the embodiments of the present disclosure are illustrated and described as block diagrams, flow charts, or using some other graphical representations, it should be understood that, as non-limiting examples, the blocks, devices, systems, techniques, or methods described herein may be implemented using hardware, software, firmware, dedicated circuits or logic, general-purpose hardware or controllers or other computing devices, or some combination thereof.

[0178] The present disclosure also provides at least one computer program product tangibly stored on a non-transitory computer-readable storage medium. The computer program product includes computer executable instructions, such as instructions included in a program module, which are executed in a device on a target real or virtual processor to perform the above referenced Figure 2-Figure 6 The method described. Typically, program modules include routines, programs, libraries, objects, classes, components, data structures, etc. that perform specific tasks or implement specific abstract data types. In various embodiments, the functions of program modules can be combined or split between program modules as needed. The machine executable instructions of program modules can be executed in local or distributed devices. In distributed devices, program modules can be located in both local and remote storage media.

[0179] The program code for executing the method of the present disclosure can be written in any combination of one or more programming languages. These program codes can be provided to a processor or controller of a general-purpose computer, a special-purpose computer or other programmable data processing device so that the program code is implemented when executed by the processor or controller in the flow chart and / or the block diagram. The program code can be executed completely on the machine, partially on the machine, as an independent software package, partially on the machine and partially on a remote machine, or completely on a remote machine or server.

[0180] In the context of the present disclosure, computer program codes or related data may be carried by any suitable carrier to enable a device, apparatus or processor to perform various processes and operations as described above. Examples of carriers include signals, computer readable media, etc.

[0181] The computer readable medium can be a computer readable signal medium or a computer readable storage medium. The computer readable medium can include, but is not limited to, electronic, magnetic, optical, electromagnetic, infrared or semiconductor systems, devices or equipment, or any suitable combination of the foregoing. A more specific example of a computer readable storage medium will include an electrical connection with one or more wires, a portable computer floppy disk, a hard disk, a random access memory (RAM), a read-only memory (ROM), an erasable programmable read-only memory (EPROM or flash memory), an optical fiber, a portable compact disk read-only memory (CD-ROM), an optical storage device, a magnetic storage device, or any suitable combination of the foregoing.

[0182] In addition, although the operations are described in a particular order, this should not be understood as requiring such operations to be performed in the particular order shown or in order or performing all the operations shown to obtain the desired result. In some cases, multitasking and parallel processing may be advantageous. Similarly, although several specific implementation details are included in the above discussion, these should not be interpreted as limitations on the scope of the present disclosure, but rather descriptions of features that may be specific to a particular embodiment. Certain features described in the context of a separate embodiment may also be implemented in combination in a single embodiment. On the contrary, the various features described in the context of a single embodiment may also be implemented in multiple embodiments individually or in any suitable sub-combination.

[0183] Although the present disclosure has been described in language specific to structural features and / or methodological acts, it should be understood that the present disclosure defined in the appended claims is not necessarily limited to the specific features or acts described above. Instead, the specific features and acts described above are disclosed as example forms of implementing the claims.

Claims

1. A first device, comprising: at least one processor; as well as at least one memory including computer program code; wherein the at least one memory and the computer program code are configured to, together with the at least one processor, cause the first device to: Continuously transforming the initial horizontal beam vector by a horizontal channel covariance matrix to determine a first set of candidate horizontal beams; continuously transforming the initial vertical beam vector by a vertical channel covariance matrix to determine a second set of candidate vertical beams; as well as Based on a first subset of the first set and a second subset of the second set, a beamforming matrix for communicating with a second device is determined.

2. The first device according to claim 1, wherein the first device is further configured to: receiving a reference signal from the second device; and Based on the reference signal, the initial horizontal beam vector and the initial vertical beam vector are determined.

3. The first device of claim 1 , wherein the first device is further configured to: determine the initial horizontal beam vector and the initial vertical beam vector by: performing horizontal beam scanning and vertical beam scanning on the second device; receiving, from the second device, a first index of the initial horizontal beam vector and a second index of the initial vertical beam vector; and The initial horizontal beam vector and the initial vertical beam vector are determined based on the first index and the second index, respectively.

4. The first device according to claim 1, wherein the first device is further configured to: The initial horizontal beam vector is determined by: performing horizontal beam scanning on the second device; receiving a first index of the initial horizontal beam vector from the second device; Based on the first index, determining the initial horizontal beam vector; and determining the initial vertical beam vector by: receiving a reference signal from the second device; and Based on the reference signal, the initial vertical beam vector is determined.

5. The first device according to claim 1, wherein the first device is further configured to: The initial vertical beam vector is determined by: performing vertical beam scanning on the second device; receiving a second index of the initial vertical beam vector from the second device; Based on the second index, determining the initial vertical beam vector; and determining the initial horizontal beam vector by: receiving a reference signal from the second device; and Based on the reference signal, the initial horizontal beam vector is determined.

6. The first device according to any one of claims 1 to 5, wherein the first device is configured to: determine the first set of candidate horizontal beams by: Determining the index of the power of the horizontal channel covariance matrix to be zero; and Execute the following a predetermined number of times: Determining the product of the power of the horizontal channel covariance matrix and the initial horizontal beam vector; including the product into the first set of candidate horizontal beams; and increasing the index of the power by 1; and The first device is further configured to: determine the first subset of the first set of candidate horizontal beams by: A first number of candidate horizontal beams are selected from the first set, the first number of candidate horizontal beams having an index of power greater than a threshold. 7 . The first device of claim 6 , wherein the predetermined number is equal to or greater than the number of beamforming vectors in the beamforming matrix.

8. The first device according to any one of claims 1 to 7, wherein the first device is configured to: determine at least one of the first set of candidate horizontal beams and the second set of candidate vertical beams by: determining a first association between uplink channel information previously received from a third plurality of devices and a predetermined beamforming process to be applied to the third plurality of devices; determining, based on the first association and uplink channel information received from the second device, a first beamforming process among the predetermined beamforming processes to be applied to the second device; as well as The at least one of the first set of candidate horizontal beams and the second set of candidate vertical beams is determined by performing the first beamforming process.

9. The first device according to any one of claims 1 to 7, wherein the first device is further configured to: determining a second association between a reference signal previously received from the second device and a horizontal channel covariance matrix and a vertical channel covariance matrix; receiving a first reference signal from the second device, the reference signal comprising the first reference signal; as well as The horizontal channel covariance matrix and the vertical channel covariance matrix are determined based on the second correlation and the first reference signal.

10. A method comprising: At the first device, continuously transforming an initial horizontal beam vector by a horizontal channel covariance matrix to determine a first set of candidate horizontal beams; continuously transforming the initial vertical beam vector by a vertical channel covariance matrix to determine a second set of candidate vertical beams; as well as Based on a first subset of the first set and a second subset of the second set, a beamforming matrix for communicating with a second device is determined.

11. The method according to claim 10, further comprising: receiving a reference signal from the second device; as well as Based on the reference signal, the initial horizontal beam vector and the initial vertical beam vector are determined.

12. The method according to claim 10, further comprising: The initial horizontal beam vector and the initial vertical beam vector are determined by: performing horizontal beam scanning and vertical beam scanning on the second device; receiving, from the second device, a first index of the initial horizontal beam vector and a second index of the initial vertical beam vector; and The initial horizontal beam vector and the initial vertical beam vector are determined based on the first index and the second index, respectively.

13. The method according to claim 10, further comprising: The initial horizontal beam vector is determined by: performing horizontal beam scanning on the second device; receiving a first index of the initial horizontal beam vector from the second device; Based on the first index, determining the initial horizontal beam vector; and determining the initial vertical beam vector by: receiving a reference signal from the second device; and Based on the reference signal, the initial vertical beam vector is determined.

14. The method according to claim 10, further comprising: The initial vertical beam vector is determined by: performing vertical beam scanning on the second device; receiving a second index of the initial vertical beam vector from the second device; Based on the second index, determining the initial vertical beam vector; and determining the initial horizontal beam vector by: receiving a reference signal from the second device; and Based on the reference signal, the initial horizontal beam vector is determined.

15. The method according to any one of claims 10 to 14, wherein determining the first set of candidate horizontal beams comprises: Determining that the index of the power of the horizontal channel covariance matrix is ​​zero; as well as Execute the following a predetermined number of times: Determining the product of the power of the horizontal channel covariance matrix and the initial horizontal beam vector; including the product into a first set of candidate horizontal beams; as well as Increasing the index of the power by 1; as well as The method further comprises: determining the first subset of the first set of candidate horizontal beams by: A first number of candidate horizontal beams are selected from the first set, the first number of candidate horizontal beams having an index of power greater than a threshold.

16. The method of claim 15, wherein the predetermined number is equal to or greater than the number of beamforming vectors in the beamforming matrix.

17. The method of any one of claims 10 to 16, wherein determining at least one of the first set of candidate horizontal beams and the second set of candidate vertical beams comprises: determining a first association between uplink channel information previously received from a third plurality of devices and a predetermined beamforming process to be applied to the third plurality of devices; determining, based on the first association and uplink channel information received from the second device, a first beamforming process among the predetermined beamforming processes to be applied to the second device; as well as The at least one of the first set of candidate horizontal beams and the second set of candidate vertical beams is determined by performing the first beamforming process.

18. The method according to any one of claims 10 to 16, further comprising: determining a second association between a reference signal previously received from the second device and a horizontal channel covariance matrix and a vertical channel covariance matrix; receiving a first reference signal from the second device, the reference signal comprising the first reference signal; as well as The horizontal channel covariance matrix and the vertical channel covariance matrix are determined based on the second correlation and the first reference signal.

19. An apparatus comprising: means for determining, at the first device, a first set of candidate horizontal beams by continuously transforming an initial horizontal beam vector by a horizontal channel covariance matrix; means for continuously transforming the initial vertical beam vector by a vertical channel covariance matrix to determine a second set of candidate vertical beams; as well as Means for determining a beamforming matrix for communicating with a second device based on a first subset of the first set and a second subset of the second set.

20. A computer-readable medium comprising program instructions, wherein the program instructions are used to cause an apparatus to at least perform the method according to any one of claims 10 to 18.

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