Beamforming method, apparatus and processor readable storage medium

Abstract

The application provides a beamforming method, device and processor readable storage medium, comprising: obtaining a channel estimation parameter; determining singular values of each stream of a plurality of streams of a signal source and first parameters of each stream according to the channel estimation parameter; performing power allocation between each stream according to the singular values of each stream and the first parameters of each stream, determining second parameters of each stream, and the second parameters of each stream are used to represent a mapping relationship between each stream and a transmitting antenna after the power allocation between each stream is performed; performing geometric mean decomposition (GMD) transformation of at least two streams in the plurality of streams according to the second parameters of each stream and the singular values of each stream, performing splicing and sorting processing according to the GMD transformation of the at least two streams in the plurality of streams, and determining first beamforming factors and second beamforming factors; and determining an apodization vector corresponding to the channel estimation parameter according to the first beamforming factors and the second beamforming factors, and the apodization vector is used for beamforming.

Description

Technical Field

[0001] This application relates to the field of wireless communication technology, and more specifically, to beamforming methods, apparatus, and processor-readable storage media. Background Technology

[0002] In 5G (5th Generation Mobile Communication Technology) Multiple-Input Multiple-Output (MIMO) communication scenarios, Eigenvalue Based Beamforming (EBB) and Geometric Mean Decomposition (GMD) beamforming algorithms are currently common beamforming methods. GMD can be considered an improvement on EBB. In certain channel scenarios, after beamforming using EBB, the gain difference between each stream is significant. When the system uses a unified modulation and coding scheme (MCS) for transmission, the stream with lower gain performs poorly, making it difficult to achieve high MCS transmission and thus limiting the overall transmission rate. GMD modifies each stream in the EBB algorithm, making the gain of each stream equal, but it also introduces inter-stream interference. Summary of the Invention

[0003] This application addresses the shortcomings of existing methods by proposing a beamforming method, apparatus, and processor-readable storage medium to resolve the aforementioned technical deficiencies.

[0004] Firstly, a beamforming method is provided, including:

[0005] Obtain channel estimation parameters;

[0006] Based on the channel estimation parameters, the singular values ​​of each stream in the multiple streams of the signal source and the first parameter of each stream are determined. The first parameter of each stream is used to characterize the mapping relationship between each stream and the transmitting antenna.

[0007] Based on the singular value of each stream and the first parameter of each stream, power allocation is performed between each stream, and the second parameter of each stream is determined. The second parameter of each stream is used to characterize the mapping relationship between each stream and the transmit antenna after the power allocation between each stream is performed.

[0008] Based on the second parameter of each stream and the singular value of each stream, perform geometric mean decomposition (GMD) transformation on at least two streams among multiple streams, and perform splicing and sorting processing based on the GMD transformation of at least two streams among multiple streams to determine the first beamforming factor and the second beamforming factor.

[0009] Based on the first beamforming factor and the second beamforming factor, the beamforming vector corresponding to the channel estimation parameters is determined, and the beamforming vector is used for beamforming.

[0010] In one embodiment, power allocation among each stream is performed based on the singular value of each stream and a first parameter of each stream, and a second parameter of each stream is determined, including:

[0011] Based on the singular values ​​of each flow, a pre-power allocation coefficient matrix is ​​determined, which is used for power allocation between each flow.

[0012] The second parameter of each flow is determined based on the previous power allocation coefficient matrix and the first parameter of each flow.

[0013] In one embodiment, the pre-power allocation coefficient matrix is ​​determined based on the singular values ​​of each stream, including:

[0014] The front power allocation coefficient matrix is ​​determined based on the singular values ​​of each flow and the preset inter-flow power allocation coefficients.

[0015] In one embodiment, the pre-power allocation coefficient matrix is ​​determined based on the singular values ​​of each flow and a preset inter-flow power allocation coefficient, including:

[0016] The front power allocation coefficient matrix is ​​determined using the following formula:

[0017]

[0018] Where Φ represents the front power allocation coefficient matrix, and Σ represents the singular value matrix for each flow. These are the diagonal elements of the singular value matrix Σ. N represents the singular value of each flow, p represents the inter-flow power distribution coefficient, and N represents the singular value of each flow. L Indicates the number of streams transmitted.

[0019] In one embodiment, determining the second parameter of each stream based on the pre-power allocation coefficient matrix and the first parameter of each stream includes:

[0020] The second parameter of each stream is determined using the following formula:

[0021]

[0022] Among them, V PAThe elements in the matrix are the second parameter of each flow, where V represents the right singular vector and Φ represents the front power distribution coefficient matrix. This represents the first parameter of each stream, which is an element in V. For elements in Φ, The second parameter for each flow, p, represents the inter-flow power allocation coefficient, N L Indicates the number of streams transmitted.

[0023] In one embodiment, GMD transforms are performed on at least two of the multiple streams based on the second parameter of each stream and the singular value of each stream, and a splicing and sorting process is performed based on the GMD transforms of at least two of the multiple streams to determine the first beamforming factor and the second beamforming factor, including:

[0024] Perform GMD transformation on the second parameters of at least two of the multiple streams to determine the third parameters of at least two streams;

[0025] The first factor is determined by concatenating the third parameters of at least two streams and the second parameters of other streams besides the at least two streams.

[0026] Perform GMD transformation on the singular values ​​of at least two streams to determine the GMD transformation matrix of at least two streams;

[0027] The second factor is determined by concatenating the matrices after GMD transformation of at least two streams and the singular values ​​of the other streams besides the at least two streams.

[0028] Sort each parameter in the first factor to determine the first beamforming factor;

[0029] The second beamforming factor is determined by sorting each parameter in the second factor.

[0030] In one embodiment, performing a GMD transformation on the second parameters of at least two of the multiple streams to determine the third parameters of the at least two streams includes:

[0031] The third parameter of the at least two streams is determined using the following formula:

[0032] P′=V′G′1

[0033] Here, the elements in P′ are the third parameters of at least two streams, the elements in V′ are the second parameters of at least two streams, and G′1 represents the GMD transformation matrix of V′.

[0034] In one embodiment, concatenating the third parameters of at least two streams and the second parameters of the other streams (excluding the at least two streams) to determine the first factor includes:

[0035] The first factor is determined using the following formula:

[0036]

[0037] Among them, V comb Indicates the first factor. The elements in P' are the second parameters of the streams other than at least two of the streams, and the elements in P' are the third parameters of at least two of the streams.

[0038] In one embodiment, the second factor is determined by concatenating the GMD-transformed matrices of at least two streams and the singular values ​​of the other streams (excluding the at least two streams) from a plurality of streams, including:

[0039] The second factor is determined using the following formula:

[0040]

[0041] Among them, R comb Indicates the second factor. The elements in are the singular values ​​of the other streams besides at least two of the streams, and R′ represents the matrix after the GMD transformation of at least two streams.

[0042] In one embodiment, determining the beamforming vector corresponding to the channel estimation parameters based on the first beamforming factor and the second beamforming factor includes:

[0043] The power allocation coefficient matrix is ​​determined based on the second beamforming factor.

[0044] Based on the post-power allocation coefficient matrix and the first beamforming factor, the beamforming vector corresponding to the channel estimation parameters is determined.

[0045] In one embodiment, determining the post-power allocation coefficient matrix based on the second beamforming factor includes:

[0046] The downlink receive power for each stream is determined based on the second beamforming factor.

[0047] The corrected downlink received power for each stream is determined based on the downlink received power of each stream and a preset power correction factor.

[0048] The post-power allocation coefficient matrix is ​​determined based on the corrected downlink received power and the second beamforming factor for each stream.

[0049] In one embodiment, determining the downlink receive power for each stream based on the second beamforming factor includes:

[0050] The downlink receive power for each stream is determined using the following formula:

[0051]

[0052] In this context, K contains the downlink received power for each stream, diag(·) denotes the diagonal element operation, and R... sort Indicates the second beamforming factor. R represents sort The conjugate transpose of .

[0053] In one embodiment, determining the corrected downlink receive power for each stream based on the downlink receive power of each stream and a preset power correction factor includes:

[0054] The corrected downlink receive power for each stream is determined using the following formula:

[0055]

[0056] Where the elements in K are the downlink receive power for each stream, K represents the downlink received power for each stream, ξ represents the power correction factor, and K represents the downlink received power for each stream. ξ The elements in the table are the corrected downlink receive power for each stream. N represents the corrected downlink receive power for each stream. L Indicates the number of streams transmitted.

[0057] In one embodiment, the post-power allocation coefficient matrix is ​​determined based on the corrected downlink received power and the second beamforming factor for each stream, including:

[0058] The power allocation coefficient matrix is ​​determined using the following formula:

[0059] in,

[0060] Where, Φ post Denotes the post-power allocation coefficient matrix, Φ post diagonal elements in N represents the inter-flow power allocation factor for each flow. L Indicates the number of streams transmitted; This represents the corrected downlink receive power for each stream. This represents an element in the second beamforming factor.

[0061] In one embodiment, determining the beamforming vector corresponding to the channel estimation parameters based on the post-power allocation coefficient matrix and the first beamforming factor includes:

[0062] The shaping vector is determined using the following formula:

[0063] W = V sort Φ post

[0064] Where W represents the shaping vector, V sort Φ represents the first beamforming factor. post This represents the power allocation coefficient matrix.

[0065] In one embodiment, sorting each parameter in the first factor to determine the first beamforming factor includes:

[0066] Sort each parameter in the second factor from largest to smallest to obtain the sorting matrix;

[0067] Based on the sorting matrix, each parameter in the first factor is sorted to determine the first beamforming factor.

[0068] In one embodiment, the first beamforming factor is determined by sorting each parameter in the first factor according to the sorting matrix, including:

[0069] The first beamforming factor is determined using the following formula:

[0070] V sort =V comb Ψ

[0071] Among them, V sort V represents the first beamforming factor. comb Let Ψ denote the first factor, and Ψ denote the sorting matrix.

[0072] In one embodiment, sorting each parameter in the second factor to determine the second beamforming factor includes:

[0073] Sort each parameter in the second factor from largest to smallest to obtain the sorting matrix;

[0074] The second beamforming factor is determined based on each parameter in the sorting matrix and the second factor.

[0075] Secondly, a beamforming device is provided, including a memory, a transceiver, and a processor:

[0076] Memory is used to store computer programs; transceiver is used to send and receive data under the control of the processor; processor is used to read the computer programs from memory and perform the following operations:

[0077] Obtain channel estimation parameters;

[0078] Based on the channel estimation parameters, the singular values ​​of each stream in the multiple streams of the signal source and the first parameter of each stream are determined. The first parameter of each stream is used to characterize the mapping relationship between each stream and the transmitting antenna.

[0079] Based on the singular value of each stream and the first parameter of each stream, power allocation is performed between each stream, and the second parameter of each stream is determined. The second parameter of each stream is used to characterize the mapping relationship between each stream and the transmit antenna after the power allocation between each stream is performed.

[0080] Based on the second parameter of each stream and the singular value of each stream, perform geometric mean decomposition (GMD) transformation on at least two streams among multiple streams, and perform splicing and sorting processing based on the GMD transformation of at least two streams among multiple streams to determine the first beamforming factor and the second beamforming factor.

[0081] Based on the first beamforming factor and the second beamforming factor, the beamforming vector corresponding to the channel estimation parameters is determined, and the beamforming vector is used for beamforming.

[0082] Thirdly, this application provides a beamforming device, comprising:

[0083] The first processing unit is used to obtain channel estimation parameters;

[0084] The second processing unit is used to determine the singular value of each stream in the multiple streams of the signal source and the first parameter of each stream based on the channel estimation parameters. The first parameter of each stream is used to characterize the mapping relationship between each stream and the transmitting antenna.

[0085] The third processing unit is used to perform power allocation between each stream based on the singular value of each stream and the first parameter of each stream, and to determine the second parameter of each stream. The second parameter of each stream is used to characterize the mapping relationship between each stream and the transmitting antenna after the power allocation between each stream is performed.

[0086] The fourth processing unit is used to perform GMD transformation on at least two of the multiple streams based on the second parameter of each stream and the singular value of each stream, and to perform splicing and sorting processing based on the GMD transformation of at least two of the multiple streams to determine the first beamforming factor and the second beamforming factor.

[0087] The fifth processing unit is used to determine the beamforming vector corresponding to the channel estimation parameters based on the first beamforming factor and the second beamforming factor. The beamforming vector is used for beamforming.

[0088] Fourthly, a processor-readable storage medium is provided, characterized in that the processor-readable storage medium stores a computer program for causing the processor to perform the method described in the first aspect.

[0089] The technical solution provided in this application has at least the following beneficial effects:

[0090] By combining GMD and EBB beamforming, the gain gap between each stream can be reduced, while suppressing inter-stream interference introduced by GMD transformation, thereby improving the transmission performance of downlink multi-stream.

[0091] Additional aspects and advantages of this application will be set forth in part in the description which follows, and will become apparent from the description or may be learned by practice of this application. Attached Figure Description

[0092] To more clearly illustrate the technical solutions in the embodiments of this application, the accompanying drawings used in the description of the embodiments of this application will be briefly introduced below.

[0093] Figure 1 A comparative diagram showing the results of shaping EBB and GMD;

[0094] Figure 2 A schematic diagram of the system architecture provided for embodiments of this application;

[0095] Figure 3 A schematic flowchart of a beamforming method provided in an embodiment of this application;

[0096] Figure 4 A flowchart illustrating another beamforming method provided in an embodiment of this application;

[0097] Figure 5 A schematic diagram comparing the upper triangular matrix of the equivalent channel provided in the embodiments of this application with the upper triangular matrix after traditional GMD transformation;

[0098] Figure 6 This is a schematic diagram of the structure of a beamforming device provided in an embodiment of this application;

[0099] Figure 7 This is a schematic diagram of a beamforming device provided in an embodiment of this application. Detailed Implementation

[0100] The embodiments of this application are described in detail below. Examples of these embodiments are shown in the accompanying drawings, wherein the same or similar reference numerals denote the same or similar elements or elements having the same or similar functions throughout. The embodiments described below with reference to the accompanying drawings are exemplary and are only used to explain this application, and should not be construed as limiting this application.

[0101] Those skilled in the art will understand that, unless specifically stated otherwise, the singular forms “a,” “an,” “the,” and “the” used herein may also include the plural forms. It should be further understood that the term “comprising” as used in this application means the presence of the stated features, integers, steps, operations, elements, and / or components, but does not exclude the presence or addition of one or more other features, integers, steps, operations, elements, components, and / or groups thereof. It should be understood that when we say an element is “connected” or “coupled” to another element, it can be directly connected or coupled to the other element, or there may be intermediate elements. Furthermore, “connected” or “coupled” as used herein can include wireless connections or wireless coupling. The term “and / or” as used herein includes all or any units and all combinations of one or more associated listed items.

[0102] In this application's embodiments, the term "and / or" describes the relationship between related objects, indicating that three relationships can exist. For example, A and / or B can represent: A existing alone, A and B existing simultaneously, or B existing alone. The character " / " generally indicates that the preceding and following related objects have an "or" relationship. In this application's embodiments, the term "multiple" refers to two or more, and other quantifiers are similar.

[0103] To better understand and explain the solutions of the embodiments of this disclosure, some technical terms involved in the embodiments of this disclosure will be briefly explained below.

[0104] In 5G Multiple-Input Multiple-Output (MIMO) communication scenarios, 5G mobile communication systems employ multi-antenna technology. During downlink transmission, beamforming can be achieved using multiple antennas. This involves adjusting the amplitude and phase of each transmitting antenna to create a specific beam direction, increasing signal strength in the desired direction and decreasing signal strength in the interference direction. This improves the signal-to-noise ratio (SNR) or signal-to-interference-and-noise ratio (SINR) at the receiver, thereby achieving array gain. The gain magnitude is closely related to the choice of beamforming factor, especially in multi-stream (i.e., multiple sets of information transmitted simultaneously at the same frequency) transmission scenarios, where it is necessary to ensure the gain of each stream while suppressing inter-stream interference. 5G transmission systems employ a unified modulation and coding scheme (MCS) for multiple streams, meaning that each stream has the same transmission rate. Therefore, it is necessary to ensure that the gain of each stream is as balanced as possible. However, the detection capabilities of downlink receiver detection algorithms often differ for each stream, so the gain relationship for each stream needs to be matched with the downlink detection method.

[0105] Let U, Σ, and V represent the left singular vector, singular value matrix, and right singular vector of the singular value decomposition, respectively, and let H represent the channel estimation result. H can be decomposed according to the EBB method (i.e., singular value decomposition H = UΣV). H Alternatively, it can be decomposed according to the GMD method, as shown in formula (1).

[0106]

[0107] In this matrix, Q and P are both unitary matrices, R is an upper triangular matrix, and the rotation matrices G1 and G2 are both unitary matrices. The operation can transform the diagonal matrix Σ into an upper triangular matrix R. The EBB algorithm uses V as the shaping factor, and the shaping amplitude gain for each flow is the diagonal element of Σ; the GMD algorithm uses R as the shaping factor, and the shaping amplitude gain is the diagonal element of matrix R, while the off-diagonal elements of matrix R represent the interference between each flow.

[0108] like Figure 1 The difference between Σ and R is shown. After EBB beamforming, the gain of each stream varies significantly, but there is no inter-stream interference. In contrast, after GMD beamforming, the gain of each stream is equal (the diagonal elements are equal, equal to the geometric mean of the singular values ​​of each stream), but there is inter-stream interference. The intensity of inter-stream interference in GMD is related to the difference in singular values ​​of each stream involved in the computation; a larger difference results in greater interference. GMD beamforming algorithms generally require the receiver to employ a detection algorithm with strong interference suppression capabilities.

[0109] The technical solutions of the embodiments of this application will be clearly and completely described below with reference to the accompanying drawings. Obviously, the described embodiments are only a part of the embodiments of this application, and not all of the embodiments. Based on the embodiments of this application, all other embodiments obtained by those of ordinary skill in the art without creative effort are within the scope of protection of this application.

[0110] A schematic diagram of a system architecture provided in this application embodiment is shown below. Figure 2 As shown, the system architecture includes: network devices and terminals, wherein the network devices are, for example... Figure 2 Network device 10, terminal, for example Figure 2 Terminal 20. Network equipment is deployed in the access network; for example, network equipment 10 is deployed in the NG-RAN (New Generation-Radio Access Network) access network of a 5G system. The terminal and network equipment communicate with each other through some air interface technology, such as cellular technology.

[0111] The terminals involved in the embodiments of this application can be devices that provide voice and / or data connectivity to users, handheld devices with wireless connectivity, or other processing devices connected to a wireless modem. Terminal types include mobile phones, vehicle user terminals, tablet computers, laptops, personal digital assistants, mobile internet devices, wearable devices, etc.

[0112] The network device involved in this application embodiment can be a base station, which may include multiple cells providing services to terminals. Depending on the specific application, a base station may also be called an access point, or a device in the access network that communicates with wireless terminal devices through one or more sectors on the air interface, or other names. The network device can be used to exchange received air frames with Internet Protocol (IP) packets, acting as a router between the wireless terminal device and the rest of the access network, where the rest of the access network may include an Internet Protocol (IP) communication network. The network device can also coordinate the attribute management of the air interface. For example, the network equipment involved in the embodiments of this application can be a base transceiver station (BTS) in a Global System for Mobile communications (GSM) or Code Division Multiple Access (CDMA), a NodeB in a Wide-band Code Division Multiple Access (WCDMA) system, an evolved Node B (eNB or e-NodeB) in a long term evolution (LTE) system, a 5G base station (gNB) in a next generation system, a Home evolved Node B (HeNB), a relay node, a femto, a pico, etc., and is not limited in the embodiments of this application. In some network structures, the network equipment may include centralized unit (CU) nodes and distributed unit (DU) nodes, and the centralized unit and distributed unit may be geographically separated.

[0113] The beamforming and downlink transmission process of the network device on side 10 is as follows: Figure 2As shown, network device 10 contains multiple streams as its signal source. Each stream is mapped to a transmit antenna array via beamforming, and each antenna transmits a signal through the channel to the receive antenna array of terminal 20. Beamforming allows each stream to utilize different paths within the channel for transmission, resulting in lower interference between streams while ensuring each stream has strong gain.

[0114] To make the objectives, technical solutions, and advantages of this application clearer, the embodiments of this application will be described in further detail below with reference to the accompanying drawings.

[0115] This application provides a beamforming method, the flowchart of which is shown below. Figure 3 As shown, the method includes:

[0116] S301, obtain channel estimation parameters.

[0117] Specifically, the channel estimation parameters can be the channel estimation result H. The dimension of H is N. R ×N T , where N T N represents the number of downlink transmit antennas. R This indicates the number of downlink receiving antennas.

[0118] S302, based on the channel estimation parameters, determine the singular value of each stream in the multiple streams of the signal source and the first parameter of each stream. The first parameter of each stream is used to characterize the mapping relationship between each stream and the transmitting antenna.

[0119] Specifically, as shown in formula (2):

[0120] H=UΣV H Formula (2)

[0121] Where U, Σ, and V represent the left singular vector, singular value matrix, and right singular vector of the singular value decomposition, respectively. The exponent H of V represents the conjugate transpose operation. V can be expressed as... The dimension of V is N T ×N L This represents the mapping relationship between each stream and the transmit antenna. The dimensions are all N T ×1; the dimension of U is N R ×N L Σ represents the mapping relationship between the receiving antenna and each stream; the dimension of Σ is N. L ×N L , representing the singular value of each stream; N T N represents the number of downlink transmit antennas. R N represents the number of downlink receive antennas. L This represents the number of transmitted streams. The channel estimation result H represents the channel estimation parameters. This represents the first parameter of each stream. Represents the diagonal elements of the singular value matrix Σ. This represents the singular value of each stream.

[0122] S303, based on the singular value of each stream and the first parameter of each stream, perform power allocation between each stream, and determine the second parameter of each stream. The second parameter of each stream is used to characterize the mapping relationship between each stream and the transmitting antenna after the power allocation between each stream is performed.

[0123] In one embodiment, power allocation among each stream is performed based on the singular value of each stream and a first parameter of each stream, and a second parameter of each stream is determined, including:

[0124] Based on the singular values ​​of each flow, a pre-power allocation coefficient matrix is ​​determined, which is used for power allocation between each flow.

[0125] The second parameter of each flow is determined based on the previous power allocation coefficient matrix and the first parameter of each flow.

[0126] In one embodiment, the pre-power allocation coefficient matrix is ​​determined based on the singular values ​​of each stream, including:

[0127] The front power allocation coefficient matrix is ​​determined based on the singular values ​​of each flow and the preset inter-flow power allocation coefficients.

[0128] In one embodiment, the pre-power allocation coefficient matrix is ​​determined based on the singular values ​​of each flow and a preset inter-flow power allocation coefficient, including:

[0129] The front power allocation coefficient matrix is ​​determined using the following formula (3):

[0130]

[0131] Where Φ represents the front power allocation coefficient matrix, and Σ represents the singular value matrix for each flow. These are the diagonal elements of the singular value matrix Σ. N represents the singular value of each flow, p represents the inter-flow power distribution coefficient, and N represents the singular value of each flow. L Indicates the number of streams transmitted.

[0132] In one embodiment, determining the second parameter of each stream based on the pre-power allocation coefficient matrix and the first parameter of each stream includes:

[0133] The second parameter of each stream is determined using the following formula (4):

[0134]

[0135] Among them, VPA The elements in the matrix are the second parameter of each flow, where V represents the right singular vector and Φ represents the front power distribution coefficient matrix. This represents the first parameter of each stream, which is an element in V. For elements in Φ, The second parameter for each flow, p, represents the inter-flow power allocation coefficient, N L Indicates the number of streams transmitted.

[0136] S304, based on the second parameter of each stream and the singular value of each stream, perform geometric mean decomposition (GMD) transformation on at least two streams among the multiple streams, and perform splicing and sorting processing based on the GMD transformation of at least two streams among the multiple streams to determine the first beamforming factor and the second beamforming factor.

[0137] In one embodiment, GMD transforms are performed on at least two of the multiple streams based on the second parameter of each stream and the singular value of each stream, and a splicing and sorting process is performed based on the GMD transforms of at least two of the multiple streams to determine the first beamforming factor and the second beamforming factor, including:

[0138] Perform GMD transformation on the second parameters of at least two of the multiple streams to determine the third parameters of at least two streams;

[0139] The first factor is determined by concatenating the third parameters of at least two streams and the second parameters of other streams besides the at least two streams.

[0140] Perform GMD transformation on the singular values ​​of at least two streams to determine the GMD transformation matrix of at least two streams;

[0141] The second factor is determined by concatenating the matrices after GMD transformation of at least two streams and the singular values ​​of the other streams besides the at least two streams.

[0142] Sort each parameter in the first factor to determine the first beamforming factor;

[0143] The second beamforming factor is determined by sorting each parameter in the second factor.

[0144] In one embodiment, performing a GMD transformation on the second parameters of at least two of the multiple streams to determine the third parameters of the at least two streams includes:

[0145] The third parameter of the at least two streams is determined using the following formula (5):

[0146] P′=V′G′1 Formula (5)

[0147] Here, the elements in P′ are the third parameters of at least two streams, the elements in V′ are the second parameters of at least two streams, and G′1 represents the GMD transformation matrix of V′.

[0148] In one embodiment, concatenating the third parameters of at least two streams and the second parameters of the other streams (excluding the at least two streams) to determine the first factor includes:

[0149] The first factor is determined using the following formula (6):

[0150]

[0151] Among them, V comb Indicates the first factor. The elements in P' are the second parameters of the streams other than at least two of the streams, and the elements in P' are the third parameters of at least two of the streams.

[0152] In one embodiment, the second factor is determined by concatenating the GMD-transformed matrices of at least two streams and the singular values ​​of the other streams (excluding the at least two streams) from a plurality of streams, including:

[0153] The second factor is determined using the following formula (7):

[0154]

[0155] Among them, R comb Indicates the second factor. The elements in are the singular values ​​of the other streams besides at least two of the streams, and R′ represents the matrix after the GMD transformation of at least two streams.

[0156] In one embodiment, sorting each parameter in the first factor to determine the first beamforming factor includes:

[0157] Sort each parameter in the second factor from largest to smallest to obtain the sorting matrix;

[0158] Based on the sorting matrix, each parameter in the first factor is sorted to determine the first beamforming factor.

[0159] In one embodiment, the first beamforming factor is determined by sorting each parameter in the first factor according to the sorting matrix, including:

[0160] The first beamforming factor is determined using the following formula (8):

[0161] V sort =V comb Formula (8)

[0162] Among them, V sortV represents the first beamforming factor. comb Let Ψ denote the first factor, and Ψ denote the sorting matrix.

[0163] In one embodiment, sorting each parameter in the second factor to determine the second beamforming factor includes:

[0164] Sort each parameter in the second factor from largest to smallest to obtain the sorting matrix;

[0165] The second beamforming factor is determined based on each parameter in the sorting matrix and the second factor.

[0166] S305, based on the first beamforming factor and the second beamforming factor, determine the beamforming vector corresponding to the channel estimation parameters, and use the beamforming vector for beamforming.

[0167] In one embodiment, determining the beamforming vector corresponding to the channel estimation parameters based on the first beamforming factor and the second beamforming factor includes:

[0168] The power allocation coefficient matrix is ​​determined based on the second beamforming factor.

[0169] Based on the post-power allocation coefficient matrix and the first beamforming factor, the beamforming vector corresponding to the channel estimation parameters is determined.

[0170] In one embodiment, determining the post-power allocation coefficient matrix based on the second beamforming factor includes:

[0171] The downlink receive power for each stream is determined based on the second beamforming factor.

[0172] The corrected downlink received power for each stream is determined based on the downlink received power of each stream and a preset power correction factor.

[0173] The post-power allocation coefficient matrix is ​​determined based on the corrected downlink received power and the second beamforming factor for each stream.

[0174] In one embodiment, determining the downlink receive power for each stream based on the second beamforming factor includes:

[0175] The downlink receive power for each stream is determined using the following formula (9):

[0176]

[0177] In this context, K contains the downlink received power for each stream, diag(·) denotes the diagonal element operation, and R... sort Indicates the second beamforming factor. R represents sort The conjugate transpose of .

[0178] In one embodiment, determining the corrected downlink receive power for each stream based on the downlink receive power of each stream and a preset power correction factor includes:

[0179] The corrected downlink receive power for each stream is determined using the following formula (10):

[0180]

[0181] Where the elements in K are the downlink receive power for each stream, K represents the downlink received power for each stream, ξ represents the power correction factor, and K represents the downlink received power for each stream. ξ The elements in the table are the corrected downlink receive power for each stream. N represents the corrected downlink receive power for each stream. L Indicates the number of streams transmitted; K′ represents K. ξ , They represent

[0182] In one embodiment, the post-power allocation coefficient matrix is ​​determined based on the corrected downlink received power and the second beamforming factor for each stream, including:

[0183] The power allocation coefficient matrix is ​​determined using the following formula (11):

[0184] in,

[0185] Where, Φ post Denotes the post-power allocation coefficient matrix, Φ post diagonal elements in N represents the inter-flow power allocation factor for each flow. L Indicates the number of streams transmitted; This represents the corrected downlink receive power for each stream. This represents an element in the second beamforming factor.

[0186] In one embodiment, determining the beamforming vector corresponding to the channel estimation parameters based on the post-power allocation coefficient matrix and the first beamforming factor includes:

[0187] The shaping vector is determined using the following formula (12):

[0188] W = V sort Φ post Formula (12)

[0189] Where W represents the shaping vector, V sort Φ represents the first beamforming factor. post This represents the power allocation coefficient matrix.

[0190] In this embodiment of the application, the gain difference between each stream can be reduced by combining GMD and EBB beamforming, while suppressing inter-stream interference introduced by GMD transformation, thereby improving the transmission performance of downlink multi-stream.

[0191] The beamforming method of the above embodiments of this application will be fully and thoroughly described through the following examples:

[0192] This application provides another beamforming method, the flowchart of which is shown below. Figure 4 As shown, the method includes:

[0193] S401, perform singular value decomposition on the channel estimation result H.

[0194] Specifically, the singular value decomposition of the channel estimation result H is shown in Equation (2):

[0195] H=UΣV H Formula (2)

[0196] Where U, Σ, and V represent the left singular vector, singular value matrix, and right singular vector of the singular value decomposition, respectively. The exponent H of V represents the conjugate transpose operation. V can be expressed as... The dimension of V is N T ×N L This represents the mapping relationship between each stream and the transmit antenna. The dimensions are all N T ×1; the dimension of U is N R ×N L Σ represents the mapping relationship between the receiving antenna and each stream; the dimension of Σ is N. L ×N L , representing the singular value of each stream; N T N represents the number of downlink transmit antennas. R N represents the number of downlink receive antennas. L This represents the number of transmitted streams. The channel estimation result H represents the channel estimation parameters. This represents the first parameter of each stream. Represents the diagonal elements of the singular value matrix Σ. This represents the singular value of each stream.

[0197] S402, calculate the power distribution coefficient matrix Φ.

[0198] Specifically, let N be the downlink. L If each stream is transmitted, then the front power allocation coefficient matrix Φ is N. L ×N L The diagonal matrix is ​​used to calculate the power distribution coefficient matrix Φ before calculation, as shown in formula (3):

[0199]

[0200] Where Φ represents the front power allocation coefficient matrix, and Σ represents the singular value matrix for each flow. These are the diagonal elements of the singular value matrix Σ. N represents the singular value of each flow, p represents the inter-flow power distribution coefficient, and N represents the singular value of each flow. L This indicates the number of streams transmitted. p can take values ​​of... p can be adjusted based on the singular value distribution of each flow.

[0201] S403 performs front power distribution.

[0202] Specifically, the inter-current power allocation (pre-power allocation) for V is shown in Equation (4):

[0203]

[0204] Among them, V PA The elements in the matrix are the second parameter of each flow, where V represents the right singular vector and Φ represents the front power distribution coefficient matrix. This represents the first parameter of each stream, which is an element in V. For elements in Φ, The second parameter for each flow, p, represents the inter-flow power allocation coefficient, N L Indicates the number of streams transmitted.

[0205] It should be noted that by reducing the singularity difference between each stream through inter-stream power allocation, the interference between each stream after the subsequent GMD transformation is reduced. The value of p should not be too large, otherwise the overall gain will decrease significantly.

[0206] S404, Select a portion of the stream for GMD transformation.

[0207] Specifically, in V PA Select the corresponding columns to perform GMD transformation. For example, you can select Stream 1 and Stream 3, i.e., V PA Perform GMD transformation on the first and third columns; for example, select stream two and stream three (i.e., V). PA Perform GMD transformation on the second and third columns. Let the factor participating in the GMD transformation be V′ (for example, V′ includes V). PA If the first and third columns are used, then the GMD transformation result is shown in formula (5):

[0208] P′=V′G′1 Formula (5)

[0209] In this matrix, P′ represents the third parameter of at least two streams, V′ represents the second parameter of at least two streams, and G′1 represents the GMD transformation matrix of V′, which transforms V′ into P′. For example, the first and third diagonal elements of Σ, after GMD transformation, yield the corresponding upper triangular matrix R′. Factors not involved in the GMD transformation are... For example, Including V PA The second and fourth columns.

[0210] S405, perform GMD-EBB combination processing.

[0211] Specifically, let the factors that do not participate in the GMD transformation be... Its corresponding singular value matrix is Will Concatenating it with P′, we get V. comb As shown in formula (6); and R′, By piecing them together, we get R. comb As shown in formula (7).

[0212]

[0213]

[0214] Among them, V comb Indicates the first factor. The elements in R are the second parameters of the streams other than at least two of the streams, and the elements in P′ are the third parameters of at least two of the streams. comb Indicates the second factor. The elements in are the singular values ​​of the other streams besides at least two of the streams, and R′ represents the matrix after the GMD transformation of at least two streams.

[0215] For example, for matrix R comb Sort the diagonal elements in descending order to obtain a sorted matrix Ψ with dimension N. L ×N L Assume N L =4. When the sorting method is [1, 4, 2, 3], the sorting matrix Ψ is as shown in formula (13):

[0216]

[0217] For V comb Sort to get

[0218] V sort =V comb Formula (8)

[0219] Among them, Vsort V represents the first beamforming factor. comb Let Ψ denote the first factor, and Ψ denote the sorting matrix.

[0220] For example, for V comb Each column is rearranged in the order [1, 4, 2, 3], R comb After reordering, it becomes R sort It is still an upper triangular matrix. It can be determined by R. comb Get V sort According to V sort , to obtain R sort ;R sort V represents sort The corresponding upper triangular matrix.

[0221] S406, calculated power distribution coefficient matrix Φ post .

[0222] Specifically, with the downlink received power of each stream ( The received power of each stream after shaping is used as the correction target, where K is calculated as shown in formula (9):

[0223]

[0224] In this context, K contains the downlink received power for each stream, diag(·) denotes the diagonal element operation, and R... sort Indicates the second beamforming factor. R represents sort The conjugate transpose of .

[0225] The K-corrected power, i.e. the corrected downlink received power for each stream, is shown in formula (10):

[0226]

[0227] Where the elements in K are the downlink receive power for each stream, K represents the downlink received power for each stream, ξ represents the power correction factor, and K represents the downlink received power for each stream. ξ The elements in the table are the corrected downlink receive power for each stream. N represents the corrected downlink receive power for each stream. L Indicates the number of streams transmitted; K′ represents K. ξ , They represent ξ can be configured according to the actual channel environment, and ξ can be 1 / 2.

[0228] R sort V represents sortThe corresponding upper triangular matrix has the structure shown in formula (14):

[0229]

[0230] in, R represents sort In each element of N, the lower triangular elements of the matrix are all 0. L Indicates the number of streams transmitted.

[0231] Let Φ be a diagonal matrix post As shown in formula (11):

[0232] in,

[0233] Where, Φ post Denotes the post-power allocation coefficient matrix, Φ post diagonal elements in N represents the inter-flow power allocation factor for each flow. L Indicates the number of streams transmitted; This represents the corrected downlink receive power for each stream. This represents an element in the second beamforming factor.

[0234] S407 performs post-power allocation to determine the shaping vector W.

[0235] Specifically, for V sort Perform inter-flow power allocation (post-power allocation) to obtain the shaping vector W, as shown in formula (12):

[0236] W = V sort Φ post Formula (12)

[0237] Where W represents the shaping vector, and the dimension of W is N. T ×N L N T N represents the number of downlink transmit antennas. L Indicates the number of streams transmitted. V sort Φ represents the first beamforming factor. post This represents the power allocation coefficient matrix.

[0238] W represents the shaping vector, and the equivalent channel after shaping is shown in Equation (15):

[0239] H e =HW Formula (15)

[0240] The upper triangular matrix of the equivalent channel is shown in equation (16):

[0241] R′ sort =Rsort Φ post . Formula (16)

[0242] Among them, R′ sort It is R sort Multiply each column by Φ post The corresponding diagonal element, such as R′ sort The first column is R sort Multiply the first column by φ post,1 .

[0243] In this embodiment, before performing GMD transformation, inter-stream power allocation (pre-power allocation) is performed on the singular value decomposition results to reduce the gain difference between each stream, thereby suppressing interference in each stream in the GMD results. Selecting a subset of streams for GMD transformation and then combining them with the original EBB shaping factors (without GMD transformation) aims to avoid completely aligning the gains of each stream. This allows for compatibility with downlink receiver detection algorithms (layer-by-layer detection algorithms at the receiver often do not perform balanced detection on every stream, but rather apply stronger interference suppression to later streams and weaker interference suppression to earlier streams). Furthermore, the GMD-EBB combination method can balance the advantages of both approaches, resulting in a relatively balanced overall gain, interference, and gain-interference relationship for each stream. Power allocation (post-power allocation) on the GMD-EBB combination results further adjusts the gain and interference relationship of each stream, ensuring the shaping results match the downlink receiver detection algorithm.

[0244] In one embodiment, such as Figure 5 As shown, the upper triangular matrix R′ of the equivalent channel sort The distribution change is relative to the distribution change of the upper triangular matrix after the traditional GMD transformation. The upper triangular matrix R′ of the equivalent channel. sort The diagonal elements are reduced (equivalent to a decrease in the gain of each flow), and the gains of each flow are not exactly equal (decreasing sequentially), but the differences are small; for example, in the off-diagonal elements, there is interference between flow two (second column) and flow three (third column), but no interference between other flows; in this way, the gain of each flow and the intensity of inter-flow interference can be flexibly changed in different scenarios to achieve performance improvement.

[0245] In this embodiment, a combination of pre-power allocation and GMD-EBB is used to suppress inter-flow interference of GMD. Simultaneously, leveraging the relatively balanced gain of each flow in GMD, the overall rate is improved under a unified MCS transmission condition for each flow. When the downlink receiver detection algorithm has varying interference suppression capabilities for each flow, GMD-EBB combination processing can be used to match the interference relationship of each flow with the interference suppression capability of each flow at the receiver. By combining the advantages of pre-power allocation, post-power allocation, and GMD-EBB combination processing, a higher transmission rate is adaptively achieved in the actual channel environment. The inter-flow power allocation coefficient and GMD-EBB combination method can be adjusted according to actual needs to match the detection capability of the downlink receiver detection algorithm for each flow.

[0246] Based on the same inventive concept, this application also provides a beamforming device, the structural schematic diagram of which is shown below. Figure 6 As shown, transceiver 1300 is used to receive and send data under the control of processor 1310.

[0247] Among them, Figure 6 In this context, the bus architecture can include any number of interconnected buses and bridges, specifically linking various circuits together, represented by one or more processors (processor 1310) and memory (memory 1320). The bus architecture can also link together various other circuits such as peripheral devices, voltage regulators, and power management circuits, which are well known in the art and therefore will not be described further herein. The bus interface provides an interface. The transceiver 1300 can be multiple elements, including transmitters and receivers, providing units for communicating with various other devices over transmission media, including wireless channels, wired channels, optical fibers, etc. The processor 1310 is responsible for managing the bus architecture and general processing, and the memory 1320 can store data used by the processor 1310 during operation.

[0248] The processor 1310 can be a central processing unit (CPU), an application-specific integrated circuit (ASIC), a field-programmable gate array (FPGA), or a complex programmable logic device (CPLD). The processor can also adopt a multi-core architecture.

[0249] Processor 1310 is configured to read the computer program in the memory and perform the following operations:

[0250] Obtain channel estimation parameters;

[0251] Based on the channel estimation parameters, the singular values ​​of each stream in the multiple streams of the signal source and the first parameter of each stream are determined. The first parameter of each stream is used to characterize the mapping relationship between each stream and the transmitting antenna.

[0252] Based on the singular value of each stream and the first parameter of each stream, power allocation is performed between each stream, and the second parameter of each stream is determined. The second parameter of each stream is used to characterize the mapping relationship between each stream and the transmit antenna after the power allocation between each stream is performed.

[0253] Based on the second parameter of each stream and the singular value of each stream, perform geometric mean decomposition (GMD) transformation on at least two streams among multiple streams, and perform splicing and sorting processing based on the GMD transformation of at least two streams among multiple streams to determine the first beamforming factor and the second beamforming factor.

[0254] Based on the first beamforming factor and the second beamforming factor, the beamforming vector corresponding to the channel estimation parameters is determined, and the beamforming vector is used for beamforming.

[0255] In one embodiment, power allocation among each stream is performed based on the singular value of each stream and a first parameter of each stream, and a second parameter of each stream is determined, including:

[0256] Based on the singular values ​​of each flow, a pre-power allocation coefficient matrix is ​​determined, which is used for power allocation between each flow.

[0257] The second parameter of each flow is determined based on the previous power allocation coefficient matrix and the first parameter of each flow.

[0258] In one embodiment, the pre-power allocation coefficient matrix is ​​determined based on the singular values ​​of each stream, including:

[0259] The front power allocation coefficient matrix is ​​determined based on the singular values ​​of each flow and the preset inter-flow power allocation coefficients.

[0260] In one embodiment, the pre-power allocation coefficient matrix is ​​determined based on the singular values ​​of each flow and a preset inter-flow power allocation coefficient, including:

[0261] The front power allocation coefficient matrix is ​​determined using the following formula:

[0262]

[0263] Where Φ represents the front power allocation coefficient matrix, and Σ represents the singular value matrix for each flow. These are the diagonal elements of the singular value matrix Σ. N represents the singular value of each flow, p represents the inter-flow power distribution coefficient, and N represents the singular value of each flow. L Indicates the number of streams transmitted.

[0264] In one embodiment, determining the second parameter of each stream based on the pre-power allocation coefficient matrix and the first parameter of each stream includes:

[0265] The second parameter of each stream is determined using the following formula:

[0266]

[0267] Among them, V PA The elements in the matrix are the second parameter of each flow, where V represents the right singular vector and Φ represents the front power distribution coefficient matrix. This represents the first parameter of each stream, which is an element in V. For elements in Φ, The second parameter for each flow, p, represents the inter-flow power allocation coefficient, N L Indicates the number of streams transmitted.

[0268] In one embodiment, GMD transforms are performed on at least two of the multiple streams based on the second parameter of each stream and the singular value of each stream, and a splicing and sorting process is performed based on the GMD transforms of at least two of the multiple streams to determine the first beamforming factor and the second beamforming factor, including:

[0269] Perform GMD transformation on the second parameters of at least two of the multiple streams to determine the third parameters of at least two streams;

[0270] The first factor is determined by concatenating the third parameters of at least two streams and the second parameters of other streams besides the at least two streams.

[0271] Perform GMD transformation on the singular values ​​of at least two streams to determine the GMD transformation matrix of at least two streams;

[0272] The second factor is determined by concatenating the matrices after GMD transformation of at least two streams and the singular values ​​of the other streams besides the at least two streams.

[0273] Sort each parameter in the first factor to determine the first beamforming factor;

[0274] The second beamforming factor is determined by sorting each parameter in the second factor.

[0275] In one embodiment, performing a GMD transformation on the second parameters of at least two of the multiple streams to determine the third parameters of the at least two streams includes:

[0276] The third parameter of the at least two streams is determined using the following formula:

[0277] P′=V′G′1

[0278] Here, the elements in P′ are the third parameters of at least two streams, the elements in V′ are the second parameters of at least two streams, and G′1 represents the GMD transformation matrix of V′.

[0279] In one embodiment, concatenating the third parameters of at least two streams and the second parameters of the other streams (excluding the at least two streams) to determine the first factor includes:

[0280] The first factor is determined using the following formula:

[0281]

[0282] Among them, V comb Indicates the first factor. The elements in P' are the second parameters of the streams other than at least two of the streams, and the elements in P' are the third parameters of at least two of the streams.

[0283] In one embodiment, the second factor is determined by concatenating the GMD-transformed matrices of at least two streams and the singular values ​​of the other streams (excluding the at least two streams) from a plurality of streams, including:

[0284] The second factor is determined using the following formula:

[0285]

[0286] Among them, R comb Indicates the second factor. The elements in are the singular values ​​of the other streams besides at least two of the streams, and R′ represents the matrix after the GMD transformation of at least two streams.

[0287] In one embodiment, determining the beamforming vector corresponding to the channel estimation parameters based on the first beamforming factor and the second beamforming factor includes:

[0288] The power allocation coefficient matrix is ​​determined based on the second beamforming factor.

[0289] Based on the post-power allocation coefficient matrix and the first beamforming factor, the beamforming vector corresponding to the channel estimation parameters is determined.

[0290] In one embodiment, determining the post-power allocation coefficient matrix based on the second beamforming factor includes:

[0291] The downlink receive power for each stream is determined based on the second beamforming factor.

[0292] The corrected downlink received power for each stream is determined based on the downlink received power of each stream and a preset power correction factor.

[0293] The post-power allocation coefficient matrix is ​​determined based on the corrected downlink received power and the second beamforming factor for each stream.

[0294] In one embodiment, determining the downlink receive power for each stream based on the second beamforming factor includes:

[0295] The downlink receive power for each stream is determined using the following formula:

[0296]

[0297] In this context, K contains the downlink received power for each stream, diag(·) denotes the diagonal element operation, and R... sort Indicates the second beamforming factor. R represents sort The conjugate transpose of .

[0298] In one embodiment, determining the corrected downlink receive power for each stream based on the downlink receive power of each stream and a preset power correction factor includes:

[0299] The corrected downlink receive power for each stream is determined using the following formula:

[0300]

[0301] Where the elements in K are the downlink receive power for each stream, K represents the downlink received power for each stream, ξ represents the power correction factor, and K represents the downlink received power for each stream. ξ The elements in the table are the corrected downlink receive power for each stream. N represents the corrected downlink receive power for each stream. L Indicates the number of streams transmitted.

[0302] In one embodiment, the post-power allocation coefficient matrix is ​​determined based on the corrected downlink received power and the second beamforming factor for each stream, including:

[0303] The power allocation coefficient matrix is ​​determined using the following formula:

[0304] in,

[0305] Where, Φ post Denotes the post-power allocation coefficient matrix, Φ post diagonal elements in N represents the inter-flow power allocation factor for each flow. L Indicates the number of streams transmitted; This represents the corrected downlink receive power for each stream. This represents an element in the second beamforming factor.

[0306] In one embodiment, determining the beamforming vector corresponding to the channel estimation parameters based on the post-power allocation coefficient matrix and the first beamforming factor includes:

[0307] The shaping vector is determined using the following formula:

[0308] W = V sort Φ post

[0309] Where W represents the shaping vector, V sort Φ represents the first beamforming factor. post This represents the power allocation coefficient matrix.

[0310] In one embodiment, sorting each parameter in the first factor to determine the first beamforming factor includes:

[0311] Sort each parameter in the second factor from largest to smallest to obtain the sorting matrix;

[0312] Based on the sorting matrix, each parameter in the first factor is sorted to determine the first beamforming factor.

[0313] In one embodiment, the first beamforming factor is determined by sorting each parameter in the first factor according to the sorting matrix, including:

[0314] The first beamforming factor is determined using the following formula:

[0315] V sort =V comb Ψ

[0316] Among them, V sort V represents the first beamforming factor. comb Let Ψ denote the first factor, and Ψ denote the sorting matrix.

[0317] In one embodiment, sorting each parameter in the second factor to determine the second beamforming factor includes:

[0318] Sort each parameter in the second factor from largest to smallest to obtain the sorting matrix;

[0319] The second beamforming factor is determined based on each parameter in the sorting matrix and the second factor.

[0320] It should be noted that the apparatus provided in this embodiment of the invention can implement all the method steps implemented in the above method embodiment and can achieve the same technical effect. Therefore, the parts and beneficial effects that are the same as those in the method embodiment will not be described in detail here.

[0321] Based on the same inventive concept as the foregoing embodiments, this application also provides a beamforming device, the structural schematic diagram of which is shown below. Figure 7 As shown, the beamforming device 70 includes a first processing unit 701, a second processing unit 702, a third processing unit 703, a fourth processing unit 704, and a fifth processing unit 705.

[0322] The first processing unit 701 is used to obtain channel estimation parameters;

[0323] The second processing unit 702 is used to determine the singular value of each stream in the multiple streams of the signal source and the first parameter of each stream according to the channel estimation parameters. The first parameter of each stream is used to characterize the mapping relationship between each stream and the transmitting antenna.

[0324] The third processing unit 703 is used to perform power allocation between each stream based on the singular value of each stream and the first parameter of each stream, and to determine the second parameter of each stream. The second parameter of each stream is used to characterize the mapping relationship between each stream and the transmitting antenna after the power allocation between each stream is performed.

[0325] The fourth processing unit 704 is used to perform GMD transformation on at least two of the multiple streams based on the second parameter of each stream and the singular value of each stream, and to perform splicing and sorting processing based on the GMD transformation of at least two of the multiple streams to determine the first beamforming factor and the second beamforming factor.

[0326] The fifth processing unit 705 is used to determine the beamforming vector corresponding to the channel estimation parameters based on the first beamforming factor and the second beamforming factor. The beamforming vector is used for beamforming.

[0327] In one embodiment, the third processing unit 703 is specifically used for:

[0328] Based on the singular values ​​of each flow, a pre-power allocation coefficient matrix is ​​determined, which is used for power allocation between each flow.

[0329] The second parameter of each flow is determined based on the previous power allocation coefficient matrix and the first parameter of each flow.

[0330] In one embodiment, the third processing unit 703 is specifically used for:

[0331] The front power allocation coefficient matrix is ​​determined based on the singular values ​​of each flow and the preset inter-flow power allocation coefficients.

[0332] In one embodiment, the third processing unit 703 is specifically used for:

[0333] The front power allocation coefficient matrix is ​​determined using the following formula:

[0334]

[0335] Where Φ represents the front power allocation coefficient matrix, and Σ represents the singular value matrix for each flow. These are the diagonal elements of the singular value matrix Σ. N represents the singular value of each flow, p represents the inter-flow power distribution coefficient, and N represents the singular value of each flow. L Indicates the number of streams transmitted.

[0336] In one embodiment, the third processing unit 703 is specifically used for:

[0337] The second parameter of each stream is determined using the following formula:

[0338]

[0339] Among them, V PA The elements in the matrix are the second parameter of each flow, where V represents the right singular vector and Φ represents the front power distribution coefficient matrix. This represents the first parameter of each stream, which is an element in V. For elements in Φ, The second parameter for each flow, p, represents the inter-flow power allocation coefficient, N L Indicates the number of streams transmitted.

[0340] In one embodiment, the fourth processing unit 704 is specifically used for:

[0341] Perform GMD transformation on the second parameters of at least two of the multiple streams to determine the third parameters of at least two streams;

[0342] The first factor is determined by concatenating the third parameters of at least two streams and the second parameters of other streams besides the at least two streams.

[0343] Perform GMD transformation on the singular values ​​of at least two streams to determine the GMD transformation matrix of at least two streams;

[0344] The second factor is determined by concatenating the matrices after GMD transformation of at least two streams and the singular values ​​of the other streams besides the at least two streams.

[0345] Sort each parameter in the first factor to determine the first beamforming factor;

[0346] The second beamforming factor is determined by sorting each parameter in the second factor.

[0347] In one embodiment, the fourth processing unit 704 is specifically used for:

[0348] The third parameter of the at least two streams is determined using the following formula:

[0349] P′=V′G′1

[0350] Here, the elements in P′ are the third parameters of at least two streams, the elements in V′ are the second parameters of at least two streams, and G′1 represents the GMD transformation matrix of V′.

[0351] In one embodiment, the fourth processing unit 704 is specifically used for:

[0352] The first factor is determined using the following formula:

[0353]

[0354] Among them, V comb Indicates the first factor. The elements in P' are the second parameters of the streams other than at least two of the streams, and the elements in P' are the third parameters of at least two of the streams.

[0355] In one embodiment, the fourth processing unit 704 is specifically used for:

[0356] The second factor is determined using the following formula:

[0357]

[0358] Among them, R comb Indicates the second factor. The elements in are the singular values ​​of the other streams besides at least two of the streams, and R′ represents the matrix after the GMD transformation of at least two streams.

[0359] In one embodiment, the fifth processing unit 705 is specifically used for:

[0360] The power allocation coefficient matrix is ​​determined based on the second beamforming factor.

[0361] Based on the post-power allocation coefficient matrix and the first beamforming factor, the beamforming vector corresponding to the channel estimation parameters is determined.

[0362] In one embodiment, the fifth processing unit 705 is specifically used for:

[0363] The downlink receive power for each stream is determined based on the second beamforming factor.

[0364] The corrected downlink received power for each stream is determined based on the downlink received power of each stream and a preset power correction factor.

[0365] The post-power allocation coefficient matrix is ​​determined based on the corrected downlink received power and the second beamforming factor for each stream.

[0366] In one embodiment, the fifth processing unit 705 is specifically used for:

[0367] The downlink receive power for each stream is determined using the following formula:

[0368]

[0369] In this context, K contains the downlink received power for each stream, diag(·) denotes the diagonal element operation, and R... sort Indicates the second beamforming factor. R represents sort The conjugate transpose of .

[0370] In one embodiment, the fifth processing unit 705 is specifically used for:

[0371] The corrected downlink receive power for each stream is determined using the following formula:

[0372]

[0373] Where the elements in K are the downlink receive power for each stream, K represents the downlink received power for each stream, ξ represents the power correction factor, and K represents the downlink received power for each stream. ξ The elements in the table are the corrected downlink receive power for each stream. N represents the corrected downlink receive power for each stream. L Indicates the number of streams transmitted.

[0374] In one embodiment, the fifth processing unit 705 is specifically used for:

[0375] The power allocation coefficient matrix is ​​determined using the following formula:

[0376] in,

[0377] Where, Φ post Denotes the post-power allocation coefficient matrix, Φ post diagonal elements in N represents the inter-flow power allocation factor for each flow. L Indicates the number of streams transmitted; This represents the corrected downlink receive power for each stream. This represents an element in the second beamforming factor.

[0378] In one embodiment, the fifth processing unit 705 is specifically used for:

[0379] The shaping vector is determined using the following formula:

[0380] W = V sort Φ post

[0381] Where W represents the shaping vector, V sort Φ represents the first beamforming factor. post This represents the power allocation coefficient matrix.

[0382] In one embodiment, the fourth processing unit 704 is specifically used for:

[0383] Sort each parameter in the second factor from largest to smallest to obtain the sorting matrix;

[0384] Based on the sorting matrix, each parameter in the first factor is sorted to determine the first beamforming factor.

[0385] In one embodiment, the fourth processing unit 704 is specifically used for:

[0386] The first beamforming factor is determined using the following formula:

[0387] V sort =V comb Ψ

[0388] Among them, V sort V represents the first beamforming factor. comb Let Ψ denote the first factor, and Ψ denote the sorting matrix.

[0389] In one embodiment, the fourth processing unit 704 is specifically used for:

[0390] Sort each parameter in the second factor from largest to smallest to obtain the sorting matrix;

[0391] The second beamforming factor is determined based on each parameter in the sorting matrix and the second factor.

[0392] It should be noted that the apparatus provided in this embodiment of the invention can implement all the method steps implemented in the above method embodiment and can achieve the same technical effect. Therefore, the parts and beneficial effects that are the same as those in the method embodiment will not be described in detail here.

[0393] It should be noted that the division of units in the embodiments of this application is illustrative and only represents one logical functional division. In actual implementation, other division methods may be used. Furthermore, the functional units in the various embodiments of this application can be integrated into one processing unit, or each unit can exist physically separately, or two or more units can be integrated into one unit. The integrated units described above can be implemented in hardware or as software functional units.

[0394] If the integrated unit is implemented as a software functional unit and sold or used as an independent product, it can be stored in a processor-readable storage medium. Based on this understanding, the technical solution of this application, in essence, or the part that contributes to the prior art, or all or part of the technical solution, can be embodied in the form of a software product. This computer software product is stored in a storage medium and includes several instructions to cause a computer device (which may be a personal computer, server, or network device, etc.) or processor to execute all or part of the steps of the methods described in the various embodiments of this application. The aforementioned storage medium includes various media capable of storing program code, such as USB flash drives, portable hard drives, read-only memory (ROM), random access memory (RAM), magnetic disks, or optical disks.

[0395] Based on the same inventive concept, embodiments of this application also provide a processor-readable storage medium storing a computer program, which, when executed by a processor, implements the steps of any beamforming method provided in any embodiment or any optional implementation of this application.

[0396] Processor-readable storage media can be any available medium or data storage device that the processor can access, including but not limited to magnetic storage (e.g., floppy disks, hard disks, magnetic tapes, magneto-optical disks (MOs), etc.), optical storage (e.g., CDs, DVDs, BDs, HVDs, etc.), and semiconductor storage (e.g., ROMs, EPROMs, EEPROMs, non-volatile memory (NAND flash), solid-state drives (SSDs)).

[0397] Those skilled in the art will understand that embodiments of this application can be provided as methods, systems, or computer program products. Therefore, this application can take the form of a completely hardware embodiment, a completely software embodiment, or an embodiment combining software and hardware aspects. Furthermore, this application can take the form of a computer program product implemented on one or more computer-usable storage media (including, but not limited to, disk storage and optical storage) containing computer-usable program code.

[0398] This application is described with reference to flowchart illustrations and / or block diagrams of methods, apparatus (systems), and computer program products according to embodiments of this application. It will be understood that each block of the flowchart illustrations and / or block diagrams, and combinations of blocks in the flowchart illustrations and / or block diagrams, can be implemented by computer-executable instructions. These computer-executable instructions can be provided to a processor of a general-purpose computer, special-purpose computer, embedded processor, or other programmable data processing apparatus to produce a machine, such that the instructions, which execute via the processor of the computer or other programmable data processing apparatus, generate instructions for implementing the flowchart... Figure 1 One or more processes and / or boxes Figure 1 A device that provides the functions specified in one or more boxes.

[0399] These processor-executable instructions may also be stored in a processor-readable memory that can direct a computer or other programmable data processing device to operate in a particular manner, such that the instructions stored in the processor-readable memory produce an article of manufacture including instruction means, which are implemented in a process Figure 1 One or more processes and / or boxes Figure 1 The function specified in one or more boxes.

[0400] These processors can execute instructions that can also be loaded onto a computer or other programmable data processing device, causing a series of operational steps to be performed on the computer or other programmable device to produce a computer-implemented process, thereby providing instructions that execute on the computer or other programmable device for implementing the process. Figure 1 One or more processes and / or boxes Figure 1 The steps of the function specified in one or more boxes.

[0401] Obviously, those skilled in the art can make various modifications and variations to this application without departing from the spirit and scope of this application. Therefore, if such modifications and variations fall within the scope of the claims of this application and their equivalents, this application also intends to include such modifications and variations.

Claims

1. A beamforming method, characterized in that, include: Obtain channel estimation parameters; Based on the channel estimation parameters, the singular values ​​of each stream in the multiple streams of the signal source and the first parameter of each stream are determined, wherein the first parameter of each stream is used to characterize the mapping relationship between each stream and the transmitting antenna; Based on the singular value of each stream and the first parameter of each stream, power allocation is performed between each stream, and a second parameter of each stream is determined. The second parameter of each stream is used to characterize the mapping relationship between each stream and the transmitting antenna after the power allocation between each stream is performed. Based on the second parameter of each stream and the singular value of each stream, perform geometric mean decomposition (GMD) transformation on at least two of the streams, and perform splicing and sorting processing based on the GMD transformation of at least two of the streams to determine the first beamforming factor and the second beamforming factor. Based on the first beamforming factor and the second beamforming factor, a beamforming vector corresponding to the channel estimation parameters is determined, and the beamforming vector is used for beamforming.

2. The method according to claim 1, characterized in that, The step of performing power allocation among the streams based on the singular values ​​of each stream and the first parameter of each stream, and determining the second parameter of each stream, includes: Based on the singular values ​​of each flow, a pre-power allocation coefficient matrix is ​​determined, which is used for power allocation between each flow; The second parameter of each stream is determined based on the previous power allocation coefficient matrix and the first parameter of each stream.

3. The method according to claim 2, characterized in that, The step of determining the pre-power allocation coefficient matrix based on the singular values ​​of each flow includes: The front power allocation coefficient matrix is ​​determined based on the singular value of each flow and the preset inter-flow power allocation coefficient.

4. The method according to claim 3, characterized in that, The step of determining the pre-power allocation coefficient matrix based on the singular values ​​of each flow and a preset inter-flow power allocation coefficient includes: The front power allocation coefficient matrix is ​​determined using the following formula: Where Φ represents the front power allocation coefficient matrix, and Σ represents the singular value matrix for each flow. The diagonal elements of the singular value matrix Σ represent the singular values ​​of each flow, p represents the inter-flow power distribution coefficient, and N L Indicates the number of streams transmitted.

5. The method according to claim 2, characterized in that, The step of determining the second parameter of each stream based on the previous power allocation coefficient matrix and the first parameter of each stream includes: The second parameter of each stream is determined using the following formula: Among them, V PA The elements in the matrix are the second parameters of each flow, where V represents the right singular vector and Φ represents the front power allocation coefficient matrix. This represents the first parameter of each stream, where the first parameter of each stream is an element in V. For elements in Φ, For each of the streams, p represents the inter-stream power allocation coefficient, and N is the second parameter. L Indicates the number of streams transmitted.

6. The method according to claim 1, characterized in that, The step of performing GMD transforms on at least two of the plurality of streams based on the second parameter of each stream and the singular value of each stream, and performing splicing and sorting processing based on the GMD transforms of at least two of the plurality of streams to determine the first beamforming factor and the second beamforming factor includes: The second parameters of at least two of the plurality of streams are subjected to GMD transformation to determine the third parameters of the at least two streams; The first factor is determined by concatenating the third parameters of the at least two streams and the second parameters of the other streams besides the at least two streams. Perform GMD transformation on the singular values ​​of the at least two streams to determine the GMD transformation matrix of the at least two streams; The second factor is determined by concatenating the matrices after GMD transformation of the at least two streams and the singular values ​​of the other streams besides the at least two streams. Sort each parameter in the first factor to determine the first beamforming factor; The second beamforming factor is determined by sorting each parameter in the second factor.

7. The method according to claim 6, characterized in that, The step of performing GMD transformation on the second parameters of at least two of the plurality of streams to determine the third parameters of the at least two streams includes: The third parameter of the at least two streams is determined using the following formula: P′=V′G′1 Wherein, the elements in P′ are the third parameters of the at least two streams, the elements in V′ are the second parameters of the at least two streams, and G′1 represents the GMD transformation matrix of V′.

8. The method according to claim 6, characterized in that, The step of concatenating the third parameters of the at least two streams and the second parameters of the other streams besides the at least two streams to determine the first factor includes: The first factor is determined using the following formula: Among them, V comb Indicates the first factor. The elements in P' are the second parameters of the other streams besides the at least two streams, and the elements in P' are the third parameters of the at least two streams.

9. The method according to claim 6, characterized in that, The step of concatenating the matrices obtained from the GMD transformation of the at least two streams and the singular values ​​of the other streams besides the at least two streams to determine the second factor includes: The second factor is determined using the following formula: Among them, R comb Indicates the second factor. The elements in are the singular values ​​of the other streams besides the at least two streams, and R′ represents the matrix after the GMD transformation of the at least two streams.

10. The method according to claim 1, characterized in that, The step of determining the beamforming vector corresponding to the channel estimation parameters based on the first beamforming factor and the second beamforming factor includes: The power allocation coefficient matrix is ​​determined based on the second beamforming factor. Based on the post-power allocation coefficient matrix and the first beamforming factor, the beamforming vector corresponding to the channel estimation parameters is determined.

11. The method according to claim 10, characterized in that, The step of determining the power allocation coefficient matrix based on the second beamforming factor includes: The downlink receive power of each stream is determined based on the second beamforming factor; The corrected downlink receive power of each stream is determined based on the downlink receive power of each stream and a preset power correction factor. The power allocation coefficient matrix is ​​determined based on the corrected downlink received power of each stream and the second beamforming factor.

12. The method according to claim 11, characterized in that, Determining the downlink receive power of each stream based on the second beamforming factor includes: The downlink receive power of each stream is determined using the following formula: In this context, K contains the downlink received power for each stream, diag(·) denotes the diagonal element operation, and R... sort This represents the second beamforming factor. R represents sort The conjugate transpose of .

13. The method according to claim 11, characterized in that, The step of determining the corrected downlink receive power for each stream based on the downlink receive power of each stream and a preset power correction factor includes: The corrected downlink receive power for each stream is determined using the following formula: Wherein, the elements in K represent the downlink received power of each stream. Let K represent the downlink received power of each stream, ξ represent the power correction factor, and K represent the downlink received power. ξ The elements in the table represent the corrected downlink receive power for each stream. N represents the corrected downlink receive power for each stream. L Indicates the number of streams transmitted.

14. The method according to claim 11, characterized in that, The step of determining the power allocation coefficient matrix based on the corrected downlink received power of each stream and the second beamforming factor includes: The power allocation coefficient matrix is ​​determined using the following formula: in, Where, Φ post Denotes the post-power allocation coefficient matrix, Φ post diagonal elements in N represents the inter-flow power allocation factor for each flow. L Indicates the number of streams transmitted; This represents the corrected downlink receive power for each stream. This represents an element in the second beamforming factor.

15. The method according to claim 10, characterized in that, The step of determining the beamforming vector corresponding to the channel estimation parameters based on the post-power allocation coefficient matrix and the first beamforming factor includes: The shaping vector is determined using the following formula: W=V sort Φ post Where W represents the shaping vector, V sort Φ represents the first beamforming factor. post This represents the power allocation coefficient matrix.

16. The method according to claim 6, characterized in that, The step of sorting each parameter in the first factor to determine the first beamforming factor includes: Sort each parameter in the second factor from largest to smallest to obtain a sorting matrix; Based on the sorting matrix, each parameter in the first factor is sorted to determine the first beamforming factor.

17. The method according to claim 16, characterized in that, The step of sorting each parameter in the first factor according to the sorting matrix to determine the first beamforming factor includes: The first beamforming factor is determined using the following formula: V sort =V comb Ψ Among them, V sort V represents the first beamforming factor. comb Let Ψ represent the first factor, and let Ψ represent the sorting matrix.

18. The method according to claim 6, characterized in that, The step of sorting each parameter in the second factor to determine the second beamforming factor includes: Sort each parameter in the second factor from largest to smallest to obtain a sorting matrix; The second beamforming factor is determined based on the sorting matrix and each parameter in the second factor.

19. A beamforming device, characterized in that, Includes memory, transceiver, and processor: The memory is used to store computer programs; the transceiver is used to send and receive data under the control of the processor. Processor, configured to read the computer program in the memory and perform the following operations: Obtain channel estimation parameters; Based on the channel estimation parameters, the singular values ​​of each stream in the multiple streams of the signal source and the first parameter of each stream are determined, wherein the first parameter of each stream is used to characterize the mapping relationship between each stream and the transmitting antenna; Based on the singular value of each stream and the first parameter of each stream, power allocation is performed between each stream, and a second parameter of each stream is determined. The second parameter of each stream is used to characterize the mapping relationship between each stream and the transmit antenna after the power allocation between each stream is performed. Based on the second parameter of each stream and the singular value of each stream, perform GMD transformation on at least two of the multiple streams, and perform splicing and sorting processing based on the GMD transformation of at least two of the multiple streams to determine the first beamforming factor and the second beamforming factor. Based on the first beamforming factor and the second beamforming factor, a beamforming vector corresponding to the channel estimation parameters is determined, and the beamforming vector is used for beamforming.

20. A beamforming device, characterized in that, include: The first processing unit is used to obtain channel estimation parameters; The second processing unit is configured to determine the singular value of each stream in the multiple streams of the signal source and the first parameter of each stream based on the channel estimation parameters. The first parameter of each stream is used to characterize the mapping relationship between each stream and the transmitting antenna. The third processing unit is configured to perform power allocation between each stream based on the singular value of each stream and the first parameter of each stream, and determine the second parameter of each stream. The second parameter of each stream is used to characterize the mapping relationship between each stream and the transmitting antenna after the power allocation between each stream is performed. The fourth processing unit is used to perform GMD transformation on at least two of the plurality of streams based on the second parameter of each stream and the singular value of each stream, and to perform splicing and sorting processing based on the GMD transformation of at least two of the plurality of streams to determine the first beamforming factor and the second beamforming factor. The fifth processing unit is configured to determine a beamforming vector corresponding to the channel estimation parameters based on the first beamforming factor and the second beamforming factor, wherein the beamforming vector is used for beamforming.

21. A processor-readable storage medium, characterized in that, The processor-readable storage medium stores a computer program for causing the processor to perform the method of any one of claims 1 to 18.

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