Near-field beam training method, electronic device, and computer-readable storage medium

Abstract

The embodiment of the present invention provides a near-field beam training method, an electronic device and a computer-readable storage medium. The method includes: obtaining a far-field codebook; performing beam scanning and candidate angle estimation processing based on the far-field codebook to obtain a user candidate angle index set; setting a polar codebook according to the user candidate angle index set, wherein each codeword in the polar codebook corresponds to a beam to be selected, and the beam to be selected carries direction information and distance information; performing effective distance estimation processing on the user candidate angle index set based on the direction information and distance information to obtain the optimal polar codeword. According to the scheme of the embodiment of the present invention, the training overhead of beam training can be significantly reduced, so that there is more sufficient time for subsequent data transmission, and the two-stage near-field beam training method of the present invention can be applied to far-field and near-field communication systems, and has extremely high practical significance.

Description

Technical Field

[0001] The present invention relates to the field of communication technology, and in particular to a near-field beam training method, an electronic device and a computer-readable storage medium. Background Art

[0002] Very large arrays / surfaces with active or passive elements have emerged as a promising technology to significantly improve the spectral efficiency and spatial resolution of future sixth-generation wireless networks. Compared with the massive multiple-input and multiple-output of the fifth generation, the very large arrays of 6G introduce several new channel characteristics. Specifically, as the number of antennas and carrier frequency increase, users are more likely to be located in the near-field region with a spherical wavefront propagation model because the user / link distance is smaller than the increased Rayleigh distance. Therefore, traditional transceiver designs based on the far-field channel model with a plane wavefront assumption may not be applicable to very large array communications.

[0003] In particular, in order to obtain the significant beamforming gain brought by the very large-scale array, the very large-scale array must perform near-field beam training to establish an initial link with a high signal-to-noise ratio before effective channel estimation and data transmission. Compared with the traditional far-field beam training method that aims to find the optimal beam direction based on a pre-defined angular domain beam codebook, the near-field beam training requires a new codebook design and effectively searches for beams that match specific channel angles and distances based on the spherical wavefront model. Therefore, directly applying the traditional far-field beam training method to the near-field communication system will lead to a significant performance degradation, especially when the user is very close to the very large-scale array. Since near-field communication is based on the spherical wavefront propagation model, near-field beam training requires determining the angle and distance of the signal source, but the current near-field beam training based on the two-dimensional exhaustive search method has a relatively large training overhead, resulting in insufficient time for subsequent data transmission. Summary of the invention

[0004] The present invention aims to solve at least one of the technical problems existing in the prior art.

[0005] To this end, the present invention proposes a near-field beam training method, which can significantly reduce the training overhead of beam training, so that there is more sufficient time for subsequent data transmission. Moreover, the two-stage near-field beam training method of the present invention can be applied to far-field and near-field communication systems, and has extremely high practical significance.

[0006] The present invention also provides an electronic device using the above-mentioned near-field beam training method.

[0007] The present invention also proposes a computer-readable storage medium that applies the above-mentioned near-field beam training method.

[0008] According to a near-field beam training method of an embodiment of the first aspect of the present invention, the method comprises:

[0009] Acquire a far-field codebook, wherein the far-field codebook is used to represent a codebook used for beam training when the user terminal is located in a far-field area of ​​the base station;

[0010] Performing beam scanning and candidate angle estimation processing based on the far-field codebook to obtain a user candidate angle index set;

[0011] A polar domain codebook is set according to the user candidate angle index set, wherein each codeword in the polar domain codebook corresponds to a beam to be selected, and the beam to be selected carries direction information and distance information;

[0012] An effective distance estimation process is performed on the user candidate angle index set based on the direction information and the distance information to obtain an optimal polar field codeword, wherein the optimal polar field codeword is an optimal codeword in the polar field codebook.

[0013] According to the near-field beam training method of the embodiment of the present invention, there are at least the following beneficial effects: in the process of near-field beam training, a far-field codebook is first obtained, wherein the far-field codebook is used to characterize the codebook used for beam training when the user terminal is located in the far-field area of ​​the base station; then beam scanning and candidate angle estimation processing are performed based on the far-field codebook to obtain a user candidate angle index set; then a polar domain codebook is set according to the user candidate angle index set, wherein each codeword in the polar domain codebook corresponds to a beam to be selected, and each beam to be selected carries direction information and distance information; finally, effective distance estimation processing is performed on the user candidate angle index set based on the direction information and distance information to obtain the optimal polar domain codeword; through the above technical scheme, the training overhead of beam training can be significantly reduced, so that there is more sufficient time for data transmission in the subsequent period, and the two-stage near-field beam training method of the present invention can be applicable to far-field and near-field communication systems, and has extremely high practical significance.

[0014] According to some embodiments of the present invention, the performing beam scanning and candidate angle estimation processing based on the far-field codebook to obtain a user candidate angle index set includes:

[0015] Performing angle domain beam scanning processing based on the far-field codebook to obtain a first received signal;

[0016] Performing angle estimation processing on the first received signal to obtain a dominant angle region;

[0017] Based on a preset selection rule, the user candidate angle index set is determined from the dominant angle area.

[0018] According to some embodiments of the present invention, performing effective distance estimation processing on the user candidate angle index set based on the direction information and the distance information to obtain an optimal polar field codeword includes:

[0019] Performing range-domain beam scanning processing on the user candidate angle index set based on the direction information and the distance information to obtain a second received signal;

[0020] The second received signal is subjected to beamforming processing to obtain the optimal polar field codeword.

[0021] According to some embodiments of the present invention, the determining the user candidate angle index set from the dominant angle region based on a preset selection rule includes:

[0022] Obtain candidate space angle selection parameters;

[0023] The dominant angle region is adjusted based on the candidate space angle selection parameter to obtain the user candidate angle index set.

[0024] According to some embodiments of the present invention, the second received signal is represented as follows:

[0025]

[0026] in, It is expressed as a polar domain codeword, N represents the number of base station antennas, h represents the complex channel gain, and b H (θ,r) represents the near-field steering vector, represents the sampling distance, θ k represents the candidate angle, z0 represents the power received by the user end is σ 2 Additive Gaussian white noise, x represents the signal with base station transmission power P, represents the base station beamforming vector, θ represents the spatial angle from the user end to the base station, and r represents the distance from the base station to the user end.

[0027] According to some embodiments of the present invention, the index of the optimal extreme field codeword is expressed as follows:

[0028]

[0029] in, Represented as a polar codeword, represents the second received signal received by the user terminal, Ξ represents the user candidate angle index set, K represents the number of candidate spatial angles, s k =0,1,2,3,…; represents a non-uniform distance index set, Represents the index of the optimal extreme field codeword.

[0030] According to some embodiments of the present invention, the first received signal is represented as follows:

[0031]

[0032] Among them, w n represents the codeword in the far-field codebook, z0 represents the power received by the user end is σ 2 Additive Gaussian white noise, b H (θ, r) represents the near-field steering vector, x represents the signal with power P transmitted by the base station, N represents the number of base station antennas, h represents the channel gain in complex form, and θ n Indicates the central direction in which the entire spatial domain is divided into N sectors of equal size, a(θ n ) indicates the direction of the center θ n The transmitting beam of θ represents the spatial angle from the user end to the base station, and r represents the distance from the base station to the user end.

[0033] According to some embodiments of the present invention, the dominant angle region is expressed as follows:

[0034]

[0035] Among them, w n represents the codeword in the far-field codebook, y(w n ) represents the first received signal, w represents the optimal codeword in the far-field codebook, ρ∈(0,1) represents the beam gain threshold of the near-field steering vector, and n=1,2,…,N.

[0036] An electronic device according to an embodiment of the second aspect of the present invention includes:

[0037] A memory, a processor, and a computer program stored in the memory and executable on the processor, wherein when the processor executes the computer program, the near-field beam training method as described above is implemented.

[0038] According to a computer-readable storage medium of an embodiment of the third aspect of the present invention, the computer-readable storage medium stores computer-executable instructions, and when the computer-executable instructions are executed by a control processor, the near-field beam training method as described above is implemented.

[0039] Other features and advantages of the present invention will be described in the following description, and partly become apparent from the description, or understood by practicing the present invention. The purpose and other advantages of the present invention can be realized and obtained by the structures particularly pointed out in the description, claims and drawings. BRIEF DESCRIPTION OF THE DRAWINGS

[0040] The accompanying drawings are used to provide further understanding of the technical solution of the present disclosure and constitute a part of the specification. Together with the embodiments of the present disclosure, they are used to explain the technical solution of the present disclosure and do not constitute a limitation on the technical solution of the present disclosure.

[0041] Figure 1 is a flow chart of a near-field beam training method provided by an embodiment of the present invention;

[0042] Figure 2 is a specific flow chart of candidate angle estimation of a near-field beam training method provided by an embodiment of the present invention;

[0043] Figure 3 It is a specific flow chart of effective distance estimation of a near-field beam training method provided by an embodiment of the present invention;

[0044] Figure 4 It is a specific flow chart of obtaining a user candidate angle index set of a near-field beam training method provided by an embodiment of the present invention;

[0045] Figure 5 A narrowband ultra-large-scale array communication system provided by an embodiment of the present invention;

[0046] Figure 6 1 is a schematic diagram of the relationship between the normalized beam gain of a far-field beamforming vector and the spatial angle under the far-field and near-field channel models provided by an embodiment of the present invention;

[0047] Figure 7 It is a schematic diagram of the structure of an electronic device provided by an embodiment of the present invention. DETAILED DESCRIPTION

[0048] In order to make the purpose, technical solution and advantages of the present invention more clearly understood, the present invention is further described in detail below in conjunction with the accompanying drawings and embodiments. It should be understood that the specific embodiments described herein are only used to explain the present invention and are not used to limit the present invention.

[0049] In the description of the present invention, "several" means one or more, "more" means more than two, "greater than", "less than", "exceed" etc. are understood as not including the number itself, and "above", "below", "within" etc. are understood as including the number itself. If there is a description of "first" or "second", it is only used for the purpose of distinguishing the technical features, and cannot be understood as indicating or implying the relative importance or implicitly indicating the number of the indicated technical features or implicitly indicating the order of the indicated technical features.

[0050] In the description of the present invention, unless otherwise clearly defined, terms such as setting, installing, connecting, etc. should be understood in a broad sense, and technicians in the relevant technical field can reasonably determine the specific meanings of the above terms in the present invention based on the specific content of the technical solution.

[0051] The present invention provides a near-field beam training method, an electronic device and a computer-readable storage medium, the method comprising: obtaining a far-field codebook and a polar domain codebook; performing candidate angle estimation processing on the beam based on the far-field codebook to obtain a user candidate angle index set; performing effective distance estimation processing on the user candidate angle index set based on the polar domain codebook to obtain an optimal polar domain codeword; through the above technical solution, the training overhead of beam training can be reduced, so that there is more sufficient time for subsequent data transmission.

[0052] The embodiments of the present invention are further described below in conjunction with the accompanying drawings.

[0053] like Figure 1 As shown, Figure 1 1 is a flow chart of a near-field beam training method provided by an embodiment of the present invention. The method includes but is not limited to step S100, step S200, step S300 and step S400:

[0054] Step S100, obtaining a far-field codebook, wherein the far-field codebook is used to represent a codebook used for beam training when the user terminal is located in a far-field area of ​​the base station;

[0055] Step S200, performing beam scanning and candidate angle estimation processing based on the far-field codebook to obtain a user candidate angle index set;

[0056] Step S300, setting a polar domain codebook according to the user candidate angle index set, wherein each codeword in the polar domain codebook corresponds to a beam to be selected, and the beam to be selected carries direction information and distance information;

[0057] Step S400, performing effective distance estimation processing on the user candidate angle index set based on the direction information and the distance information to obtain an optimal polar field codeword, wherein the optimal polar field codeword is the optimal codeword in the polar field codebook.

[0058] It should be noted that, in the process of near-field beam training, the far-field codebook is first obtained; then beam scanning and candidate angle estimation processing are performed based on the far-field codebook to obtain a user candidate angle index set; then the polar domain codebook is set according to the user candidate angle index set, wherein each codeword in the polar domain codebook corresponds to a pending beam, and the pending beam carries direction information and distance information; finally, based on the direction information and distance information, the user candidate angle index set is effectively estimated, and finally the optimal polar domain codeword is obtained; through the above technical solution, the training overhead of beam training can be significantly reduced, so that there is more sufficient time for subsequent data transmission, and the two-stage near-field beam training method of the present invention can be applicable to far-field and near-field communication systems, and has extremely high practical significance.

[0059] It is worth noting that the far-field codebook is used to characterize the codebook used for beam training when the user terminal is located in the far-field area of ​​the base station; the polar codebook is customized according to the user candidate angle index set and can be customized manually. The pending beam carries direction information and distance information, where the direction information can be angle information, and for a pending beam, the direction information and distance information appear in pairs.

[0060] It should be noted that beam training is also commonly referred to as beam alignment; beam training uses simulated transmit beams and receive beams to detect the millimeter-wave large-scale multi-input multi-output channel, looking for the transmit-receive beam combination with the largest received signal energy, that is, the beam pair that is most suitable for the channel transmission, thereby avoiding direct estimation of the large-dimensional air interface channel. When beam training is completed, a small-dimensional equivalent channel matrix is ​​formed, and only a small number of pilots are needed to perform fast estimation based on least squares or minimum mean square error.

[0061] It is worth noting that in problems such as multi-input multi-output channel estimation and beam training, codebooks are often required, and the remote codebook in the embodiment of the present application refers to the codebook set for the far-field beam training corresponding to the base station, where electromagnetic radiation can be divided into the far-field area and the near-field area. Specifically, when the distance between the base station and the user is greater than the Rayleigh distance, the user will be considered to be in the far-field area, and when the distance between the base station and the user is less than the Rayleigh distance, the user will be considered to be in the near-field area; the polar codebook can be a codebook set by the tester according to the actual needs. Among them, the user of this application can be a mobile phone or other mobile device.

[0062] It is worth noting that the actual spatial direction of the user is roughly in the middle of the dominant angular region, so the near-field beam training can be divided into two consecutive parts: candidate angle estimation and effective distance estimation; the first stage determines the user's candidate angle based on the far-field codebook and angle domain beam scanning. Then, the second stage uses a customized extreme domain codebook to find the user's optimal effective distance given the candidate angle, rather than using the full angle domain as in an exhaustive search. The main advantage of the present invention over the best prior art is that it greatly reduces the training overhead of the best prior art, while also achieving beamforming performance comparable to the best prior art.

[0063] It is worth noting that the near-field beam training method provided in the embodiment of the present application can be applied to far-field and near-field communication systems, and has extremely high practical significance.

[0064] In addition, in one embodiment, if Figure 2 As shown, the above step S200 may include but is not limited to step S210, step S220 and step S230.

[0065] Step S210, performing angle domain beam scanning processing based on the far-field codebook to obtain a first received signal;

[0066] Step S220, performing angle estimation processing on the first received signal to obtain a dominant angle region;

[0067] Step S230: Based on a preset selection rule, a user candidate angle index set is determined from the dominant angle region.

[0068] It should be noted that in the process of estimating the candidate angles of the beam, the first received signal can be obtained by first performing angle domain beam scanning processing based on the far-field codebook; then, the first received signal is subjected to angle estimation processing to obtain the dominant angle area; finally, according to the preset selection rules, the user candidate angle index set is determined from the dominant angle area.

[0069] It is worth noting that the base station sends several training symbols in sequence and dynamically adjusts the beam direction according to the preset far-field codebook, where the beam direction is specified by the codeword in the far-field codebook. According to each codeword, the user end can receive the first received signal. After the first stage of beam scanning is completed, angle estimation processing can also be performed based on the first received signal to obtain the dominant angle area; finally, based on the preset selection rules, the user candidate angle index set is determined from the dominant angle area.

[0070] In addition, in one embodiment, if Figure 3 As shown, the above step S400 may include but is not limited to step S410 and step S420.

[0071] Step S410, performing range domain beam scanning processing on the user candidate angle index set based on the direction information and the distance information to obtain a second received signal;

[0072] Step S420: Perform beamforming processing on the second received signal to obtain an optimal polar field codeword.

[0073] It should be noted that in the process of obtaining the optimal polar domain codeword, the user candidate angle index set is first subjected to distance domain beam scanning processing based on the direction information and distance information to obtain the second received signal; then the second received signal is subjected to beam measurement processing to obtain the optimal polar domain codeword.

[0074] It is worth noting that the direction information may be the angle information between the base station and the user terminal, and the distance information may represent the distance between the base station and the user terminal.

[0075] It is worth noting that after the range domain beam scanning process, the optimal range domain codeword can be determined based on the signal power or signal-to-noise ratio of the received second received signal.

[0076] In addition, in one embodiment, if Figure 4 As shown, the above step S230 includes but is not limited to step S231 and step S232.

[0077] Step S231, obtaining candidate space angle selection parameters;

[0078] Step S232: adjusting the dominant angle region based on the candidate space angle selection parameter to obtain a user candidate angle index set.

[0079] It should be noted that, in the process of obtaining the user candidate angle index set, the candidate space angle selection parameters are first obtained, and then the dominant angle region can be adjusted based on the candidate space angle selection parameters, and then the user candidate angle index set can be obtained.

[0080] It is worth noting that due to the influence of power fluctuation and receiving noise, the middle angle of the dominant angle area obtained above may not be accurate enough. In order to solve this problem, a candidate spatial angle selection parameter can be set, and then the number of candidate spatial angles of the candidate spatial angle selection parameter is selected in the middle position of the quantized dominant angle area instead of selecting only one spatial angle, so as to obtain a user candidate angle index set.

[0081] In some embodiments, the second received signal is represented as follows:

[0082]

[0083] in, It is expressed as a polar domain codeword, N represents the number of base station antennas, h represents the complex channel gain, and b H (θ,r) represents the near-field steering vector, represents the sampling distance, θ k represents the candidate angle, z0 represents the power received by the user end is σ 2 Additive Gaussian white noise, x represents the signal with power P transmitted by the base station, represents the base station beamforming vector, θ represents the spatial angle from the user end to the base station, and r represents the distance from the base station to the user end.

[0084] In some embodiments, the index of the best domain codeword is represented as follows:

[0085]

[0086] in, Represented as a polar codeword, represents the second received signal received by the user end, Ξ represents the user candidate angle index set, K represents the number of candidate spatial angles, s k=0,1,2,3,…; represents a non-uniform distance index set, Represents the index of the optimal extreme field codeword.

[0087] In some embodiments, the first received signal is represented as follows:

[0088]

[0089] Among them, w n represents the codeword in the far-field codebook, and z0 represents the power received by the user end as σ 2 Additive Gaussian white noise, b H (θ, r) represents the near-field steering vector, x represents the signal with power P transmitted by the base station, N represents the number of base station antennas, h represents the channel gain in complex form, and θ n Indicates the central direction in which the entire spatial domain is divided into N sectors of equal size, a(θ n ) indicates the direction of the center θ n The transmitting beam of the base station is θ, θ represents the spatial angle from the base station to the user end, and r represents the distance from the base station to the user end.

[0090] In some embodiments, the dominant angular region is represented as follows:

[0091]

[0092] Among them, w n represents the codeword in the far-field codebook, y(w n ) represents the first received signal, w represents the optimal codeword in the far-field codebook, ρ∈(0,1) represents the beam gain threshold of the near-field steering vector, and n=1,2,…,N.

[0093] In order to more clearly illustrate the near-field beam training method provided by the embodiment of the present invention, a specific example is given below for illustration.

[0094] like Figure 5 As shown, an embodiment of the present invention provides a downlink beam training for a narrowband ultra-large-scale array communication system, wherein a base station configured with a passive uniform linear array of N antennas communicates with a single-antenna user.

[0095] This application proposes a communication near-field channel model. Generally speaking, the electromagnetic radiation field can be divided into far-field and near-field regions, resulting in different channel characteristics. Specifically, when the distance between the base station and the user is greater than the well-known Rayleigh distance is the antenna array aperture, λ is the carrier wavelength), the user is in the far field. When the user distance is less than the Rayleigh distance, it is in the near field. Especially for ultra-large-scale array communication systems in high frequency bands (such as millimeter wave / terahertz), for example, when D = 0.4m and f = 100GHz, the Rayleigh distance Z is about 107m, so the user is usually in the near field, and its channel modeling is as follows.

[0096] Without loss of generality, a base station with N antennas is placed on the y-axis, and the coordinates of the nth antenna are (0, δ n d). Among them represents the spacing between antennas. Then, based on the spherical wavefront propagation model, the near-field line-of-sight (LoS) channel from the base station to the user is expressed as It can be modeled as

[0097]

[0098] here represents the channel gain in complex form, where β and r represent the reference channel gain at a distance of 1 m between the center of the base station and the user and the distance between the center of the base station and the user, respectively. H (θ,r) represents the near-field steering vector,

[0099]

[0100] Where θ represents the spatial angle, Here φ represents the physical angle from the center of the base station to the user (angle-of-departure, AoD). Indicates the nth antenna of the base station, i.e. (0, δ n d) Distance from the user.

[0101] For the signal model, based on the above formula, the signal received by the user end is given by the following formula

[0102]

[0103] in, Indicates that the power of the base station transmitting signal x is P, v∈C N×1 represents the transmit beamforming vector at the base station based on the power-efficient analog phase shifter, and z0 is the power σ received by the user end. 2 Additive white Gaussian noise.

[0104] For near-field beam training, the optimal base station beamforming vector v can be easily obtained opt= b(θ, r). This indicates that the optimal beam training codeword should align both the spatial angle θ and the distance r from the base station to the user, which is significantly different from the traditional far-field beam training method.

[0105] First, the following key definitions are made.

[0106] Definition 1: Define A(u H ,w) is the beamforming vector w along the channel steering vector u H The normalized beam gain of is given by

[0107]

[0108] Definition 2: Define w(Ω) as the far-field beamforming vector function of the spatial angle Ω∈[-1,1]. Then, let Indicates b H The dominant angular region of (θ,r) (the near-field steering vector) characterizes the region where the use of the far-field beamforming vector w can result in b H (θ, r) is the spatial angular region where the beam power is sufficiently high. Mathematically, Given by the following formula

[0109]

[0110] where ρ∈(0,1) is b H The beam gain threshold of (θ, r). In particular, ρ can be set to Corresponding to the 3dB dominant angle region.

[0111] Among them, Figure 6 The relationship between the normalized beam gain of the far-field beamforming vector w and the spatial angle under the far-field and near-field channel models is shown in An important observation is given below.

[0112] Among them, the traditional far-field beam training method and its direct application to near-field beam training have problems. Based on the plane wavefront assumption, the far-field channel model Can be characterized as

[0113]

[0114] Among them, a H (θ) represents the far-field steering vector

[0115]

[0116] The signal received by the user end can be characterized as:

[0117]

[0118] For classic far-field beam training, the entire spatial domain [-1,1] is divided into N sectors of equal size, and the central direction can be expressed as Therefore, the far-field codebook consisting of N codewords can be constructed as W = {w1, w2, ..., w N}, each codeword w n Corresponding to the center direction θ n The transmit beam, that is, w n =a(θ n ). Then, the BS selects N codewords from the codebook as transmission beamforming vectors on the training symbols in turn. Finally, the user measures its received signal power varying with time and feeds back the codeword index that results in the maximum received signal power.

[0119] exist Figure 6 In the example, based on the far-field beamforming vector w, the user's true spatial angle θ is approximately located in the middle of the dominant angle region. Mathematically, we get

[0120] w(Ω) along the far-field (dashed line) and near-field (solid line) beam steering vectors, i.e., a H (·) and b H (·), Normalized beam gains at four spatial angles (indicated by black dashed lines), where the number of base station antennas is 256 and the carrier frequency is 100 GHz. The base station user distances in the near field and far field are set to 1 m and 100 m, respectively.

[0121] By using the traditional far-field beam training method, the real spatial angle of the near-field user can be approximated. Based on this, a new two-stage near-field beam training method is proposed. The core idea is to first estimate the candidate spatial angle based on the far-field codebook, and then perform effective distance estimation based on the customized polar codebook in the second stage. The detailed process of the two stages is described as follows.

[0122] In the first stage, the aim is to estimate the spatial angle of the user based on the far-field beam training method. Specifically, an angular domain codebook W is constructed, where each codeword points to a spatial direction.

[0123] Angle domain beam scanning: The base station sends N training symbols in sequence and simultaneously uses the predefined angle domain codebook W = {w1, w2, …, w N} Dynamically adjust the beam direction (specified by the codeword). For each codeword w n , the signal received by the user end is given by

[0124]

[0125] Candidate angle estimation: After beam scanning, based on Definition 2, the codeword index set (i.e., the dominant angle region) where the user receives significant high power is recorded as Ψ, which is given by Ψ = {n||y(w n )| 2 >ρ 2 max w |y(w)| 2} given.

[0126] It is worth noting that due to power fluctuations, reception noise, and the approximation in the above observations, the obtained middle angle of the dominant angle region may not be accurate enough. To solve this problem, a new middle K candidate angle selection scheme is proposed. This scheme selects K candidate spatial angles at the middle position of the quantized dominant angle region instead of selecting only one spatial angle. Specifically, let Ξ denote the candidate angle index set, and Represented by, where K represents the number of candidate spatial angles.

[0127] Phase 2 (Effective Distance Estimation): Based on the candidate angle index set Ξ obtained in the first phase, a customized polar domain beam training method based on a non-uniform distance sampling method is proposed for estimating the effective user distance in the second phase. It is worth noting that the effective user distance is defined as the optimal sampling distance corresponding to the user in the polar domain codebook. Due to the limited number of sampling times, this distance may not be the actual distance from the base station to the user. Specifically, the polar domain codebook F is used, which is composed of The codewords are composed of a group of codewords, each of which corresponds to a specific angle-distance pair.

[0128] Range domain beam scanning: The base station sends K groups of pilot symbols to the user. For each candidate angle θ k ,k∈Ξ, the sampling distance is given by

[0129]

[0130] in is the threshold distance defined to limit the column coherence between two near-field steering vectors. Its corresponding non-uniform distance index set is It is expressed as follows:

[0131]

[0132] Then, given the polar codeword The received signal at the user end is expressed as

[0133]

[0134] Beam determination: After the second phase of range domain beam scanning, the user determines its best polar domain beam codeword based on its received signal power / signal-to-noise ratio, expressed as Mathematically, the index of the best polar codeword is given by:

[0135]

[0136] Therefore, the direction and distance of the optimal beam are determined by Given.

[0137] The embodiment of the present application first gives an important observation, that is, the user's actual spatial angle θ is approximately located in the middle of the newly defined dominant angle area. Based on this, the two-dimensional search is decomposed into two consecutive stages.

[0138] Stage 1 (Candidate Angle Estimation)

[0139] Angle domain beam scanning: Use the traditional far-field codebook (angle domain codebook) to perform beam scanning to obtain the user's dominant angular area.

[0140] Candidate angle estimation: According to the proposed intermediate K candidate angle principle, a set of user candidate angle indexes is determined.

[0141] Phase 2 (Effective Distance Estimation)

[0142] Range domain beam scanning: Use a customized polar codebook for range domain beam scanning.

[0143] Beam determination: The user determines the best beam code based on the received signal power or signal-to-noise ratio.

[0144] Through the above technical solution, the first stage determines the candidate angles of the user based on the far-field codebook and angle domain beam scanning. Then, the second stage uses a customized far-field codebook to find the optimal effective distance of the user given the candidate angle, instead of using the full angle domain as in an exhaustive search. The main advantage of this application over the prior art is that it greatly reduces the training overhead of the best prior art, while also achieving beamforming performance comparable to the best prior art.

[0145] In some embodiments of the present invention, Figure 7 As shown, an embodiment of the present invention further provides an electronic device 700, including: a memory 720, a processor 710, and a computer program stored in the memory 720 and executable on the processor 710. When the processor 710 executes the computer program, the near-field beam training method in the above embodiment is implemented, for example, the above-described Figure 1 Steps S100 to S400 of the method, Figure 2 Steps S210 to S230 of the method, Figure 3 Method steps S410 to S420 and Figure 4It should be noted that the electronic device in the embodiment of the present invention may be a base station.

[0146] In some embodiments of the present invention, an embodiment of the present invention further provides a computer-readable storage medium, which stores computer-executable instructions, and the computer-executable instructions are executed by a processor or controller, for example, by a processor in the above-mentioned device embodiment, so that the above-mentioned processor can execute the near-field beam training method in the above-mentioned embodiment, for example, execute the above-mentioned Figure 1 Steps S100 to S400 of the method, Figure 2 Steps S210 to S230 of the method, Figure 3 Method steps S410 to S420 and Figure 4 Method steps S231 to S232 in .

[0147] It will be appreciated by those skilled in the art that all or some of the steps and systems in the disclosed method above may be implemented as software, firmware, hardware and appropriate combinations thereof. Some physical components or all physical components may be implemented as software executed by a processor, such as a central processing unit, a digital signal processor or a microprocessor, or may be implemented as hardware, or may be implemented as an integrated circuit, such as an application specific integrated circuit. Such software may be distributed on a computer-readable medium, which may include a computer storage medium (or a non-transitory medium) and a communication medium (or a temporary medium). As known to those skilled in the art, the term computer storage medium includes volatile and non-volatile, removable and non-removable media implemented in any method or technology for storing information (such as computer-readable instructions, data structures, program modules or other data). Computer storage media include, but are not limited to, RAM, ROM, EEPROM, flash memory or other memory technologies, CD-ROM, digital versatile disks (DVD) or other optical disk storage, magnetic cassettes, magnetic tapes, disk storage or other magnetic storage devices, or any other medium that may be used to store desired information and may be accessed by a computer. Furthermore, it is well known to those skilled in the art that communication media typically embodies computer readable instructions, data structures, program modules, or other data in a modulated data signal such as a carrier wave or other transport mechanism, and may include any information delivery media.

[0148] The above is a specific description of the preferred implementation of the present invention, but the present invention is not limited to the above-mentioned implementation mode. Technical personnel familiar with the field can also make various equivalent deformations or substitutions without violating the spirit of the present invention. These equivalent deformations or substitutions are all included in the scope defined by the claims of the present invention.

Claims

1. A near-field beam training method, characterized in that: The method comprises: Acquire a far-field codebook, wherein the far-field codebook is used to represent a codebook used for beam training when the user terminal is located in a far-field area of ​​the base station; Performing beam scanning and candidate angle estimation processing based on the far-field codebook to obtain a user candidate angle index set; Setting a polar domain codebook according to the user candidate angle index set, wherein each codeword in the polar domain codebook corresponds to a beam to be selected, and the beam to be selected carries direction information and distance information; Performing effective distance estimation processing on the user candidate angle index set based on the direction information and the distance information to obtain an optimal polar domain codeword, wherein the optimal polar domain codeword is an optimal codeword in the polar domain codebook; The performing of beam scanning and candidate angle estimation processing based on the far-field codebook to obtain a user candidate angle index set includes: Performing angle domain beam scanning processing based on the far-field codebook to obtain a first received signal; Performing angle estimation processing on the first received signal to obtain a dominant angle region; Based on a preset selection rule, determining the user candidate angle index set from the dominant angle area; The performing effective distance estimation processing on the user candidate angle index set based on the direction information and the distance information to obtain an optimal polar field codeword includes: Performing range-domain beam scanning processing on the user candidate angle index set based on the direction information and the distance information to obtain a second received signal; The second received signal is subjected to beamforming processing to obtain the optimal polar field codeword.

2. The near-field beam training method according to claim 1, characterized in that: The step of determining the user candidate angle index set from the dominant angle region based on a preset selection rule includes: Obtain candidate space angle selection parameters; The dominant angle region is adjusted based on the candidate space angle selection parameter to obtain the user candidate angle index set.

3. The near-field beam training method according to claim 1, characterized in that: The second received signal is represented as follows: in, It is expressed as a polar domain codeword, N represents the number of base station antennas, h represents the complex channel gain, and b H (θ,r) represents the near-field steering vector, represents the sampling distance, θ k represents the candidate angle, z0 represents the power received by the user end is σ 2 Additive Gaussian white noise, x represents the signal with power P transmitted by the base station, represents the base station beamforming vector, θ represents the spatial angle from the user end to the base station, r represents the distance from the base station to the user end, k represents the user candidate angle index of the polar codeword, and s k Represents the non-uniform distance index of the polar codeword.

4. The near-field beam training method according to claim 1, characterized in that: The index of the optimal domain codeword is expressed as follows: in, Represented as a polar codeword, represents the second received signal received by the user terminal, Ξ represents the user candidate angle index set, s k =0,1,2,3,···; represents a non-uniform distance index set, represents the index of the optimal polar codeword, k represents the user candidate angle index of the polar codeword, s k represents the non-uniform distance index of the polar codeword, k * represents the user candidate angle index of the optimal polar codeword, Represents the non-uniform distance index of the optimal polar codeword.

5. The near-field beam training method according to claim 1, characterized in that: The first received signal is represented as follows: Among them, w n represents the codeword in the far-field codebook, z0 represents the power received by the user end is σ 2 Additive Gaussian white noise, b H (θ, r) represents the near-field steering vector, x represents the signal with power P transmitted by the base station, N represents the number of base station antennas, h represents the channel gain in complex form, and θ n Indicates the central direction in which the entire spatial domain is divided into N sectors of equal size, a(θ n ) indicates the direction of the center θ n The transmitting beam of θ represents the spatial angle from the user end to the base station, and r represents the distance from the base station to the user end.

6. The near-field beam training method according to claim 1, characterized in that: The dominant angle region is expressed as follows: Among them, w n represents the codeword in the far-field codebook, y(w n ) represents the first received signal, w represents the optimal codeword in the far-field codebook, ρ∈(0,1) represents the beam gain threshold of the near-field steering vector, and n=1,2,…,N.

7. An electronic device, characterized in that: include: A memory, a processor, and a computer program stored in the memory and executable on the processor, wherein when the processor executes the computer program, the near-field beam training method according to any one of claims 1 to 6 is implemented.

8. A computer-readable storage medium storing computer-executable instructions, characterized in that: When the computer executable instructions are executed by the control processor, the near-field beam training method according to any one of claims 1 to 6 is implemented.

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