Channel estimation method and device, storage medium and program product

Abstract

The embodiment of the invention provides a channel estimation method and device, a storage medium and a program product. The method comprises the following steps: performing angle estimation on a base station and a first scatterer around the base station through a discrete Fourier transform algorithm to determine first angle information; according to the first angle information, designing a codebook transmission beam forming matrix; and sending an uplink pilot signal to the base station based on the codebook transmission beamforming matrix. According to the scheme of the invention, the codebook transmission beam forming matrix is designed based on the determined angle information, the precision of uplink channel estimation is improved, and the channel estimation limitation of a traditional MIMO-OFDM system is broken through.

Description

Technical Field

[0001] The present application relates to the field of mobile communication technology, and in particular to a channel estimation method, device, storage medium, and program product. Background Art

[0002] Orthogonal frequency division multiplexing (OFDM) effectively combats frequency-selective fading through subcarrier orthogonality, while multiple-input multiple-output (MIMO) technology leverages spatial diversity to increase system capacity. The combined MIMO-OFDM system has become a core solution for integrated interawareness systems. Existing research has shown that perception parameters such as angle and delay are strongly correlated with channel state information (CSI), providing a theoretical basis for joint optimization.

[0003] The existing perception-assisted uplink / downlink channel estimation schemes have the following limitations: (1) Insufficient joint perception and channel estimation. Although the existing methods based on sparse Bayesian learning or tensor decomposition can jointly estimate the target parameters and channels, they do not fully exploit the spatiotemporal sparse commonality of the perception channel and the communication channel, and there is a problem of insufficient sparsity utilization. (2) Defects of perception-assisted channel estimation. Existing schemes (such as Kalman filtering and compressed sensing) are only designed for single time slots, and do not utilize the quasi-static characteristics of the channel of continuous time slots, resulting in the problem of lack of time slot collaboration; uplink / downlink channel estimation is performed independently, and there is a lack of cross-time slot parameter sharing mechanism, resulting in repeated resource consumption.

[0004] In summary, existing research on channel estimation for MIMO-OFDM integrated systems is mostly limited to single time slots and does not fully utilize channel time correlation for joint uplink and downlink processing, resulting in limited improvement in channel estimation performance. Summary of the Invention

[0005] At least one embodiment of the present application provides a channel estimation method, apparatus, storage medium, and program product to address the drawbacks of the prior art.

[0006] In order to solve the above technical problems, this application is implemented as follows:

[0007] In a first aspect, an embodiment of the present application provides a channel estimation method, applied to a user equipment, including:

[0008] Performing angle estimation on a base station and a first scatterer around the base station by using a discrete Fourier transform algorithm to determine first angle information;

[0009] designing a codebooked transmit beamforming matrix according to the first angle information;

[0010] An uplink pilot signal is sent to the base station based on the codebooked transmit beamforming matrix.

[0011] Optionally, the method of performing angle estimation on a base station and a first scatterer around the base station by using a discrete Fourier transform algorithm to determine first angle information includes:

[0012] receiving a downlink reference signal sent by a base station;

[0013] Performing a discrete Fourier transform on the downlink reference signal using a discrete Fourier transform algorithm to obtain frequency domain information;

[0014] According to the frequency domain information and the antenna array geometry, the angle corresponding to the maximum peak is used as the base station line-of-sight path angle, and the remaining peak angles represent the angle information of the first scatterer;

[0015] The base station line-of-sight path angle and the angle information of the first scatterer are determined as the first angle information.

[0016] Optionally, designing a codebooked transmit beamforming matrix based on the first angle information includes:

[0017] generating a discretized angle set covering an angle interval according to the first angle information;

[0018] Based on the array antenna structure characteristics of the user equipment and the discretized angle set, a beamforming vector set corresponding to each discrete angle is generated to form a codebooked transmit beamforming matrix.

[0019] In a second aspect, an embodiment of the present application provides a channel estimation method, applied to a base station, comprising:

[0020] receiving an uplink pilot signal sent by a user equipment;

[0021] performing a discrete Fourier transform on the uplink pilot signal to extract second angle information of the user equipment and a second scatterer around the user equipment;

[0022] According to the first angle information and the second angle information determined by the downlink, an orthogonal matching pursuit algorithm is dynamically optimized, and channel estimation information is determined based on the optimized matching pursuit algorithm.

[0023] Optionally, performing a discrete Fourier transform on the uplink pilot signal to extract second angle information of the user equipment and a second scatterer around the user equipment includes:

[0024] Performing discrete Fourier transform processing on the uplink pilot signal to obtain frequency domain signal characteristics corresponding to the uplink pilot signal;

[0025] extracting, based on the frequency domain signal characteristics, a set of peak components corresponding to the user equipment and a second scatterer around the user equipment;

[0026] Calculating an estimated angle of arrival value corresponding to each peak component based on a phase difference characteristic of a signal received by an array antenna of the base station and the set of peak components;

[0027] According to the arrival angle estimation values corresponding to the peak components, the main path angle of the user equipment and the reflection path angle of the second scatterer are jointly used to form the second angle information.

[0028] Optionally, dynamically optimizing an orthogonal matching pursuit algorithm according to the first angle information and the second angle information determined in the downlink, and determining channel estimation information based on the optimized matching pursuit algorithm includes:

[0029] Performing a joint analysis on the first angle information determined by the downlink and the second angle information extracted by the uplink to construct a fused angle feature set including the main path of the user equipment and the reflection path of the second scatterer;

[0030] Based on the fused angle feature set, the search range and iteration step of the orthogonal matching pursuit algorithm are dynamically adjusted, and atomic matching is performed within the effective angle range to determine the optimized matching pursuit algorithm.

[0031] Based on the optimized matching pursuit algorithm, the output is the channel impulse response estimation result including multipath delay, angle and complex gain.

[0032] In a third aspect, an embodiment of the present application provides a channel estimation device, applied to a user equipment, including:

[0033] A first determining module is configured to perform angle estimation on a base station and a first scatterer around the base station by using a discrete Fourier transform algorithm to determine first angle information;

[0034] A first processing module, configured to design a codebooked transmit beamforming matrix according to the first angle information;

[0035] The second processing module is configured to send an uplink pilot signal to the base station based on the codebooked transmit beamforming matrix.

[0036] In a fourth aspect, an embodiment of the present application provides a channel estimation device, applied to a base station, including:

[0037] A receiving module, configured to receive an uplink pilot signal sent by a user equipment;

[0038] a third processing module, configured to perform discrete Fourier transform on the uplink pilot signal to extract second angle information of the user equipment and a second scatterer around the user equipment;

[0039] The fourth processing module is used to dynamically optimize the orthogonal matching pursuit algorithm according to the first angle information and the second angle information determined by the downlink, and determine the channel estimation information based on the optimized matching pursuit algorithm.

[0040] In a fifth aspect, an embodiment of the present application provides a computer-readable storage medium, on which a program is stored. When the program is executed by a processor, the steps of the method described in any one of the first aspect or the second aspect are implemented.

[0041] In a sixth aspect, an embodiment of the present application provides a computer program product, comprising computer instructions, which, when executed by a processor, implement the steps of the method described in any one of the first aspect or the second aspect.

[0042] Compared with the prior art, the channel estimation method, device, storage medium and program product provided in the embodiments of the present application first use discrete Fourier transform to extract the scatterer angle information (first angle information) of the downlink on the base station side and build a spatial feature library; then dynamically design the codebook beamforming matrix based on the information to achieve directional transmission of the uplink pilot signal. This joint uplink and downlink angle information processing method solves the existing problems through three key improvements: (1) Expanding the single time slot estimation to cross-time slot angle feature tracking, and using the time domain stability of the scatterer's spatial position to establish a channel time correlation model; (2) Enhancing the effective coverage of the pilot signal and improving the signal-to-noise ratio through uplink and downlink joint beam optimization; (3) Reconstructing the sparse representation dictionary based on the dual space-time constraints to reduce the channel estimation error. The solution of the present application improves the channel tracking capability in high-mobility scenarios. BRIEF DESCRIPTION OF THE DRAWINGS

[0043] Various other advantages and benefits will become apparent to those skilled in the art upon reading the detailed description of the preferred embodiment below. The accompanying drawings are for illustration purposes only and are not to be considered as limiting the present application. The same reference symbols are used throughout the drawings to represent the same components. In the drawings:

[0044] Figure 1 This is a schematic diagram of a single scene of synaesthesia integration;

[0045] Figure 2 A schematic flow chart of a channel estimation method applied to a user equipment is provided for an embodiment of the present invention;

[0046] Figure 3 A schematic flow chart of a channel estimation method applied to a base station is provided for an embodiment of the present invention;

[0047] Figure 4 A schematic diagram of the overall flow of a channel estimation method provided by an embodiment of the present invention;

[0048] Figure 5 A schematic diagram showing a comparison of normalized mean square errors provided by an embodiment of the present invention;

[0049] Figure 6 A schematic structural diagram of a channel estimation device applied to user equipment is provided for an embodiment of the present invention;

[0050] Figure 7 A structural diagram of a channel estimation device applied to a base station is provided for an embodiment of the present invention. DETAILED DESCRIPTION

[0051] The terms "first", "second", etc. in this application are used to distinguish similar objects, and are not used to describe a specific order or sequence. It should be understood that the terms used in this way are interchangeable where appropriate, so that the embodiments of the present application can be implemented in an order other than those illustrated or described herein, and the objects distinguished by "first" and "second" are generally of the same type, and do not limit the number of objects, for example, the first object can be one or more. In addition, "or" in this application represents at least one of the connected objects. For example, "A or B" covers three options, namely, Option 1: including A but not including B; Option 2: including B but not including A; Option 3: including both A and B. The character " / " generally indicates that the objects associated before and after are in an "or" relationship.

[0052] The term "indication" in this application can be either a direct indication (or explicit indication) or an indirect indication (or implicit indication). A direct indication can be understood as the sender explicitly informing the receiver of specific information, the operation to be performed, or the requested result, etc. in the instruction sent; an indirect indication can be understood as the receiver determining the corresponding information based on the instruction sent by the sender, or making a judgment and determining the operation to be performed or the requested result, etc. based on the judgment result.

[0053] As described in the background, most existing research focuses solely on channel estimation within a single uplink or downlink time slot, failing to exploit the collaborative potential between adjacent time slots. Because channels are time-correlated, they typically exhibit quasi-static characteristics between consecutive uplink and downlink time slots. However, no research has yet explored in-depth perception-assisted joint uplink and downlink processing to further enhance channel estimation performance. To address at least one of the above issues, embodiments of the present application provide a channel estimation method, apparatus, storage medium, and program product that can reduce or avoid the occurrence of the above situations and improve channel estimation accuracy.

[0054] Reference Figure 1 As shown, an embodiment of the present application provides a MIMO-OFDM synaesthesia integrated system that operates in the millimeter wave frequency band and time division duplex mode. The system model parameter settings and assumptions of the synaesthesia integrated system are as follows: (1) In the perception operation, the user equipment is regarded as a point target; (2) Each base station is equipped with a uniform linear antenna array, each equipped with a transmitting antenna and a receiving antenna; (3) The base station and the user equipment are perfectly synchronized through a global reference clock. The scenario setting is realized here.

[0055] The system of the present application also includes signal and channel models. In the case of sending signals, in the system provided by the present application, the base station and the user equipment send OFDM signals to perform tasks to ensure compatibility with existing wireless communication networks. Specifically, the transmitted analog time domain signal is represented as:

[0056]

[0057] Wherein, i=D or i=U corresponds to the transmission signal of downlink or uplink respectively; L i Represents the number of symbols, whose index can be expressed as L i ={0,…,L i -1}, K i represents the number of subcarriers, and △fi represents the subcarrier spacing. The duration of an OFDM symbol is in, Indicates the duration of the basic symbol, Indicates the duration of the cyclic prefix. and They represent the frequency domain signals sent by the base station and the device on the kth subcarrier and the lth OFDM symbol respectively. is a rectangular function, when 0≤t≤T s When , the function takes the value 1, otherwise, it takes the value 0.

[0058] In the downlink / uplink channel, due to the sparsity of the millimeter wave channel, this application uses a geometric channel model containing P paths to characterize the uplink and downlink channels. The downlink channel on the kth subcarrier can be expressed as:

[0059]

[0060] in, p = 0 represents the channel response of the line-of-sight path, p∈{1,…,P-1} corresponds to the non-line-of-sight path associated with the pth scatterer, P represents the total number of multipaths, and its index set can be expressed as P=={0,…,P-1}, ε p represents the equivalent path gain of the pth path, τ p represents the delay of the pth path, φ p represents the angle of arrival (AoA) of the pth path, θ p represents the angle of departure (AoD) of the p-th path. In addition, represents the downlink transmitter array response vector, represents the downlink receiving end array response vector.

[0061] Due to the channel heterogeneity of the time division duplex system, the uplink channel is the transpose of the downlink channel and can be expressed as:

[0062]

[0063] in,

[0064] In the case of receiving signals, the downlink OFDM signal sent by the base station is received by the user equipment after propagating through the downlink channel, while the uplink OFDM signal sent by the user equipment is received by the base station after propagating through the uplink channel. Specifically, the frequency domain signal received by the base station or user equipment at the kth subcarrier and the lth OFDM symbol can be expressed as:

[0065]

[0066] Where i=D or i=U represents the received signal of downlink or uplink respectively. Indicates the complex additive white Gaussian noise (AWGN) received by the device. Indicates the AWGN received by the BS.

[0067] Based on the above, refer to Figure 2 As shown, an embodiment of the present application provides a channel estimation method, applied to a user equipment, including:

[0068] Step 21 : performing angle estimation on the base station and a first scatterer around the base station by using a discrete Fourier transform algorithm to determine first angle information.

[0069] In an embodiment of the present application, the channel estimation method applied to the user equipment is in the downlink phase. In the downlink phase, an angle estimation algorithm based on discrete Fourier transform is used to perform a rough angle estimation of the base station and its surrounding scatterers (i.e., the first scatterer) at the user equipment end to determine the first angle information. For example, the user equipment uses a discrete Fourier transform algorithm to analyze the multipath signals of the base station and the surrounding scatterers, and extracts the first angle information including AoA and AoD. This step captures the time and frequency domain features simultaneously through two-dimensional transformation, overcoming the limitations of traditional single-slot estimation.

[0070] Step 22: Design a codebooked transmit beamforming matrix according to the first angle information.

[0071] Here, a codebooked transmit beamforming matrix is dynamically constructed based on the extracted angular features, precisely directing the main lobe of the beam toward the effective scattering path. This design significantly improves the signal-to-noise ratio of the pilot signal while reducing energy leakage in non-essential directions.

[0072] Step 23: Send an uplink pilot signal to the base station based on the codebooked transmit beamforming matrix.

[0073] In this embodiment, an optimized beamforming matrix is used to transmit uplink pilot signals, ensuring that the base station receiver can accurately identify the characteristics of multipath components. This mechanism improves the efficiency of acquiring channel state information through dual space-time constraints. This method improves channel estimation performance in complex scenarios by combining uplink and downlink angle information with dynamic beam steering.

[0074] Optionally, the above step 21 includes:

[0075] receiving a downlink reference signal sent by a base station;

[0076] Performing a discrete Fourier transform (DFT) on the downlink reference signal using a discrete Fourier transform (DFT) algorithm to obtain frequency domain information;

[0077] According to the frequency domain information and the antenna array geometry, the angle corresponding to the maximum peak is used as the line-of-sight (LoS) angle of the base station, and the remaining peak angles represent the angle information of the first scatterer;

[0078] The base station line-of-sight path angle and the angle information of the first scatterer are determined as the first angle information.

[0079] In this application, the user equipment receives a known downlink reference signal sent by the base station, which contains the spatial characteristic information of the base station antenna array. DFT is used to convert the time domain reference signal into a frequency domain representation, and the spatial frequency components of the signal are obtained through complex spectrum analysis. According to the geometric structure of the antenna array and the frequency domain peak position, the angle corresponding to the maximum energy peak is resolved as the base station LoS angle; the remaining obvious peaks correspond to the arrival angles of multipath scatterers, reflecting the spatial scattering characteristics of the propagation environment. The LoS angle and the scatterer angle are then combined into the first angle information to provide a spatial channel feature library for subsequent beamforming. This mechanism significantly improves the angle resolution accuracy through joint time-frequency domain analysis.

[0080] Specifically, the downlink reference signal sent by the base station is received by the above formula (4), and the downlink reference signal is subjected to DFT by the DFT algorithm to obtain frequency domain information. Specifically, based on the received downlink reference signal, the downlink arrival angle is estimated by the DFT method, that is,

[0081] Specifically, the frequency domain received signal of the user equipment on the υth antenna, the kth subcarrier, and the lth symbol is expressed as:

[0082]

[0083] in, It can be seen It is a constant in the spatial dimension and is independent of the receiving antenna index υ.

[0084] The DFT-based angle estimation algorithm in the above steps can be expressed as follows:

[0085]

[0086] Among them, n D ∈{0,…,N u -1}. Then, applying peak detection, the estimated angle of arrival can be calculated as:

[0087]

[0088] in, Represents the peak index. Due to the dominant role of LoS in the millimeter wave channel, the angle corresponding to the maximum peak index is the arrival angle relative to the base station, that is,

[0089] Optionally, the above step 22 includes:

[0090] generating a discretized angle set covering an angle interval according to the first angle information;

[0091] Based on the array antenna structure characteristics of the user equipment and the discretized angle set, a beamforming vector set corresponding to each discrete angle is generated to form a codebooked transmit beamforming matrix.

[0092] In the embodiment of the present application, step 22 is the core link of designing a beamforming strategy based on angle estimation, and mainly includes two key sub-steps: discretization of angle sets and generation of codebook beamforming matrices. These two steps together construct an optimization scheme suitable for directional transmission of uplink pilot signals. The purpose of generating a discretized angle set covering the angle interval based on the first angle information is to convert the continuous angle space into a finite number of discrete angle points for the subsequent construction of the beamforming codebook. The implementation method is: based on the first angle information estimated in step 21 (such as the AoA of the base station or the scatterer angle distribution), determine an angle interval covering the main signal energy (for example, a range of ±Δθ centered on the estimated angle). The angle interval is evenly divided into multiple discrete angle points to form a discretized angle set. Here, by discretization, the infinite-dimensional angle space is converted into a finite-dimensional problem, which reduces the complexity of the system; the design of the coverage angle interval ensures effective coverage of the main signal path, even if there is an estimation error.

[0093] Furthermore, the purpose of forming a codebooked transmit beamforming matrix is to generate the optimal beamforming vector for each discrete angle, concentrating the uplink pilot signal energy in the target direction. This requires obtaining the array antenna structural characteristics, such as the geometry of the antenna array, such as uniform linear array (ULA) or uniform planar array (UPA); the antenna spacing d; and the number of antennas M, which affects the beamforming gain. For each discrete angle, a corresponding beamforming vector is generated based on the array response function. All beamforming vectors are arranged in columns to form a codebook matrix.

[0094] The codebook matrix of this application predefines a set of optimal beam directions, from which the user device can directly select the beamforming vector that best matches the estimated angle; the beamforming vector designed by the array response function can maximize the signal gain in the target direction and suppress interference in other directions.

[0095] Specifically, based on the estimated angle information, a codebook-based transmit beamforming strategy is designed to achieve directional transmission of the uplink pilot signal. In an embodiment of the present invention, considering the power limitation of the user equipment and the huge propagation loss of the millimeter wave signal, the transmit beamforming is designed to point to the base station to enhance the uplink signal quality. However, due to the complexity of the channel environment and hardware limitations, angle estimation errors are inevitable. To this end, the codebook-based transmit beamforming in the above steps can be expressed as:

[0096]

[0097] in, Denote the angle set, and assume that L U >1, and assume that the angle estimation error of each path is limited to [-Δφ max ,Δφ max ]. This enables the beam direction to be oriented around the estimated angle Dynamic adjustments are made to improve beam alignment accuracy and enhance uplink robustness.

[0098] Existing technologies may use fixed codebooks (such as DFT codebooks) and are unable to adaptively adjust the angular coverage range. This step dynamically generates coverage intervals based on real-time estimated angle information, improving adaptability to dynamic channels. Existing solutions may ignore the actual array structure (such as antenna spacing and arrangement), resulting in reduced beamforming performance. This step explicitly considers array characteristics, and the generated codebook is more closely aligned with the actual hardware configuration. By covering angle intervals rather than single-point angles, the codebook can tolerate certain angle estimation errors (such as the rough estimation error in step 21), ensuring robustness in practical applications.

[0099] The uplink pilot signal transmitted directionally in this application enhances the signal strength at the base station receiving end, improves the channel estimation accuracy, and thus improves the communication quality.

[0100] Reference Figure 3 As shown, an embodiment of the present application provides a channel estimation method, which is applied to a base station, including:

[0101] Step 31: Receive an uplink pilot signal sent by a user equipment.

[0102] Here, step 31 is to obtain a reference signal for channel estimation, providing a data basis for subsequent angle extraction and parameter optimization. For example, the pilot signal can be designed using an orthogonal sequence or a pseudo-random sequence to ensure that the signal has good autocorrelation characteristics in the time-frequency domain; the pilot density must satisfy the Nyquist sampling theorem. Correspondingly, the multi-antenna array on the base station side can synchronously receive signals through step 31 to form a received signal matrix. Existing solutions may rely on a fixed pilot pattern, but this step supports dynamic adjustment of the pilot position based on downlink feedback, such as increasing the pilot density in high-Doppler areas.

[0103] Step 32: Perform a discrete Fourier transform (DFT) on the uplink pilot signal to extract second angle information of the user equipment and a second scatterer around the user equipment.

[0104] In an embodiment of the present application, a DFT is performed on the uplink pilot signal. An N-point DFT can be performed on the received signal of each antenna, converted to the frequency domain, and frequency domain signal characteristics corresponding to the uplink pilot signal are obtained. Peak detection is performed on the frequency domain signal characteristics, and the frequency index corresponding to the maximum peak is mapped to an angle. If multiple peaks exist, corresponding to multipath signals, each peak corresponds to a scatterer angle. Using the frequency index corresponding to the maximum peak mapped to an angle and the multiple scatterer angles, second angle information of the user device and a second scatterer surrounding the user device is determined.

[0105] Step 33: Dynamically optimize the orthogonal matching pursuit algorithm according to the first angle information and the second angle information determined in the downlink, and determine channel estimation information based on the optimized matching pursuit algorithm.

[0106] It should be noted that the sensing-aided orthogonal matching pursuit (SAOMP) algorithm is a sparse signal reconstruction algorithm that gradually approximates the channel impulse response by iteratively selecting the atoms most correlated with the residual (corresponding to the channel multipath).

[0107] In an embodiment of the present application, the first angle information is the angle of the scatterer around the base station estimated by the downlink; the second angle information is the angle of the scatterer around the user equipment estimated by the uplink, and the first angle information and the second angle information together constitute a multipath angle pair. By using the multipath angle pair, only the array response atoms corresponding to the angle pair can be retained, the atomic space can be reduced, and redundant searches can be reduced. The multipath angle pair is used to determine the angle estimation error, such as the downlink angle error and the uplink angle error, and a weight factor is added to each atom. The smaller the error, the higher the weight, and high-weight atoms are given priority. By using the angle estimation error and combining the sparsity of the angle information, the orthogonal matching pursuit algorithm is dynamically optimized, such as the millimeter wave channel multipath number P<<M, the preset sparsity K=P+Q, and the algorithm is terminated after K iterations to avoid overfitting. The optimized SAOMP algorithm is used to output the index set of non-zero atoms and the corresponding channel gain, and finally the channel matrix is output.

[0108] Specifically, the parameter configuration examples for the dynamically optimized orthogonal matching pursuit algorithm include: the number of DFT points (N = 256), the number of antennas (M = 64), an angle estimation error threshold of ±5°, and an upper limit of the number of SAOMP iterations (K = 16) (corresponding to the number of multipaths (P = 8) and the number of downlink angles (Q = 8)).

[0109] This application realizes the complementarity between the first downlink angle (base station perspective) and the second uplink angle (user equipment perspective), narrowing the multipath search space and improving the SAOMP convergence speed; DFT peak detection combined with angle prior information reduces the interference of noise on angle estimation; through angle constraints, the atomic space dimension is reduced, which is suitable for real-time channel estimation of large-scale MIMO systems (such as 128-antenna base stations). For example, this application can be applied to millimeter wave communication systems (28GHz / 60GHz), using angle sparsity to improve channel estimation efficiency; it can also be applied to mobile scenarios (such as high-speed rail and drone communications) to adapt to fast time-varying channels through dynamic angle updates.

[0110] Optionally, the above step 32 includes:

[0111] Performing discrete Fourier transform processing on the uplink pilot signal to obtain frequency domain signal characteristics corresponding to the uplink pilot signal;

[0112] extracting, based on the frequency domain signal characteristics, a set of peak components corresponding to the user equipment and a second scatterer around the user equipment;

[0113] Calculating an estimated angle of arrival value corresponding to each peak component based on a phase difference characteristic of a signal received by an array antenna of the base station and the set of peak components;

[0114] According to the arrival angle estimation values corresponding to the peak components, the main path angle of the user equipment and the reflection path angle of the second scatterer are jointly used to form the second angle information.

[0115] In an embodiment of the present application, an N-point DFT conversion is performed on the uplink pilot signal received by each antenna of the base station to the frequency domain to obtain the frequency domain signal characteristics corresponding to the uplink pilot signal. Here, the time domain signal is converted to the frequency domain representation to separate different frequency components for subsequent peak detection. Frequency domain signal characteristics such as amplitude and phase can directly reflect the frequency selective fading and multipath effect of the channel. Based on the frequency domain signal characteristics, the amplitude of each frequency point is calculated, and a threshold is set, such as the mean + 3 times the standard deviation, to filter out the frequency points whose amplitude exceeds the threshold. Non-maximum suppression is performed on adjacent peaks to ensure that each multipath corresponds to a unique peak point, and each peak component corresponds to an independent signal path (line-of-sight path or scattering path), and finally a set of peak components is output. The arrival angle is calculated based on the array phase difference and the peak component. The corresponding angle with the largest peak amplitude is used as the main path angle of the user equipment, and the corresponding angles of the remaining peaks are the reflection path angles of the second scatterer. The second angle information is composed of the main path angle and the scatterer reflection path angle merged into a set.

[0116] The main path angle in the second angle information of the present application is used for main direction alignment of beamforming; the scattering path angle is used for multipath diversity combining or channel modeling.

[0117] Specifically, in the uplink phase, the base station estimates the angle information of the user equipment and its surrounding scatterers based on the received pilot signal using the DFT method. In the embodiment of the present application, the DFT technology is used to estimate the uplink arrival angle using the received frequency domain signal in the above formula (4), that is, Specifically, the base station The frequency domain received signal on the kth antenna, the kth subcarrier, and the lth symbol is:

[0118]

[0119] in, It is worth noting that the omnidirectional pilot signal sent by the base station Different from the above, the user equipment uses transmit beamforming to send uplink pilot signals. It can be further expressed as It can be seen that and receiving antenna index Therefore, the received signal on all antennas Apply N in the above steps b By performing point DFT and applying peak detection, the arrival angle of the uplink can be effectively estimated, which can be expressed as Due to the dominant influence of the line-of-sight path, the angle corresponding to the maximum peak index is the estimated arrival angle relative to the device, that is,

[0120] Optionally, the above step 33 includes:

[0121] Performing a joint analysis on the first angle information determined by the downlink and the second angle information extracted by the uplink to construct a fused angle feature set including the main path of the user equipment and the reflection path of the second scatterer;

[0122] Based on the fused angle feature set, the search range and iteration step of the orthogonal matching pursuit algorithm are dynamically adjusted, and atomic matching is performed within the effective angle range to determine the optimized matching pursuit algorithm.

[0123] Based on the optimized matching pursuit algorithm, the output is the channel impulse response estimation result including multipath delay, angle and complex gain.

[0124] In this embodiment, first and second angle information are jointly analyzed to construct a fused angle feature set. This integrates the uplink and downlink angle information to form a more complete channel multipath characterization, providing accurate angle priors for subsequent SAOMP algorithm optimization. The first angle information is the angle of the base station and surrounding scatterers estimated by the user equipment in the downlink (e.g., downlink AoA); the second angle information is the angle of the user equipment and surrounding scatterers estimated by the base station in the uplink (e.g., uplink AoA). Through spatial geometric relationships, the uplink and downlink angles are associated as multipath "AoA-AoD" pairs. For example, the AoA and AoD of the line-of-sight path satisfy a mirror-symmetric relationship. Outliers with angle estimation errors exceeding a threshold (e.g., ±5°) are eliminated, and valid angle pairs are screened. The angles of the scatterer reflection paths are clustered to form a fused set of LoS and K scattering paths, merging overlapping angle intervals. Here, the joint analysis of uplink and downlink angles can reduce angle estimation errors and avoid the one-sidedness of single-link angle estimation. The fused feature set directly reflects the multipath topology of the channel, providing precise atomic spatial constraints for the SAOMP algorithm. According to the fusion angle set, the atomic space of the SAOMP algorithm is limited to the valid angle range, and the array response atoms corresponding to invalid angles are excluded. The atomic space dimension is reduced from (O(MN) to (O(K) (M is the number of antennas, N is the number of frequency points), and the computational complexity is reduced by MN / K times (K is the number of multipaths). For the main path angle pair, a smaller iteration step size (such as 0.1°) is set to improve the estimation accuracy. For the scattering path angle pair, the step size is dynamically adjusted according to the angle estimation error (the larger the error, the larger the step size, which speeds up the convergence). Here, the preset iteration step size formula can be used for iterative calculation. The number of iterations is reduced from 20 times of the standard SAOMP to 8-12 times, and the convergence speed is improved. The accuracy is improved; the multipath resolution capability is enhanced, and dense multipaths with an angle interval of less than 1° can be distinguished. The multipath delay is calculated by the frequency domain peak index and the sampling frequency; the fused angle pair corresponds to the incoming and outgoing directions of the multipath to determine the angle information; the complex gain is determined by estimating the channel amplitude and phase by the least squares method. The channel impulse response (CIR) is constructed using a preset impulse function. The estimation results determined by the above steps in this application can be directly used for beamforming in millimeter wave communications (such as the main path angle for beam steering); the multipath delay and complex gain provide precise parameters for channel modeling (such as the Saleh-Valenzuela model) to support time-varying channel prediction.

[0125] Specifically, according to the estimated angle information, a codebook-based receiver combiner is designed to improve the quality of the received signal. In the embodiment of the present application, in order to improve the quality of the received signal, the base station designs a receiver combiner based on the estimated AoD to enhance the desired signal. Considering the imperfection of the angle estimation, it is assumed that the angle estimation error of each path is limited to [-Δθ max ,Δθ max]. The codebook of the receiving combiner in the above steps can be constructed as in, Θ represents the angle set, which can be expanded into

[0126] Based on the angle information, the sparse representation matching strategy in the orthogonal matching pursuit process is dynamically optimized through perception information to achieve high-precision channel state information estimation, including: perception-assisted sparse signal reconstruction method. In order to improve the accuracy of channel estimation, the device sends pilot signals in sequence, and the base station performs channel response measurement under different transmission and reception parameters configured based on the angle information obtained by perception. Specifically, the received signal of the base station on the kth subcarrier and the lth symbol can be expressed as:

[0127]

[0128] in, Equation (a) is based on Then, stack L U The received signal on consecutive symbols can be obtained:

[0129]

[0130] in,

[0131] The channel matrix in the above formula (3) is It can be compactly expressed in matrix form as:

[0132]

[0133] in, and represents the array response matrix, each column of which represents the array response vector. In addition, in, Represents the channel gain. Due to the dominant role of LoS and the limited number of strong scatterers in millimeter wave propagation, the channel exhibits obvious sparsity in the angular domain. This sparsity can be characterized by discretizing the angular domain into a finite set of grid points, each of which represents a possible AoD or AoA. Using the estimated angle as prior information, the present invention dynamically constructs a grid to focus on the main propagation path. Specifically, based on the estimated angle, the grids corresponding to the uplink AoD (i.e., downlink AoA) and uplink AoA are defined as follows:

[0134]

[0135] Where Q = {0,…,Q-1}, Q>1 represents the number of grid points. The grids Ω and Γ both contain G = PQ>>P grid points. Using sparsity, the channel matrix It can be expressed in the form of sparse angle domain:

[0136]

[0137] in, and represents the array response matrix corresponding to the grid, and denote the grid points corresponding to the uplink arrival and departure angles, respectively, represents a sparse matrix containing P non-zero elements, representing the channel gain. Then, using the channel matrix in (14), the received signal can be transformed into:

[0138]

[0139] in, represents a sparse vector containing P non-zero elements, represents the measurement matrix, Given that Sparsity,channel estimation can be transformed into a sparse signal recovery problem,,and therefore can be solved using methods based on compressed,sensing.

[0140] Finally, this application provides a detailed description of the sensing-aided orthogonal matching pursuit (SAOMP) algorithm, which uses estimated angles to optimize the orthogonal matching pursuit process to achieve high-precision channel state information estimation.

[0141] In the SAOMP algorithm, the input information is: receiving signal Angle estimate and Residual Iteration Channel gain Index Collection Iteration index j = 0. The output information is:

[0142] The execution step 1 of the SAOMP algorithm is to generate a grid based on the perception results.

[0143] Based on the estimated angle, a grid corresponding to the uplink AoD is generated and the grid corresponding to the uplink AoA

[0144] Generate array response matrix based on the grid and

[0145] Generate measurement matrix in,

[0146] The execution step 2 of the SAOMP algorithm is: obtaining a non-zero channel gain value. When j≤P-1, j=j+1; Stop the loop.

[0147] The execution step 3 of the SAOMP algorithm is: obtaining the channel gain vector. 2 ; if g∈J, otherwise, Stop the loop.

[0148] Step 4 of the SAOMP algorithm is to generate a channel matrix.

[0149] In step 1, the angle information obtained by perception is used to construct the grids Ω and Γ corresponding to the uplink AoD and AoA, and the measurement matrix is generated accordingly. In each iteration of step 2, step b) selects the measurement matrix The residual The column with the strongest correlation. In step c), update the column index set J (j) =, where each element in the set corresponds to an arrival angle / pair in the grid. Subsequently, in step d), the channel gain corresponding to the selected arrival angle / departure angle pair is estimated using the least squares method. In step e), the residual is updated by subtracting the contribution of the selected column. This iterative process continues until a preset sparsity level is reached, at which point all non-zero channel gains are determined. Next, in step 3, the channel gain vector is obtained based on the non-zero channel gain values. Finally, in step 4, a high-precision channel estimate is constructed based on the array response matrix and the estimated channel gain vector, which is denoted as

[0150] Conventional channel estimation methods based on compressed sensing rely on a fixed grid obtained by uniformly quantizing the angle domain [0,π). In contrast, it can be seen that the embodiments of the present invention dynamically construct a grid based on the estimated angles, thereby focusing on the main propagation paths. Specifically, by limiting the angle domain to the range of departure angle and arrival angle, respectively and The present invention significantly reduces the grid size and improves the grid resolution, thereby effectively reducing the computational complexity and improving the estimation accuracy.

[0151] Reference Figure 4The overall flow chart shown can realize the coordination of uplink and downlink. The embodiment of the present application designs a frame structure and signal processing flow chart that follows the time division duplex mechanism. Figure 4 As shown. Each frame is divided into three stages: Stage I is used for downlink pilot signal transmission, Stage II is used for uplink pilot signal transmission, and Stage III is used for uplink or downlink data transmission. The focus of the present invention is on the first two stages, aiming to achieve high-precision uplink channel estimation. Specifically, in Stage I, due to the lack of prior information about the device, the base station sends an omnidirectional pilot signal, and the device receives the downlink signal through LoS and non-line-of-sight paths (NLoS). Considering the limitation of computing resources, the device only estimates the AoD to obtain rough angle information. Using these preliminary estimates and combining the time correlation of the channel, the device designs the transmit beamforming to enhance the uplink signal quality. In Stage II, the base station estimates the AOD based on the received pilot signal and designs the combiner accordingly. Subsequently, the base station uses the estimated angular domain information to perform refined channel estimation to obtain high-precision channel state information.

[0152] Further, Figure 5 A comparison diagram of the normalized mean square error (NMSE) provided in the embodiment of the present invention. Figure 5 The figure shows a comparison of the MMSE performance of the proposed SAOMP algorithm with that of the least-squares (LS) method, the minimum mean square error (MMSE) method, and a beam training-based MMSE method. The horizontal axis represents the signal-to-noise ratio (SNR) in decibels, and the vertical axis represents the NMSE. It can be seen that the NMSE gradually decreases with increasing SNR. Furthermore, the proposed SAOMP algorithm demonstrates superior estimation performance under all SNR conditions. Even in low SNR environments, the algorithm achieves the lowest NMSE, demonstrating strong robustness in adverse scenarios. Furthermore, the proposed algorithm's estimation accuracy significantly improves with increasing SNR, further expanding its performance advantage over other solutions.

[0153] In summary, the solution of the present application proposes an uplink channel estimation method based on perception assistance and downlink collaboration, makes full use of the channel time domain correlation between adjacent time slots, and designs a two-stage channel estimation method to obtain high-precision uplink channel state information. First, in the downlink stage, an angle estimation algorithm based on discrete Fourier transform is used to perform a rough angle estimation of the base station and surrounding scatterers on the device side, and based on this, a codebook-based transmit beamforming is designed to send the uplink pilot signal in a directionally direction to the base station. Subsequently, in the uplink stage, the base station uses a discrete Fourier transform algorithm to obtain the angle of the device and the scatterer, and based on this, a codebook-based receiving combiner is designed to enhance the signal reception quality. Finally, the present application also proposes a perception-assisted orthogonal matching pursuit (SAOMP) algorithm, which uses the estimated angle to optimize the orthogonal matching pursuit process, thereby achieving high-precision channel state information estimation.

[0154] The above describes various methods of the embodiments of the present application. The following further provides apparatuses for implementing the above methods.

[0155] Please refer to Figure 6 , an embodiment of the present application further provides a channel estimation device, applied to a user equipment, comprising:

[0156] A first determining module 61 is configured to perform angle estimation on a base station and a first scatterer around the base station by using a discrete Fourier transform algorithm to determine first angle information;

[0157] A first processing module 62 is configured to design a codebooked transmit beamforming matrix according to the first angle information;

[0158] The second processing module 63 is configured to send an uplink pilot signal to the base station based on the codebooked transmit beamforming matrix.

[0159] Optionally, the first determining module 61 includes:

[0160] A receiving unit, configured to receive a downlink reference signal sent by a base station;

[0161] an obtaining unit, configured to perform a discrete Fourier transform on the downlink reference signal using a discrete Fourier transform algorithm to obtain frequency domain information;

[0162] A first processing unit is configured to use, based on the frequency domain information and the antenna array geometry, an angle corresponding to a maximum peak as a base station line-of-sight path angle, and other peak angles to represent angle information of the first scatterer;

[0163] The first determining unit is configured to determine the base station line-of-sight path angle and the angle information of the first scatterer as the first angle information.

[0164] Optionally, the first processing module 62 includes:

[0165] A second processing unit, configured to generate a discretized angle set covering an angle interval according to the first angle information;

[0166] The third processing unit is configured to generate a set of beamforming vectors corresponding to each discrete angle based on the array antenna structure characteristics of the user equipment and the set of discrete angles to form a codebooked transmit beamforming matrix.

[0167] It should be noted that the device in this embodiment corresponds to the method applied to the user device side described above. The implementation methods in the above embodiments are all applicable to the embodiments of this device and can achieve the same technical effects. The above-mentioned device provided in the embodiment of the present application can implement all the method steps implemented in the above-mentioned method embodiment and can achieve the same technical effects. The parts and beneficial effects of this embodiment that are the same as those in the method embodiment will not be described in detail here.

[0168] Please refer to Figure 7 , an embodiment of the present application further provides a channel estimation device, applied to a base station, comprising:

[0169] Receiving module 71, configured to receive an uplink pilot signal sent by a user equipment;

[0170] a third processing module 72, configured to perform a discrete Fourier transform on the uplink pilot signal to extract second angle information of the user equipment and a second scatterer around the user equipment;

[0171] The fourth processing module 73 is configured to dynamically optimize the orthogonal matching pursuit algorithm according to the first angle information and the second angle information determined in the downlink, and determine channel estimation information based on the optimized matching pursuit algorithm.

[0172] Optionally, the third processing module 72 includes:

[0173] an acquiring unit, configured to perform discrete Fourier transform processing on the uplink pilot signal to acquire a frequency domain signal feature corresponding to the uplink pilot signal;

[0174] an extraction unit, configured to extract a set of peak components corresponding to the user equipment and a second scatterer around the user equipment based on the frequency domain signal feature;

[0175] a calculation unit, configured to calculate an estimated value of an angle of arrival corresponding to each peak component based on a phase difference characteristic of a signal received by an array antenna of the base station and the set of peak components;

[0176] The fourth processing unit is configured to, based on the arrival angle estimation values corresponding to the peak components, combine the main path angle of the user equipment and the reflection path angle of the second scatterer to form the second angle information.

[0177] Optionally, the fourth processing module 73 includes:

[0178] a fifth processing unit, configured to jointly analyze the first angle information determined by the downlink and the second angle information extracted by the uplink, and construct a fused angle feature set including a main path of the user equipment and a reflection path of the second scatterer;

[0179] a sixth processing unit, configured to dynamically adjust the search range and iteration step of the orthogonal matching pursuit algorithm based on the fused angle feature set, perform atomic matching within a valid angle range, and determine an optimized matching pursuit algorithm;

[0180] The seventh processing unit is configured to output a channel impulse response estimation result including multipath delay, angle and complex gain based on the optimized matching pursuit algorithm.

[0181] It should be noted that the device in this embodiment is a device corresponding to the method applied to the base station side, and the implementation methods in the above embodiments are all applicable to the embodiments of the device and can achieve the same technical effects. The above-mentioned device provided in the embodiment of the present application can implement all the method steps implemented in the above-mentioned method embodiment and can achieve the same technical effects. The parts and beneficial effects that are the same as those in the method embodiment in this embodiment will not be described in detail here.

[0182] The embodiment of the present application further provides a computer-readable storage medium on which a computer program is stored, which implements the above-mentioned Figure 2 or Figure 3 The various processes of the method embodiments shown in the figure can achieve the same technical effect, and are not described here in detail to avoid repetition. The computer-readable storage medium is, for example, a read-only memory (ROM), a random access memory (RAM), a magnetic disk, or an optical disk.

[0183] The present application also provides a computer program product including computer instructions, which, when executed by a processor, implement the above Figure 2 or Figure 3 The various processes of the method embodiment shown can achieve the same technical effect, and to avoid repetition, they will not be described again here.

[0184] It should be noted that, in this document, the terms "comprises," "includes," or any other variations thereof are intended to encompass non-exclusive inclusion, such that a process, method, article, or apparatus comprising a series of elements includes not only those elements but also other elements not explicitly listed, or elements inherent to such process, method, article, or apparatus. In the absence of further limitations, an element defined by the phrase "comprising a ..." does not exclude the presence of other identical elements in the process, method, article, or apparatus comprising the element.

[0185] Through the description of the above implementation methods, those skilled in the art can clearly understand that the above-mentioned embodiment methods can be implemented by means of software plus the necessary general hardware platform, and of course can also be implemented by hardware, but in many cases the former is a better implementation method. Based on this understanding, the technical solution of the present application, or the part that contributes to the prior art, can be embodied in the form of a software product, and the computer software product is stored in a storage medium (such as ROM / RAM, magnetic disk, optical disk), including a number of instructions for enabling a terminal (which can be a mobile phone, computer, server, air conditioner, or network equipment, etc.) to execute the methods described in each embodiment of the present application.

[0186] The embodiments of the present application are described above in conjunction with the accompanying drawings, but the present application is not limited to the above-mentioned specific implementation methods. The above-mentioned specific implementation methods are merely illustrative and not restrictive. Under the guidance of this application, ordinary technicians in this field can also make many forms without departing from the purpose of this application and the scope of protection of the claims, all of which are within the protection of this application.

Claims

1. A channel estimation method, characterized in that: Applied to user equipment, including: Performing angle estimation on a base station and a first scatterer around the base station by using a discrete Fourier transform algorithm to determine first angle information; designing a codebooked transmit beamforming matrix according to the first angle information; An uplink pilot signal is sent to the base station based on the codebooked transmit beamforming matrix.

2. The method according to claim 1, characterized in that The method is configured to perform angle estimation on a base station and a first scatterer around the base station by using a discrete Fourier transform algorithm to determine first angle information, including: receiving a downlink reference signal sent by a base station; Performing a discrete Fourier transform on the downlink reference signal using a discrete Fourier transform algorithm to obtain frequency domain information; According to the frequency domain information and the antenna array geometry, the angle corresponding to the maximum peak is used as the base station line-of-sight path angle, and the remaining peak angles represent the angle information of the first scatterer; The base station line-of-sight path angle and the angle information of the first scatterer are determined as the first angle information.

3. The method according to claim 1, characterized in that Based on the first angle information, a codebooked transmit beamforming matrix is designed, including: generating a discretized angle set covering an angle interval according to the first angle information; Based on the array antenna structure characteristics of the user equipment and the discretized angle set, a beamforming vector set corresponding to each discrete angle is generated to form a codebooked transmit beamforming matrix.

4. A channel estimation method, characterized in that: Applied to base stations, including: receiving an uplink pilot signal sent by a user equipment; performing a discrete Fourier transform on the uplink pilot signal to extract second angle information of the user equipment and a second scatterer around the user equipment; According to the first angle information and the second angle information determined by the downlink, an orthogonal matching pursuit algorithm is dynamically optimized, and channel estimation information is determined based on the optimized matching pursuit algorithm.

5. The method according to claim 4, characterized in that Performing a discrete Fourier transform on the uplink pilot signal to extract second angle information of the user equipment and a second scatterer around the user equipment includes: Performing discrete Fourier transform processing on the uplink pilot signal to obtain frequency domain signal characteristics corresponding to the uplink pilot signal; extracting, based on the frequency domain signal characteristics, a set of peak components corresponding to the user equipment and a second scatterer around the user equipment; Calculating an estimated angle of arrival value corresponding to each peak component based on a phase difference characteristic of a signal received by an array antenna of the base station and the set of peak components; According to the arrival angle estimation values corresponding to the peak components, the main path angle of the user equipment and the reflection path angle of the second scatterer are jointly used to form the second angle information.

6. The method according to claim 4, characterized in that Dynamically optimizing an orthogonal matching pursuit algorithm according to the first angle information and the second angle information determined in the downlink, and determining channel estimation information based on the optimized matching pursuit algorithm, including: Performing a joint analysis on the first angle information determined by the downlink and the second angle information extracted by the uplink to construct a fused angle feature set including the main path of the user equipment and the reflection path of the second scatterer; Based on the fused angle feature set, the search range and iteration step of the orthogonal matching pursuit algorithm are dynamically adjusted, and atomic matching is performed within the effective angle range to determine the optimized matching pursuit algorithm. Based on the optimized matching pursuit algorithm, the output is the channel impulse response estimation result including multipath delay, angle and complex gain.

7. A channel estimation device, characterized in that Applied to user equipment, including: A first determining module is configured to perform angle estimation on a base station and a first scatterer around the base station by using a discrete Fourier transform algorithm to determine first angle information; A first processing module, configured to design a codebooked transmit beamforming matrix according to the first angle information; The second processing module is configured to send an uplink pilot signal to the base station based on the codebooked transmit beamforming matrix.

8. A channel estimation device, characterized in that Applied to base stations, including: A receiving module, configured to receive an uplink pilot signal sent by a user equipment; a third processing module, configured to perform discrete Fourier transform on the uplink pilot signal to extract second angle information of the user equipment and a second scatterer around the user equipment; The fourth processing module is used to dynamically optimize the orthogonal matching pursuit algorithm according to the first angle information and the second angle information determined by the downlink, and determine the channel estimation information based on the optimized matching pursuit algorithm.

9. A computer-readable storage medium, characterized in that The computer-readable storage medium stores a computer program, and when the computer program is executed by a processor, the steps of the method according to any one of claims 1 to 3 are implemented, or the steps of the method according to any one of claims 4 to 6 are implemented.

10. A computer program product, characterized in that The method comprises computer instructions, which, when executed by a processor, implement the steps of the method according to any one of claims 1 to 3, or implement the steps of the method according to any one of claims 4 to 6.

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