A method for multipath angle estimation in a RIS-assisted communication system and a RIS-assisted communication system

Abstract

The application relates to the technical field of wireless communication sensing, and discloses a multipath angle estimation method in an RIS-assisted communication system and an RIS-assisted communication system. After a transmission signal is divided into a frame structure, a reflection unit is used for signal activation, a reflection mode is acquired, a cascaded channel is constructed, and a composite receiving signal matrix is integrated and acquired; by designing a time-varying RIS reflection mode, a virtual uniform linear array is constructed under a single-antenna receiving condition, the spatial structure required for multipath angle estimation is recovered, and the limitation of a traditional method in a direct path missing scene is overcome. Meanwhile, based on the composite receiving signal, a forward and backward covariance matrix is constructed, is averaged, a forward-backward spatial smoothing covariance matrix is acquired, eigenvalue decomposition is carried out, an MUSE spatial spectrum of a decomposed characteristic vector is acquired, the angles of arrival of each dominant path in the RIS-assisted communication system are identified, and the problem of rank deficiency of a covariance matrix caused by the coherence of multipath signals is effectively solved.

Description

TECHNICAL FIELD

[0001] The present application relates to the technical field of wireless communication sensing, in particular to a method for multi-path angle estimation in a RIS-assisted communication system and a RIS-assisted communication system. BACKGROUND

[0002] Integrated sensing and communications (ISAC) as a key technology of the next generation wireless network aims to share hardware and spectrum resources to achieve efficient coordination of communication and sensing. Reconfigurable intelligent surfaces (RIS) have great potential in ISAC systems due to their excellent wireless environment regulation capability, especially for users without direct links. Based on this, using RIS to assist in achieving high-precision angle of arrival (AOA) estimation has become an important research direction. However, in a complex multipath propagation environment, coherent sources will cause the rank deficiency of the received signal covariance matrix, making high-resolution estimation algorithms such as MUSIC invalid. Existing RIS-assisted schemes focus on constructing sensing paths, but fail to effectively solve this core problem, limiting their sensing performance in real scenarios.

[0003] In RIS-assisted angle of arrival estimation, a major challenge is that the direct path (LOS) between the user and the base station (BS) may be blocked, causing traditional BS physical array-based estimation algorithms to fail. To solve this problem, existing methods carefully design the reflection pattern sequence of RIS to create a virtual multi-dimensional received signal in the time domain; this method enables the base station to use its time-domain signal to estimate the angle information from the user to the RIS, and the MUSIC algorithm can be applied to achieve angle estimation. However, it is only suitable for multi-user angle estimation in ideal direct path scenarios, and does not consider the rank deficiency problem of the virtual array covariance matrix caused by complete coherence of signals in the actual multipath propagation environment, which makes the MUSIC algorithm invalid in practical applications.

[0004] Currently, there are methods to use spatial smoothing preprocessing technology to solve the problem of signal coherence caused by multipath propagation. Spatial smoothing preprocessing technology restores the rank of the matrix by dividing the sub-array, and the forward smoothing scheme proposed by Evans and Shan et al. requires 2K sensors to estimate K coherent sources. In order to reduce the hardware requirement, Pillai and Kwon further proposed a forward-backward smoothing technology, which reduces the number of sensors required to 3K / 2 by jointly using forward and complex conjugate backward sub-arrays, effectively solving the problem of coherent signal estimation under physical sensor array. However, this method is mainly aimed at traditional physical array design and does not involve the specific problem of how to deal with multipath coherence and achieve efficient angle estimation in the virtual array constructed by RIS through time domain reflection.

[0005] In summary, there are two technical bottlenecks in implementing multipath angle estimation in RIS-assisted communication systems: First, in a multipath environment where the direct path is blocked, the base station's received signal lacks spatial structure and cannot directly apply traditional super-resolution direction finding algorithms such as MUSIC; Second, even if a virtual array is synthesized in the time domain through an innovative time-varying reflection protocol, the signal components of each path are completely coherent because they originate from the same reference signal, which causes the rank deficiency of the received covariance matrix of the virtual array, making MUSIC-based algorithms still ineffective. Therefore, existing technologies mainly consider de-coherent techniques in traditional physical arrays or consider angle estimation from multiple incoherent source signals in a simple non-scattering environment, but in a rich multipath scattering environment, multiple signal waveforms from the same source arriving through different paths are highly coherent. This coherence can cause the received signal covariance matrix to have a "rank deficiency", i.e., the rank of the matrix decreases to 1, which cannot accurately reflect the number of sources, and thus angle estimation cannot be achieved. SUMMARY

[0006] Therefore, the technical problem to be solved by the present application is to overcome the problem of rank deficiency of the received signal covariance matrix caused by signal coherence in the prior art, and thus the problem of angle estimation cannot be achieved.

[0007] To solve the above technical problems, the present application provides a method for multipath angle estimation in an RIS-assisted communication system, comprising:

[0008] dividing the transmitted signal into frame structures to form a continuous time block with frame structures, and constructing continuous time blocks;

[0009] In each continuous time block, a sliding window containing reflection units is used to activate the signal of each frame structure to obtain the reflection pattern of each frame structure in each continuous time block;

[0010] constructing a concatenated channel of each frame structure based on a user-RIS channel and a RIS-base station channel corresponding to the reflection mode of the frame structure;

[0011] integrating the concatenated channels of all frame structures in the transmitting signal to obtain a composite receiving signal matrix;

[0012] dividing each column receiving signal vector in the composite receiving signal matrix into a plurality of preset length overlapping forward sub-vectors; and performing set averaging on all overlapping forward sub-vectors to obtain a forward covariance matrix;

[0013] constructing each backward sub-vector corresponding to the anti-diagonal matrix and each overlapping forward sub-vector; and performing set averaging on all backward sub-vectors to obtain a backward covariance matrix;

[0014] averaging the forward covariance matrix and the backward covariance matrix to obtain a forward-backward spatial smoothing covariance matrix, performing eigenvalue decomposition to obtain a decomposed eigenvector;

[0015] constructing a MUSIC spatial spectrum based on the decomposed eigenvector to identify the angles of arrival of each dominant path in the RIS-assisted communication system.

[0016] Preferably, the transmitting signal is divided into frame structures, and a continuous time block is composed of frame structures. Preferably, the transmitting signal is divided into frame structures, and a continuous time block is composed of

[0017] frame structures. For the th continuous time block, the sample values of all frame structures in the continuous time block are the same, and are expressed as: , .

[0018] For the th continuous time block and the th continuous time block, the sample values of the frame structures in different continuous time blocks are different, and are expressed as: , .

[0019] wherein represents the sample value of the th frame structure in the th continuous time block, and represents the sample of the transmitting signal in the th continuous time block.

[0020] Preferably, in each continuous time block, the number of frame structures contained in the continuous time block is The sliding window of the reflection unit activates the signal of each frame structure, obtains the reflection pattern of each frame structure in each continuous time block, and is represented as:

[0021] ;

[0022] wherein, represents the reflection pattern of the m-th frame structure in the continuous time block, ; ; represents the linear phase offset term introduced by the n-th reflection unit in the sliding window in the m-th frame structure in the continuous time block, ; represents the imaginary unit, represents the n-th reflection unit in the sliding window, ; represents the RIS unit spacing, ; represents the preset phase offset parameter, represents the wavelength of the transmitted signal, represents the matrix transposition operation; represents the complex domain, represents the complex vector of .

[0023] Preferably, based on the user-RIS channel and the RIS-base station channel corresponding to the reflection pattern of each frame structure, a cascade channel of each frame structure is constructed, including:

[0024] Based on the reflection pattern of the m-th frame structure in the continuous time block, the RIS-BS channel corresponding to the n-th sliding window is constructed , and is represented as:

[0025] ;

[0026] Based on the reflection pattern of the m-th frame structure in the continuous time block, the UE-RIS channel corresponding to the n-th sliding window is constructed , and is represented as:

[0027] ;

[0028] Based on the RIS-BS channel and the UE-RIS channel corresponding to the n-th sliding window, the cascade channel of the m-th frame structure is obtained, and is represented as: ; wherein,

[0029] ​​​​​​​RIS-base station channel response steering vector element of the th reflecting element in the sliding window within the th frame structure in the consecutive time block, denotes the angle of departure at the RIS, RIS-base station channel response steering vector element of the th reflecting element in the sliding window within the th frame structure in the consecutive time block, denotes the angle of departure at the RIS, denotes the angle of departure at the RIS, denotes the angle of departure at the RIS, denotes the angle of departure at the RIS, denotes the total number of dominant paths in the RIS-aided communication system, denotes the main diagonal operation of the extraction matrix.

[0030] Preferably, the concatenated channel of all frame structures in the transmit signal is integrated to obtain a composite receive signal matrix, denoted as:

[0031]

[0032] wherein, denotes the composite receive signal matrix, denotes the concatenated channel vector composed of the concatenated channels of all frame structures, denoted as , denotes the concatenated channel of the th frame structure, denotes the transmit signal vector, denoted as , denotes the transmit signal sample corresponding to the th consecutive time block, denotes the noise matrix, denotes the complex number field, denotes the complex matrix of .

[0033] Preferably, each column receive signal vector in the composite receive signal matrix is respectively divided into a plurality of overlapping forward sub-vectors of a preset length; all the overlapping forward sub-vectors are set-averaged to obtain a forward covariance matrix, including:

[0034] The th column receive signal vector corresponding to the th consecutive time block in the composite receive signal matrix is divided into overlapping forward sub-vectors with a length of , and the th overlapping forward sub-vector​ is represented as:

[0035] ;

[0036] performing set averaging on all the overlapping forward sub-vectors to obtain a forward covariance matrix is represented as:

[0037] ;

[0038] wherein, denotes the element of ; , , , ; denotes conjugate transpose; denotes complex field, denotes the complex vector of , denotes the complex matrix of .

[0039] Preferably, based on the anti-diagonal matrix and each overlapping forward sub-vector, a corresponding each backward sub-vector is constructed; performing set averaging on all the backward sub-vectors to obtain a backward covariance matrix, comprising:

[0040] obtaining an anti-diagonal matrix ;

[0041] multiplying the anti-diagonal matrix and the conjugate matrix of the th overlapping forward sub-vector to obtain the th backward sub-vector is represented as: ;

[0042] performing set averaging on all the backward sub-vectors to obtain a backward covariance matrix is represented as:

[0043] .

[0044] Preferably, performing averaging on the forward covariance matrix and the backward covariance matrix to obtain a forward-backward spatial smoothing covariance matrix, performing eigenvalue decomposition to obtain a decomposed eigenvector, comprising:

[0045] performing averaging on the forward covariance matrix and the backward covariance matrix to obtain a forward-backward spatial smoothing covariance matrix is represented as: ;

[0046] forward-backward spatially smoothed covariance matrix Eigenvalue decomposition is performed, expressed as:

[0047] wherein, denotes the decomposed eigenvector.

[0048] Preferably, a MUSIC spatial spectrum is constructed based on the decomposed eigenvector, and the angles of arrival of each dominant path in the RIS-assisted communication system are identified, including:

[0049] The eigenvalues in the decomposed eigenvector are sorted from small to large, and the first P eigenvalues are obtained to form a noise subspace .

[0050] The MUSIC spatial spectrum of the noise subspace is calculated using a preset scanning parameter, expressed as:

[0051] The peak values in the MUSIC spatial spectrum are sorted from large to small, and the first K peak values are obtained as the angles of arrival of the K dominant paths;

[0052] wherein, and denote the composite steering vector of the cascaded UE-RIS-BS channel response and its conjugate transpose matrix, respectively, , denotes the steering vector element of the synthesized virtual array under the scanning angle, denotes a phase term, and the expression is . denotes the imaginary unit, denotes the RIS unit spacing, denotes a preset phase offset parameter, denotes the wavelength of the transmitted signal, denotes the scanning angle, denotes the angle of departure at the RIS, and denote the noise subspace and its corresponding conjugate transpose matrix, respectively.

[0053] The embodiment provides an RIS-assisted communication system, including:

[0054] A single-antenna user equipment for generating a transmitted signal;

[0055] An RIS containing a plurality of passive units for signal activation using reflective units to generate a corresponding reflection pattern;

[0056] ​​​​The base station equipped with a single antenna receives a transmitted signal from a single-antenna user equipment and a reflection pattern from the RIS, and estimates the angle of arrival of each dominant path by applying the multipath angle estimation method in the RIS-assisted communication system as described above.

[0057] The above technical solutions of the present application have the following beneficial effects compared with the prior art:

[0058] The multipath angle estimation method in the RIS-assisted communication system divides the transmitted signal into a frame structure, activates the signal using the reflection unit, obtains the reflection pattern, constructs a cascaded channel, and integrates the composite received signal matrix. By designing the time-varying RIS reflection pattern, a virtual uniform linear array is successfully constructed under the condition of single-antenna reception, effectively recovering the spatial structure required for multipath angle estimation, and overcoming the limitations of traditional methods in the absence of direct path scenarios. At the same time, based on the composite received signal, forward and backward covariance matrices are constructed, averaged to obtain a forward-backward spatial smoothing covariance matrix, eigenvalue decomposition is performed to obtain the MUSIC spatial spectrum of the decomposed eigenvectors, and the angle of arrival of each dominant path in the RIS-assisted communication system is identified. By introducing the forward-backward spatial smoothing technique, the problem of rank deficiency of the covariance matrix caused by the coherence of the multipath signal is effectively solved, enabling the stable application of super-resolution estimation algorithms such as MUSIC in the virtual array. Without significantly increasing the hardware complexity of the base station, the present application realizes high-precision and high-robustness estimation of the angle of arrival of multiple coherent signals in a complex multipath environment, improving the perception ability of the RIS-assisted communication system.

[0059] The RIS-assisted communication system of the present application, under the condition of limited base station antenna configuration, constructs an effective virtual uniform linear array by designing a time-varying RIS reflection pattern, and solves the problem of matrix rank deficiency caused by multipath coherence on this basis, ultimately realizing high-precision and high-robustness estimation of the angle of arrival of multiple coherent signals in a complex multipath environment. BRIEF DESCRIPTION OF DRAWINGS

[0060] In order to make the content of the present application easier to be clearly understood, the following further describes the present application in detail according to specific embodiments of the present application and in conjunction with the drawings, in which:

[0061] Figure 1 is a step flow chart of the multipath angle estimation method in the RIS-assisted communication system of the present application;

[0062] Figure 2 is a structural schematic diagram of the RIS-assisted communication system;

[0063] Figure 3This is a comparison of the performance impact curves of the virtual array aperture of RIS on communication success rate under different combinations of the number of consecutive time blocks and the sliding window length.

[0064] Figure 4 This is a comparison of the performance impact curves of the virtual array aperture of RIS on the root mean square error under different combinations of the number of continuous time blocks and the sliding window length.

[0065] Figure 5 This is a comparison chart of communication success rate curves under different frame structures and the number of consecutive time blocks;

[0066] Figure 6 This is a comparison chart of the root mean square error curves under different frame structures and the number of consecutive time blocks;

[0067] Figure 7 This is a comparison chart of the communication success rate versus SNR under different numbers of consecutive time blocks;

[0068] Figure 8 This is a comparison chart of the performance curves of RMSE as a function of SNR under different numbers of consecutive time blocks. Detailed Implementation

[0069] The present invention will be further described below with reference to the accompanying drawings and specific embodiments, so that those skilled in the art can better understand and implement the present invention. However, the embodiments described are not intended to limit the present invention.

[0070] Reference Figure 1 The flowchart shown illustrates the steps of the multipath angle estimation method in the RIS-assisted communication system of the present invention. The specific steps include:

[0071] S101: Divide the transmitted signal into... A frame structure, in continuous Each frame structure forms a continuous time block, constructing A continuous time block;

[0072] S102: In each consecutive time block, utilize the included... The sliding window of each reflection unit activates the signal for each frame structure, obtaining the reflection mode of each frame structure in each consecutive time block, as shown below:

[0073] ;

[0074] in, Indicates the first time block in a continuous time block Reflection patterns in frame structures ; Indicates the first time block in a continuous time block The first frame in the sliding window linear phase offset term introduced by the denotes imaginary unit, denotes the th reflection unit in the sliding window, ; denotes RIS unit spacing, denotes preset phase offset parameter, denotes transmit signal wavelength, denotes matrix transpose operation; denotes complex field, denotes complex vector of

[0075] S103: based on the user-RIS channel and the RIS-base station channel corresponding to the reflection mode of each frame structure, construct the cascade channel of each frame structure, including:

[0076] S103-1: based on the reflection mode of the th frame structure in the continuous time block, construct the RIS-BS channel corresponding to the th sliding window, denoted as:

[0077] ;

[0078] S103-2: based on the reflection mode of the th frame structure in the continuous time block, construct the UE-RIS channel corresponding to the th sliding window, denoted as:

[0079] ;

[0080] S103-3: based on the RIS-BS channel and the UE-RIS channel corresponding to the th sliding window, obtain the cascade channel of the th frame structure, denoted as: ;

[0081] wherein, denotes the RIS-base station channel response steering vector element of the th reflection unit in the sliding window within the th frame structure in the continuous time block, denotes the angle of departure at the RIS, denotes the user-RIS channel response steering vector element of the th reflection unit in the sliding window within the th frame structure in the continuous time block, denotes the ​​the corresponding angle of arrival of the dominant path at the RIS, the first the complex path gain of the corresponding angle of arrival of the dominant path at the RIS, the total number of dominant paths in the RIS-aided communication system, representing a main diagonal operation of the extraction matrix;

[0082] S104: integrating the concatenated channels of all frame structures in the transmitted signal to obtain a composite received signal matrix, denoted as:

[0083] ;

[0084] wherein, the composite received signal matrix; the concatenated channel vector composed of the concatenated channels of all frame structures, denoted as , the first frame structure; the transmitted signal vector, denoted as , the transmitted signal sample of the continuous time block, the noise matrix; the complex field, the complex matrix of ;

[0085] S105: dividing each column received signal vector in the composite received signal matrix into a plurality of overlapping forward sub-vectors of a preset length, respectively; performing set averaging on all overlapping forward sub-vectors to obtain a forward covariance matrix, including:

[0086] S105-1: dividing the column received signal vector corresponding to the continuous time block in the composite received signal matrix into overlapping forward sub-vectors of length , the overlapping forward sub-vector , denoted as:

[0087] ;

[0088] S105-2: performing set averaging on all overlapping forward sub-vectors to obtain a forward covariance matrix , denoted as:

[0089] ;

[0090] wherein, denotes the th element of , , ; denotes conjugate transpose; denotes complex field, denotes a complex vector of denotes a complex matrix of

[0091] S106: constructing each backward sub-vector corresponding to each overlap forward sub-vector based on the anti-diagonal matrix; performing set average on all the backward sub-vectors to obtain a backward covariance matrix, comprising:

[0092] S106-1: obtaining the anti-diagonal matrix ;

[0093] S106-2: multiplying the anti-diagonal matrix by the conjugate matrix of the th overlap forward sub-vector to obtain the th backward sub-vector , denoted as: ;

[0094] S106-3: performing set average on all the backward sub-vectors to obtain a backward covariance matrix , denoted as: ;

[0095] S107: performing average on the forward covariance matrix and the backward covariance matrix to obtain a forward-backward spatial smoothing covariance matrix, performing eigenvalue decomposition to obtain a decomposed eigenvector, comprising:

[0096] S107-1: performing average on the forward covariance matrix and the backward covariance matrix to obtain a forward-backward spatial smoothing covariance matrix , denoted as: ;

[0097] S107-2: performing eigenvalue decomposition on the forward-backward spatial smoothing covariance matrix , denoted as: ;

[0098] wherein, denotes the decomposed eigenvector;

[0099] S108: Construct a MUSIC spatial spectrum based on the decomposed eigenvectors to identify the angles of arrival of each dominant path in the RIS-assisted communication system, including:

[0100] S108-1: Sort the eigenvalues in the decomposed eigenvectors from small to large, obtain the first eigenvalues, and form a noise subspace ;

[0101] S108-2: Calculate the MUSIC spatial spectrum of the noise subspace using the preset scanning parameters, denoted as: ;

[0102] S108-3: Sort the peak values in the MUSIC spatial spectrum from large to small, obtain the first K peak values as the angles of arrival of the K dominant paths;

[0103] wherein, and respectively represent the composite steering vector of the cascaded UE-RIS-BS channel response and its conjugate transpose matrix, , represents the steering vector element of the synthesized virtual array under the scanning angle, represents the phase term, and the expression is ; represents the imaginary unit, represents the RIS unit spacing, represents the preset phase offset parameter, represents the wavelength of the transmitted signal, represents the scanning angle, represents the angle of departure at the RIS, and respectively represent the noise subspace and its corresponding conjugate transpose matrix.

[0104] Specifically, in step S101, the transmitted signal is divided into frame structures, and frame structures form a continuous time block, and continuous time blocks are constructed, including:

[0105] S101-1: For the continuous time block, the sample values of all frame structures within it are the same, denoted as: , , ;

[0106] S101-2: For the continuous time block and the ​a sample value of a frame structure in the i-th continuous time block, and the sample values of the frame structure in different continuous time blocks are different, denoted as: , ;

[0107] wherein, denotes a sample value of a frame structure in the i-th continuous time block, denotes a sample value of a frame structure in the i-th continuous time block, denotes a sample value of a frame structure in the i-th continuous time block, denotes a sample value of a frame structure in the i-th continuous time block.

[0108] The application organizes the transmission signal into a frame structure containing P*Q samples, and divides it into Q time blocks; in each time block, a sliding window activation mechanism is used to control the RIS reflection unit, and the phase design induces linear phase evolution, thereby constructing a virtual array.

[0109] Based on the above embodiment, the application also provides an RIS-assisted communication system, comprising:

[0110] A single-antenna user equipment for generating a transmission signal;

[0111] An RIS containing a plurality of passive units for signal activation using reflection units to generate a corresponding reflection pattern;

[0112] A base station equipped with a single antenna, which receives the transmission signal from the single-antenna user equipment and the reflection pattern from the RIS, and applies the multipath angle estimation method in the RIS-assisted communication system as described above to estimate and obtain the angles of arrival of each dominant path.

[0113] The RIS-assisted communication system of the application, under the condition of limited base station antenna configuration, constructs an effective virtual uniform linear array by designing time-varying RIS reflection patterns, and solves the problem of matrix rank deficiency caused by multipath coherence, and finally realizes high-precision and high-robustness estimation of the angles of arrival of multiple coherent signals in a complex multipath environment.

[0114] Based on the above embodiment, the application provides a method for realizing multipath angle estimation in a reconfigurable intelligent surface (RIS)-assisted communication system, aiming to solve the deficiencies of the prior art in virtual array construction and multipath coherence processing. Specifically, the system contains a single-antenna user equipment UE, an RIS with I passive units, and a base station BS equipped with M uniformly linear array ULA arranged antennas. Referring to Figure 2 , which is a structural schematic diagram of the RIS-assisted communication system.

[0115] Further, the system works in an uplink scenario, and the signal sent by the user is transmitted through the UE-RIS-BS cascade channel, received by the base station and processed. The received signal of the base station can be represented as:​

[0116] ;

[0117] in, For the RIS-BS channel matrix, This is the diagonal matrix of the RIS reflection mode. For UE-RIS channel vector, Indicates the transmission of a signal; This represents additional white Gaussian noise (AWGN), whose components obey... The Gaussian distribution.

[0118] Among them, the RIS-BS channel matrix It is composed of the outer product of the corresponding guide vectors, and is expressed as , To be from an angle The guiding vector is a feature. Indicates the angle of arrival (AOA) at the base station. Indicates the departure angle (AOD) at RIS; , ;when At that time, calculate , obtain ;when At that time, calculate , obtain .

[0119] Among them, the UE-RIS channel vector Characterized as a multipath channel, containing independent propagation paths, its expression is: ; and They represent the first The path corresponds to the angle of arrival at RIS. The steering vector and complex path gain.

[0120] Although the base station receives signals It contains angle information, but because it contains the steering vector corresponding to the UE-RIS channel and the RIS side departure angle, it is important to note that this information is not directly related to the angle information. The multiplication results in a scalar, causing the base station to be unable to obtain the steering vector. Effective spatial information is extracted from it. Therefore, to simplify the analysis and focus on the essence of the problem, the signal received by the first antenna is selected as the object of analysis without loss of generality; at this time, the RIS-BS channel degenerates into However, such scalar measurements inherently lack the spatial structure required to resolve multipath angles of arrival, rendering traditional high-resolution estimation algorithms such as MUSIC inapplicable.

[0121] In this embodiment, to overcome the above limitations, the present invention proposes a time-domain transmission protocol combining a specific RIS reflection mode. By constructing a virtual ULA structure in the time domain, the spatial information required for angle estimation is recovered. The virtual array response is ultimately extracted in the form of a spatial covariance matrix and must satisfy the rank condition required for multipath resolution and angle estimation. The specific steps of multipath angle estimation include:

[0122] S201: Organize the transmitted signal into a form containing The frame structure of each sample is divided into: A series of consecutive time blocks, each containing One sample. The transmitted signal remains constant within each time block, but varies between different time blocks, satisfying:

[0123] ;

[0124] S202: The core mechanism of virtual ULA synthesis lies in the reflection mode design of RIS. Specifically, within each time block, a sliding window activation mechanism is used to control... The first reflection unit. Within each time block, the first... The reflection pattern of each sample is designed as follows:

[0125] ;

[0126] S203: This time-varying reflection mode is in all Repeat consistently within each time block. Therefore, the first... The cascaded channels at each time sample (denoted as ) ) is represented as:

[0127] ;

[0128] in, and These represent the corresponding reflection modes. The The RIS-BS channel and UE-RIS channel with a sliding window are represented as follows:

[0129] ;

[0130] ;

[0131] in, This represents the RIS-base station channel response steering vector element of the l-th reflection unit in the sliding window within the p-th frame structure of a continuous time block. Indicates the departure angle at RIS. This represents the user-RIS channel response steering vector element of the l-th reflection unit in the sliding window within the p-th frame structure of a continuous time block. Indicates the first The angle of arrival of the dominant path at RIS Indicates the first The complex path gain of the dominant path at the RIS corresponding to the angle of arrival. This represents the total number of dominant paths in a RIS-assisted communication system. This indicates the operation of extracting the main diagonal of a matrix.

[0132] S204: By integrating the full-frame received signals, the composite received signal matrix at the base station can be represented as:

[0133] ;

[0134] in, For cascaded channel vectors, The transmitted signal vector, This is the noise matrix.

[0135] This invention enables flexible adjustment of the sensing beamwidth, and its adjustment mechanism is related to the design of the virtual array aperture and RIS reflection mode.

[0136] Based on the above embodiments, in order to verify the effectiveness of the proposed protocol in multipath angle estimation, the following theoretical analysis is performed:

[0137] Given the first In the nth sample Reflection mode of a sliding window Cascaded channels can be explicitly derived into a geometric series form: ;in, This expression indicates that for each time sample All include the sample index Phase term of linear evolution This linear phase evolution characteristic is key to the synthesis of virtual array structures in the time domain. By aggregating all... Each channel response, combined into a composite channel vector. It can be represented as The superposition of several virtual guide vectors. Specifically, this manifests as:

[0138] ;

[0139] in, Indicates the first The complex amplitude of the path; the structure exhibits typical ULA response characteristics, indicating that the protocol proposed in this embodiment successfully converts the time-domain measurements of a single-antenna receiver into... Metamaterial virtual array response , thereby encoding the angular information of all propagation paths in its spatial structure.

[0140] However, although the virtual array is constructed successfully, The multipath components in each snapshot are fully coherent because they originate from the same reference signal, which will result in a rank deficiency of the received signal covariance matrix, thus hindering the effective application of the MUSIC algorithm. To solve this rank deficiency problem, the present application introduces the forward-backward spatial smoothing (FBSS) technique, which realizes the decorrelation of coherent sources through subarray averaging and forward-backward joint processing, thereby recovering the rank of the covariance matrix.

[0141] S301: Specifically, let denote the received signal matrix , and let denote the received signal vector during the th transmission block. To apply the forward-backward spatial smoothing technique, each is divided into overlapping forward subvectors of length , where is selected to satisfy . The th forward subvector is defined as:

[0142] ;

[0143] where denotes the th element of ;

[0144] S302: By performing set averaging on all subvector positions and transmission blocks, the forward covariance matrix is obtained, which is represented as:

[0145] ;

[0146] S303: To construct the backward subvector, the anti-diagonal matrix is introduced, which is defined as: ; using the anti-diagonal matrix, the th backward subvector is constructed, which is represented as: ; the backward covariance matrix is calculated using the same set averaging method, which is represented as: ;

[0147] S304: By averaging the forward and backward covariance estimates, the forward-backward spatial smoothing covariance matrix , is denoted as: ;

[0148] S305: Perform eigenvalue decomposition on the forward-backward spatially smoothed covariance matrix to apply the MUSIC algorithm;

[0149] The eigenvalue decomposition is denoted as: ;

[0150] Let denote the noise subspace consisting of eigenvectors corresponding to the smallest eigenvalues. The MUSIC spatial spectrum is calculated by scanning the parameter : ;

[0151] where, is the composite steering vector of the cascaded UE-RIS-BS channel response, whose expression is ; the phase term is defined as: ;

[0152] By identifying the largest peaks in the spatial spectrum , the angles of arrival from each dominant path can be estimated.

[0153] The present application successfully constructs a virtual array with spatial resolution capability under the condition of not significantly increasing the base station antenna configuration, effectively overcomes the algorithm limitations brought by multipath coherence, and finally realizes high-precision and high-robust estimation of the multipath angle of arrival in a complex propagation environment.

[0154] The present application successfully constructs a virtual uniform linear array under the condition of single antenna reception by designing time-varying RIS reflection patterns, effectively restores the spatial structure required for multipath angle estimation, and overcomes the limitations of traditional methods in the absence of direct path scenarios. At the same time, the forward-backward spatial smoothing technique is introduced, effectively solving the problem of rank deficiency of the covariance matrix caused by multipath signal coherence, so that super-resolution estimation algorithms such as MUSIC can be stably applied in virtual arrays. The present application realizes high-precision and high-robust estimation of the angles of arrival of multiple coherent signals in a complex multipath environment without significantly increasing the hardware complexity of the base station, improving the perception ability of the RIS-assisted communication system. The present application has good scalability and adaptability, and is suitable for various practical communication scenarios such as Internet of Vehicles, emergency rescue, etc., and has strong practical value.

[0155] Based on the above embodiments, to verify the effectiveness and superiority of the method proposed in this invention, this embodiment conducts a systematic performance evaluation through a series of simulation experiments. The simulation focuses on exploring the impact of different system parameters on the performance of multipath angle estimation, and uses the detection communication success rate and root mean square error (RMSE) as the core evaluation indicators.

[0156] The simulation settings are as follows: the number of multipaths K is set to 4. In this embodiment, a successful detection is defined as the algorithm correctly detecting 3 paths, with the angle estimation deviation of all detected paths not exceeding 2°. RMSE is calculated based on the angles of all successfully detected paths to measure the estimation accuracy.

[0157] First, this embodiment examines the impact of the virtual array aperture (P) of the RIS on performance. With a signal-to-noise ratio (SNR) of 0 dB, this embodiment fixes the RIS sliding window length L at 32 and 128, and varies the number of transport blocks Q (taking values ​​of 1, 2, 5, and 10) to obtain the performance curves. (Refer to...) Figure 3 The figure shows a comparison of the performance impact curves of the RIS virtual array aperture on communication success rate under different combinations of the number of consecutive time blocks and the sliding window length; refer to... Figure 4 The figure shows a comparison of the performance impact curves of the virtual array aperture on the root mean square error of the RIS under different combinations of the number of consecutive time blocks and the sliding window length; based on Figure 3 and Figure 4 The simulation results clearly show that parameter L has a relatively weak impact on estimation performance; in contrast, parameter P plays a crucial role. With L and Q fixed, as P increases, the system's successful detection probability significantly improves, while the RMSE steadily decreases. This strongly demonstrates that increasing the virtual array aperture P can effectively enhance the system's resolution and estimation accuracy. Furthermore, Figure 4 This also reveals that the parameter Q has a significant impact on performance.

[0158] As can be seen from the technical solution of this invention, the total frame length of the transmitted signal is To further clarify the respective roles of P and Q under the total frame length constraint, this embodiment sets up a comparative experiment with a fixed total sample size, and the results are as follows. Figure 5 and Figure 6 As shown. (Refer to...) Figure 5 The figure shown is a comparison of communication success rate curves under different frame structures and the number of consecutive time blocks; refer to Figure 6 The figure shows a comparison of the root mean square error curves under different frame structures and the number of consecutive time blocks; analysis Figure 5 and Figure 6It can be seen that when the total frame length is constant, the change of Q in a certain range has little effect on the success rate, but the RMSE decreases obviously with the decrease of Q, that is, the corresponding increase of P. This finding has important engineering guiding significance, which proves that in the limited time domain resource, preferentially increasing the virtual array aperture P can more effectively improve the angle estimation accuracy compared with increasing the transmission block diversity Q.

[0159] Finally, the robustness of the algorithm under different signal-to-noise ratio conditions is evaluated. Figure 7 With Figure 8 The curves of success rate and RMSE changing with signal-to-noise ratio SNR under different Q settings are shown. Figure 7 The performance curve comparison diagram of communication success rate changing with SNR under different numbers of continuous time blocks is shown. Figure 8 The performance curve comparison diagram of RMSE changing with SNR under different numbers of continuous time blocks is shown.

[0160] In summary, through detailed simulation analysis, it is fully verified that the method of the present application can realize high success rate and high precision angle estimation in a complex multipath environment. The simulation results clearly show the influence law of key parameters P, Q, L and SNR on performance, providing valuable design guidance for actual system configuration, highlighting the practical value and engineering feasibility of the present application.

[0161] The multipath angle estimation method in the RIS-assisted communication system divides the transmitted signal into a frame structure, uses the reflection unit to activate the signal and obtain the reflection mode to construct the cascaded channel and integrate the composite received signal matrix; by designing the time-varying RIS reflection mode, a virtual uniform linear array is successfully constructed under single-antenna reception conditions, effectively recovering the spatial structure required for multipath angle estimation, overcoming the limitations of traditional methods in the absence of direct path scenarios. At the same time, based on the composite received signal, forward and backward covariance matrices are constructed, averaged to obtain a forward-backward spatial smoothing covariance matrix, eigenvalue decomposition is performed to obtain the MUSIC spatial spectrum of the decomposed eigenvectors, and the angles of arrival of each dominant path in the RIS-assisted communication system are identified. By introducing the forward-backward spatial smoothing technique, the problem of rank deficiency of the covariance matrix caused by the coherence of the multipath signal is effectively solved, enabling the stable application of super-resolution estimation algorithms such as MUSIC in virtual arrays. The present application realizes high-precision and high-robustness estimation of the angles of arrival of multiple coherent signals in a complex multipath environment without significantly increasing the hardware complexity of the base station, improving the perception ability of the RIS-assisted communication system.

[0162] Those skilled in the art will appreciate that embodiments of the application can be devised for a method, a system, or a computer program product. Accordingly, the present application can be embodied in the form of an entirely hardware embodiment, an entirely software embodiment, or an embodiment combining software and hardware aspects. Furthermore, the present application can take the form of a computer program product on one or more computer-usable storage media (including, but not limited to, disk storage, CD-ROMs, optical storage devices, etc.) embodying computer readable program code.

[0163] The present application is described in reference to the flowchart illustrations and / or block diagrams of methods, apparatus (systems) and computer program products according to embodiments of the application. It will be understood that each block of the flowchart illustrations and / or block diagrams, and combinations of blocks in the flowchart illustrations and / or block diagrams, can be implemented by computer program instructions. These computer program instructions can be provided to a processor of a general purpose computer, special purpose computer, embedded processor, or other programmable data processing apparatus to produce a machine, such that the instructions, which execute via the processor of the computer or other programmable data processing apparatus, create means for implementing the functions specified in the flowchart illustrations and / or block diagrams. Figure 1 one or more functions specified in the flowchart illustrations and / or block diagrams. Figure 1 one or more functions specified in the flowchart illustrations and / or block diagrams.

[0164] These computer program instructions can also be stored in a computer- readable memory that can direct a computer or other programmable data processing apparatus to function in a particular manner, such that the instructions stored in the computer-readable memory produce an article of manufacture including instructions which implement the functions specified in the flowchart illustrations and / or block diagrams. Figure 1 one or more functions specified in the flowchart illustrations and / or block diagrams. Figure 1 one or more functions specified in the flowchart illustrations and / or block diagrams.

[0165] These computer program instructions can also be loaded onto a computer or other programmable data processing apparatus to cause a series of operational steps to be performed on the computer or other programmable apparatus to produce a computer-implemented process such that the instructions which execute on the computer or other programmable apparatus provide steps for implementing the functions specified in the flowchart illustrations and / or block diagrams. Figure 1 one or more functions specified in the flowchart illustrations and / or block diagrams. Figure 1 one or more functions specified in the flowchart illustrations and / or block diagrams.

[0166] Obviously, the above-described embodiments are only examples and are not intended to limit the present application. Based on the above description, those skilled in the art can make other variations and modifications of the present application without departing from the present application. Neither requiring nor intending to limit the present application to the exact forms of implementations shown and described, the application is to cover all modifications and alternatives arising from the practical application of the ideas expressed.

Claims

1. A multipath angle estimation method in a RIS-assisted communication system, characterized in that, include: The transmitted signal is divided into A frame structure, in continuous Each frame structure forms a continuous time block, constructing A continuous time block; In each consecutive time block, using the inclusion The sliding window of each reflection unit activates the signal for each frame structure to obtain the reflection mode of each frame structure in each consecutive time block. Based on the user-RIS channel and RIS-base station channel corresponding to the reflection mode of each frame structure, a cascaded channel of each frame structure is constructed. The concatenated channels of all frame structures in the transmitted signal are integrated to obtain the composite received signal matrix; Each column of the received signal vector in the composite received signal matrix is ​​divided into multiple overlapping forward sub-vectors of a preset length. The forward covariance matrix is ​​obtained by ensemble averaging of all overlapping forward sub-vectors. Based on the anti-angle matrix and each overlapping forward sub-vector, construct the corresponding backward sub-vectors; The backward covariance matrix is ​​obtained by ensemble averaging of all backward subvectors. The forward and backward covariance matrices are averaged to obtain the forward-backward spatial smooth covariance matrix, and eigenvalue decomposition is performed to obtain the decomposed eigenvectors. Based on the decomposed feature vectors, a MUSIC spatial spectrum is constructed to identify the angle of arrival of each dominant path in the RIS-assisted communication system.

2. The multipath angle estimation method in the RIS-assisted communication system according to claim 1, characterized in that, The transmitted signal is divided into A frame structure, in continuous Each frame structure forms a continuous time block, constructing A series of consecutive time blocks, including: For the A series of consecutive time blocks, in which all frame structures have the same sample values, are represented as: , , ; For the The consecutive time block and the first There are several consecutive time blocks, and the sample values ​​of the frame structure are different in different consecutive time blocks, represented as follows: , ; in, Indicates the first In the nth consecutive time block Sample values ​​of each frame structure Indicates the first Transmitted signal samples of a continuous time block.

3. The multipath angle estimation method in the RIS-assisted communication system according to claim 1, characterized in that, In each consecutive time block, using the inclusion The sliding window of each reflection unit activates the signal for each frame structure, obtaining the reflection mode of each frame structure in each consecutive time block, as shown below: ； in, Indicates the first time block in a continuous time block Reflection patterns in frame structures ; Indicates the first time block in a continuous time block The first frame in the sliding window The linear phase shift term introduced by each reflective unit, Represents the imaginary unit. Indicates the first in the sliding window One reflective unit, ; Indicates the RIS cell spacing. This indicates the preset phase offset parameter. Indicates the wavelength of the transmitted signal. This represents the matrix transpose operation; Represents the field of complex numbers. express A complex vector.

4. The multipath angle estimation method in the RIS-assisted communication system according to claim 3, characterized in that, Based on the user-RIS channel and RIS-base station channel corresponding to the reflection modes of each frame structure, a cascaded channel for each frame structure is constructed, including: Based on the first continuous time block The reflection pattern of the frame structure is used to construct the first frame. RIS-BS channel corresponding to each sliding window , represented as: ； Based on the first continuous time block The reflection pattern of the frame structure is used to construct the first frame. UE-RIS channel corresponding to each sliding window , represented as: ； Based on the The RIS-BS channel and UE-RIS channel corresponding to the sliding window are obtained to acquire the first sliding window. A cascaded channel with a frame structure is represented as follows: ; in, Indicates the first time block in a continuous time block The first frame in the sliding window RIS-base station channel response steering vector elements of each reflection unit Indicates the departure angle at RIS. Indicates the first time block in a continuous time block The first frame in the sliding window User-RIS channel response steering vector element of each reflection unit Indicates the first The angle of arrival of the dominant path at RIS Indicates the first The complex path gain of the dominant path at the RIS corresponding to the angle of arrival. This represents the total number of dominant paths in a RIS-assisted communication system. This indicates the operation of extracting the main diagonal of a matrix.

5. The multipath angle estimation method in the RIS-assisted communication system according to claim 1, characterized in that, By integrating the concatenated channels of all frame structures in the transmitted signal, a composite received signal matrix is ​​obtained, represented as: ； in, Represents the composite received signal matrix; The concatenated channel vector, representing the concatenated channels of all frame structures, is denoted as: , Indicates the first A cascaded channel with a frame structure; The transmitted signal vector is represented as... , Indicates the first Transmitted signal samples of a continuous time block, Represents the noise matrix; Represents the field of complex numbers. express A complex matrix.

6. The multipath angle estimation method in the RIS-assisted communication system according to claim 1, characterized in that, Each column of the received signal vector in the composite received signal matrix is ​​divided into multiple overlapping forward sub-vectors of a preset length. Perform a ensemble average of all overlapping forward sub-vectors to obtain the forward covariance matrix, including: The first in the composite received signal matrix The corresponding _th consecutive time block Column received signal vector Divided into A length of The overlapping forward sub-vectors, the first overlapping forward subvectors , represented as: ； Perform ensemble averaging on all overlapping forward subvectors to obtain the forward covariance matrix. , represented as: ； in, express The One element; , , ; Indicates conjugate transpose; Represents the field of complex numbers. express Complex vectors, express A complex matrix.

7. The multipath angle estimation method in the RIS-assisted communication system according to claim 6, characterized in that, Based on the anti-angle matrix and each overlapping forward sub-vector, construct the corresponding backward sub-vectors; The backward covariance matrix is ​​obtained by ensemble averaging of all backward subvectors, including: Obtain the anti-diagonal matrix ; Connect the anti-diagonal matrix with the first The conjugate matrix of overlapping forward sub-vectors Multiply to obtain the first... backward sub-vectors , represented as: ; The backward covariance matrix is ​​obtained by ensemble averaging of all backward subvectors. , represented as: 。 8. The multipath angle estimation method in the RIS-assisted communication system according to claim 7, characterized in that, The forward and backward covariance matrices are averaged to obtain the forward-backward spatially smoothed covariance matrix. Eigenvalue decomposition is then performed to obtain the decomposed eigenvectors, including: For the forward covariance matrix With backward covariance matrix Averaging is performed to obtain the forward-backward spatially smoothed covariance matrix. , represented as: ; Smoothing covariance matrix in forward-backward space Eigenvalue decomposition is performed, which is expressed as: ; in, This represents the eigenvectors after decomposition.

9. The multipath angle estimation method in the RIS-assisted communication system according to claim 8, characterized in that, Based on the decomposed eigenvectors, a MUSIC spatial spectrum is constructed to identify the angle of arrival of each dominant path in the RIS-assisted communication system, including: Sort the eigenvalues ​​in the decomposed eigenvectors from smallest to largest, and obtain the top... Each eigenvalue forms a noise subspace. ; Using preset scanning parameters, calculate the MUSIC spatial spectrum of the noise subspace. , represented as: ; The peaks in the MUSIC spatial spectrum are sorted from largest to smallest, and the top K peaks are used as the angles of arrival for the K dominant paths. in, and Let represent the composite steering vector and its conjugate transpose matrix of the cascaded UE-RIS-BS channel response, respectively. , This represents the steering vector element of the cascaded channel response of the synthetic virtual array at the scanning angle. The phase term is represented by the expression: ; Represents the imaginary unit. Indicates the RIS cell spacing. This indicates the preset phase offset parameter. Indicates the wavelength of the transmitted signal. Indicates the scanning angle. Indicates the departure angle at RIS. and Let represent the noise subspace and its corresponding conjugate transpose matrix, respectively.

10. A RIS-assisted communication system, characterized in that, include: Single-antenna user equipment used to generate transmit signals; A RIS containing multiple passive units is used to activate signals using reflection units to generate corresponding reflection modes. A base station equipped with a single antenna receives transmitted signals from a single-antenna user equipment and reflection patterns from a RIS (Reflection Signal System), and uses the multipath angle estimation method in the RIS-assisted communication system as described in any one of claims 1 to 9 to estimate and obtain the angle of arrival of each dominant path.

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