Cascading channel estimation method based on time correlation for XLHRIS system

Abstract

The invention discloses a cascade channel estimation method based on time correlation for an XLHRIS system, and the method comprises the steps: at an initial moment, an XLHRIS firstly designs an optimal active unit selection scheme through the XLHRIS side angle information detected from a received pilot signal, and then precisely estimates the XLHRIS side distance information; comprising an uplink channel parameter between the XLHRIS and a user and a downlink channel parameter between the XLHRIS and a base station; then, the XLHRIS designs a phase shift scheme according to the estimated XLHRIS side space parameters, enhances the BS side receiving signal power to assist in completing BS side channel parameter estimation, and reconstructs a cascade channel; and finally, the XLHRIS quickly reconstructs the time-varying near-field channel based on the low-dimensional sub-dictionary by using the time strong correlation between the time-varying channels at the subsequent moment. The invention provides a time-varying cascade channel estimation method of an XLHRIS system, and particularly solves the problem of time-varying cascade channel CSI acquisition in a high-speed mobile scene.

Description

Technical Field

[0001] The invention relates to a cascade channel estimation method based on time correlation for an XLHRIS system, and in particular to a near-field time-varying cascade channel estimation method based on time correlation for a TDD ultra-large-scale HRIS auxiliary system, belonging to the technical field of channel estimation. Background Art

[0002] The rapid growth in the demand for spectrum efficiency in the sixth generation of wireless communication systems has stimulated the development of many emerging technologies. Reconfigurable smart surfaces (RIS) are composed of multiple metamaterial units, each of which can be controlled in an almost completely passive manner, and have attracted increasing attention in recent years. RIS has the characteristics of high array gain, low hardware cost, low power consumption, and negligible noise. It is considered to be a promising technology for obtaining enhanced spectrum efficiency and energy efficiency in the sixth generation of wireless communication systems. In order to maximize the communication performance improvement brought by RIS, the base station (BS) needs to know the channel state information in advance. However, the cascaded channel characteristics brought by RIS make channel estimation have a large overhead. Due to the mobile characteristics of users, how to complete channel reconstruction with lower time overhead needs to be studied and explored. Therefore, the estimation of cascaded channels has become one of the difficult problems of RIS-assisted systems.

[0003] The mainstream RIS architecture currently under consideration is a pure passive RIS structure. All RIS units can only reflect the incident signal and do not have the ability to receive and process signals. The channel state information (CSI) estimation process is completely completed by the BS. The user (UE) sends multiple uplink pilot signals. The BS estimates the RIS side channel parameters and the BS side channel parameters respectively through the received pilot signals and reconstructs the cascaded channel. However, most passive RIS system CSI estimation requires the user to send pilot signals equal to the number of RIS units. As the number of RIS units increases, the pilot overhead will be greatly increased, and it cannot be efficiently applied to the sixth generation wireless communication system with strong user mobility. In addition, in the passive RIS system, the BS can only obtain the cascaded channel CSI, but cannot obtain the separated channel state information. RIS cannot use the separated CSI to design phase-assisted wireless communication performance. Therefore, CSI acquisition in the ultra-large-scale hybrid reconfigurable smart surface (XLHRIS) system becomes a bottleneck.

[0004] Preliminary research has been conducted on CSI acquisition for ultra-large-scale HRIS systems. The widely adopted strategy is to replace some RIS units with active units with signal processing and reflection capabilities. In TDD systems, HRIS estimates the separation channels between UE and BS respectively. However, this method requires RIS to have strong signal processing capabilities, which will increase the hardware cost in XLHRIS systems. Other research results propose a two-stage cascade channel estimation scheme. HRIS first receives the pilot signal from the user to estimate the UE-RIS uplink channel, and then reflects the signal to the BS. The base station completes the RIS-BS channel estimation, thereby avoiding RHIS directly estimating the high-dimensional RIS-BS channel. However, due to the low signal processing capability of RIS and the increasing number of units, CSI acquisition still requires a large overhead and cannot meet the low computational complexity and low time overhead requirements of actual systems.

[0005] In summary, how to obtain time-varying cascaded CSI of time division duplex (TDD) ultra-large-scale HRIS with high availability with less computational complexity and time overhead has become a difficult problem to be solved in the sixth generation mobile communication. Summary of the invention

[0006] The technical problem to be solved by the present invention is to provide a cascade channel estimation method based on time correlation for XLHRIS system, utilize the characteristics of reconfigurable XLHRIS unit to realize the estimation of cascade channel of TDD ultra-large-scale HRIS system with lower computational complexity, and utilize the time correlation of time-varying channel to realize the rapid reconstruction of cascade channel in high-mobility scenario, while ensuring the accuracy of reconstructed channel.

[0007] The present invention adopts the following technical solutions to solve the above technical problems:

[0008] A cascade channel estimation method based on time correlation for an XLHRIS system comprises the following steps:

[0009] Step 1, at the initial moment of the channel estimation phase, each user equipment sends two uplink orthogonal pilot sequences to the XLHRIS system, and the XLHRIS system estimates the XLHRIS side angle parameter of the UE-XLHIRS channel according to the first uplink orthogonal pilot sequence received; the position of the active unit of the XLHRIS system is readjusted using the estimated XLHRIS side angle parameter, and the XLHRIS side distance parameter is estimated according to the second uplink orthogonal pilot sequence received;

[0010] Step 2: The base station sends two downlink pilot signals to the XLHRIS system, and the XLHRIS system estimates the XLHRIS side angle parameter and distance parameter of the XLHRIS-BS channel using the same method as step 1;

[0011] Step 3: Each user equipment resends an uplink orthogonal pilot sequence to the XLHRIS system. The XLHRIS system reflects the sequence signal to the base station and designs a reconfigurable phase for each XLHRIS unit to maximize the base station received signal power. The base station uses the received multi-user signals to jointly estimate the BS side angle using a joint compressed sensing algorithm.

[0012] The base station reconstructs the cascade channel between the user and the base station by using the estimated multi-user multi-path spatial parameters, including: UE-XLHIRS channel side angle parameter and distance parameter, XLHRIS-BS channel XLHRIS side angle parameter and distance parameter and BS side angle;

[0013] Step 4: In the subsequent channel estimation phase, the user equipment sends an uplink orthogonal pilot sequence. The XLHIRS system extrapolates the UE-XLHIRS channel angle parameters and distance parameters at the current moment based on the UE-XLHIRS channel angle parameters and distance parameters estimated at the previous moment, and uses time correlation to quickly reconstruct the cascade channel at the current moment.

[0014] Compared with the prior art, the present invention adopts the above technical solution and has the following technical effects:

[0015] 1. The present invention utilizes the reconfigurable characteristics of XLHRIS. After estimating the angle information, it adjusts the optimal active unit position and estimates the distance parameters. By decoupling the channel parameters based on the array structure, the computational complexity of CSI estimation is effectively reduced, thus solving the problem of high computational complexity of CSI estimation in ultra-large-scale HRIS.

[0016] 2. After XLHRIS estimates the XLHRIS side spatial parameters of the UE-RIS channel and the RIS-BS channel respectively, the present invention designs the XLHRIS unit phase shift using the detected parameter information, enhances the BS received signal power, and ensures that the BS estimation path matches the XLHRIS estimation path sequence. The three-stage estimation strategy decouples the cascade channel at the parameter level, ensures the low computational complexity of high-dimensional cascade channel estimation, and greatly improves the low overhead characteristics of channel reconstruction.

[0017] 3. After estimating the CSI of the cascaded channel at the initial moment, the present invention utilizes the time correlation between time-varying channels at subsequent moments to detect the user's current mobile position with a low-dimensional dictionary, and determines the common path through the detected scatterers to quickly reconstruct the cascaded channel, thereby ensuring the low time overhead characteristic of time-varying cascaded channel reconstruction in the TDD ultra-large-scale HRIS system, and greatly improving the feasibility of channel reconstruction in high-speed mobile scenarios. BRIEF DESCRIPTION OF THE DRAWINGS

[0018] Figure 1It is a flow chart of a cascade channel estimation method based on time correlation for an XLHRIS system of the present invention;

[0019] Figure 2 It is a diagram of the reconfigurable XLHRIS architecture;

[0020] Figure 3 It is a schematic diagram of the time correlation between UE-RIS channels at adjacent moments in a high-speed mobile scenario. DETAILED DESCRIPTION

[0021] The embodiments of the present invention are described in detail below, and examples of the embodiments are shown in the accompanying drawings. The embodiments described below with reference to the accompanying drawings are exemplary and are only used to explain the present invention, and cannot be interpreted as limiting the present invention.

[0022] The present invention proposes a cascade channel estimation method based on time correlation for the XLHRIS system. Based on the channel reciprocity of the TDD system, the cascade channel is parameter decoupled. After estimating the XLHRIS side parameters by using the reconfigurable characteristics, the XLHRIS designs a phase-enhanced BS receiving power, so that the BS accurately detects the BS side spatial parameters and reconstructs the cascade channel. At a subsequent moment, the XLHRIS uses the time correlation between time-varying channels based on the channel parameters estimated at the previous moment, and accurately extrapolates the channel parameters at the current moment through low computational complexity to reconstruct the downlink channel. Specifically, the following steps are included:

[0023] (1) The user equipment sends two uplink orthogonal pilot sequences. XLHRIS estimates the angle parameter of the XLHRIS side of the UE-XLHIRS channel using the first received orthogonal pilot sequence, adjusts the position of the active unit, and estimates the distance parameter of the XLHRIS side using the second received orthogonal pilot sequence.

[0024] (2) The base station sends two downlink pilot signals. XLHRIS estimates the angle parameter of the XLHRIS-BS channel on the XLHRIS side using the first downlink pilot signal received, adjusts the active unit position, and estimates the distance parameter on the HRIS side using the second downlink pilot signal received.

[0025] (3) XLHRIS designs a phase-enhanced BS receiving power based on the estimated XLHRIS side channel parameters. The UE sends an uplink pilot signal, and the BS estimates the BS side channel parameters and reconstructs the uplink cascade channel.

[0026] (4) At the subsequent time, the UE sends an uplink pilot signal, and XLHRIS uses time correlation to quickly reconstruct the time-varying cascade channel at the current time based on the channel parameters estimated at the previous time;

[0027] The base station can estimate the cascade channels between multiple user equipment and the base station; the cascade channels corresponding to each user equipment have multiple propagation paths; the forms of rapidly reconstructing the time-varying channels using time correlation include but are not limited to: a) establishing a low-dimensional sub-dictionary using the user movement trend to detect the direct-view path parameters; b) re-detecting the multiple scatterer information estimated in steps (1), (2), and (3) to determine whether the scattering path still exists; c) detecting the newly appeared path information based on the orthogonal pilot sequence received from the user.

[0028] In the TDD ultra-large-scale HRIS-assisted system, the number of XLHRIS antennas is N, which is usually in the order of 10. 3 , 10 4 , where the number of active units is N s , N s <<N, the number of BS antennas is M, the order of magnitude is usually 10 1 , 10 2 , the user equipment uses a single antenna configuration. To detect and transmit data, the base station needs to obtain real-time CSI and reconstruct the cascade channel H UB This example will be H UB Reconstruction, such as Figure 1 As shown, the following steps are included:

[0029] Step 1: In the initial channel estimation phase, each user equipment sends two uplink orthogonal pilot sequences, and the XLHRIS is set to active mode, and its active unit can receive and process signals. Figure 2 As shown, the signal model received by XLHRIS at this time is:

[0030]

[0031] in, is the uplink pilot signal received by XLHRIS, is the uplink channel between the user equipment and the base station, Y is XLHR S N s The position index of the active unit on the entire array, P is the transmission power of the user equipment, For noise, the uplink channel has the following expression:

[0032]

[0033] Among them, L UR,k is the number of propagation paths of the kth UE-XLHRIS channel, g UR,k,l1 is the gain of the l1th path in the kth user channel, w(·) is the XLHRIS unit array response, is the direction angle of the l1th path in the kth user channel, r UR,k,l1is the distance of the l1th path in the kth user channel.

[0034] At this time, the active units are located densely, and the corresponding channel can be simplified to a plane wave model that is only related to the angle. The base station uses the first received orthogonal pilot sequence and a compressed sensing algorithm to calculate the received signal Y. UR After processing and calculation, we get The propagation path Group azimuth parameter estimates, each group of parameter estimates includes For ultra-large-scale arrays, their channels exhibit non-negligible near-field characteristics, so it is also necessary to estimate the distance and near-field gain.

[0035] The XLHRIS system uses the estimated azimuth parameters to reselect the active unit position. The XLHRIS array is divided into several sub-arrays, and an active unit position is selected in each sub-array. Multiple sub-arrays use compressed sensing algorithms to jointly estimate distance and near-field gain. The active unit selection principle is to minimize the lower bound of the energy maximum path distance estimation error (statistical Cramer-Rao lower bound CRLB). The active unit position selected in the nth sub-array It can be expressed as:

[0036]

[0037] in, Indicates the number of units in each sub-array, w n,m (·) is the mth element of the nth subarray unit array response, n=1,…,N s ,m=1,…,N sub , r s =(s / N sub )d R Represents the sth sampling point of the distance parameter, s=1,…,N sub , each set of parameter estimates includes

[0038] Step 2: The single antenna at the base station center sends two downlink pilot signals. XLHRIS is in active mode. At this time, the signal model received by XLHRIS is:

[0039]

[0040] Among them, L RB is the number of propagation paths of the XLHRIS-BS channel, is the gain of the l2th path, is the direction angle of the l2th path, is the distance of the l2th path.

[0041] XLHRIS uses the method used in step 1 to estimate the XLHRIS side angle, distance and gain of the XLHRIS-BS channel. In the TDD system, the estimated downlink parameters can be directly applied to the uplink channel, and each set of estimated parameters includes Indicates the number of XLHRIS-BS channel estimation paths.

[0042] Step 3: The user equipment resends the uplink orthogonal pilot sequence, and the XLHRIS is set to passive mode to reflect the signal to the BS. Each unit is attached with a reconfigurable phase to maximize the BS received signal power and ensure that the BS estimated path sequence is consistent with the XLHRIS estimated path sequence in step 2. The XLHRIS phase is designed to be Ω = Ω RB Ω UR , where Ω UR Indicates beamforming for the maximum eigenvector of the UE-XLHRIS multi-user channel, Ω RB Indicates weighted beamforming for XLHRIS-BS channel multipath.

[0043] Ω RB Can be designed as:

[0044]

[0045] After receiving the multi-user signal, the BS performs orthogonal decomposition. At this time, the signal model received by the BS can be expressed as:

[0046]

[0047] Where a(·) is the base station antenna array vector, is the BS side angle of the l2th path of the XLHRIS-BS channel, l2=1,...,L RB .

[0048] The BS uses the received multi-user signals to jointly estimate the BS side angle using a joint compressed sensing algorithm. Multiple users share the same XLHRIS-BS channel and have the same receiving angle. The multi-dimensional signals provided by multiple users are used to reduce the pilot overhead required for CSI estimation. Each set of estimated parameters includes

[0049]

[0050] Among them, Y r represents the multi-user signal received at the BS side, Γ is the DFT sampling dictionary of the angle parameter at the BS side,

[0051] The base station reconstructs the cascade channel between the user and the base station using the estimated multi-user multi-path spatial parameters, including the number, distance, gain and XLHRIS side angle of the UE-XLHRIS channel path, the number, distance, gain, XLHRIS side angle and BS side angle of the XLHRIS-BS channel path:

[0052]

[0053] in, It is a multi-user channel between user equipment and XLHRIS.

[0054] Step 4: In the subsequent channel estimation phase, the user sends an uplink orthogonal pilot signal, such as Figure 3 As shown in the figure, HRIS estimates the UE-RIS channel parameter information at the previous moment (the tth moment) to establish a low-dimensional sub-dictionary to extrapolate the user's mobile position at the current moment (the t+1th moment), and quickly detects the public path information and the newly appeared path information. Due to the slowly changing movement characteristics of users and scatterers, the relationship between the channel parameters at adjacent moments can be expressed as:

[0055]

[0056] in, is the change of the channel parameters at adjacent moments. Based on the channel parameter estimation at the previous moment, XLHRIS uses a low-dimensional sampling dictionary to quickly extrapolate the channel parameters at the current moment, which can be expressed as:

[0057]

[0058] in, are the azimuth, elevation and distance of the kth user to the lth path estimated in the XLHRIS channel at time t+1, ψ represents the low-dimensional sampling dictionary near the channel parameter estimate at the previous moment, y UR,k,t+1 It means that at the t+1th time, XLHRIS receives the pilot signal from the kth user;

[0059] Based on the extrapolated angle and distance parameters, XLHRIS recalculates the path gain at the current moment using the least squares method, thereby quickly reconstructing the time-varying UE-XLRIS channel at the current moment and updating the cascade channel.

[0060] Based on the same inventive concept, an embodiment of the present application provides a computer device, including a memory, a processor, and a computer program stored in the memory and executable on the processor. When the processor executes the computer program, the steps of the aforementioned time-correlation-based cascade channel estimation method for the XLHRIS system are implemented.

[0061] Based on the same inventive concept, an embodiment of the present application provides a computer-readable storage medium, which stores a computer program. When the computer program is executed by a processor, the steps of the aforementioned time-correlation-based cascade channel estimation method for the XLHRIS system are implemented.

[0062] Those skilled in the art will appreciate that embodiments of the present invention may be provided as methods, systems, or computer program products. Therefore, the present invention may take the form of a complete hardware embodiment, a complete software embodiment, or an embodiment combining software and hardware. Moreover, the present invention may take the form of a computer program product implemented on one or more computer-usable storage media (including but not limited to disk storage, CD-ROM, optical storage, etc.) containing computer-usable program code.

[0063] The present invention is described with reference to flowcharts and / or block diagrams of methods, devices (systems), and computer program products according to embodiments of the present invention. It should be understood that each process and / or block in the flowchart and / or block diagram, as well as the combination of processes and / or blocks in the flowchart and / or block diagram, can be implemented by computer program instructions. These computer program instructions can be provided to a processor of a general-purpose computer, a special-purpose computer, an embedded processor, or other programmable data processing device to produce a machine, so that the instructions executed by the processor of the computer or other programmable data processing device generate instructions for implementing the processes in the flowchart and / or block diagram. Figure 1 A process or multiple processes and / or boxes Figure 1 A device that provides the functions specified in a block or multiple blocks.

[0064] These computer program instructions may also be stored in a computer-readable memory capable of directing a computer or other programmable data processing device to operate in a specific manner, so that the instructions stored in the computer-readable memory produce an article of manufacture comprising an instruction device, which implements the process Figure 1 A process or multiple processes and / or boxes Figure 1 A function specified in one or more boxes.

[0065] These computer program instructions can also be loaded onto a computer or other programmable data processing device so that a series of operating steps are executed on the computer or other programmable device to produce a computer-implemented process, thereby providing instructions for implementing the process. Figure 1 A process or multiple processes and / or boxes Figure 1 The steps for the functions specified in one or more boxes.

[0066] The above embodiments are only for illustrating the technical idea of ​​the present invention, and cannot be used to limit the protection scope of the present invention. Any changes made on the basis of the technical solution in accordance with the technical idea proposed by the present invention shall fall within the protection scope of the present invention.

Claims

1. A cascade channel estimation method based on time correlation for XLHRIS system, characterized in that: The steps include: Step 1, at the initial moment of the channel estimation phase, each user equipment sends two uplink orthogonal pilot sequences to the XLHRIS system, and the XLHRIS system estimates the XLHRIS side angle parameter of the UE-XLHIRS channel according to the first uplink orthogonal pilot sequence received; the position of the active unit of the XLHRIS system is readjusted using the estimated XLHRIS side angle parameter, and the XLHRIS side distance parameter is estimated according to the second uplink orthogonal pilot sequence received; Step 2: The base station sends two downlink pilot signals to the XLHRIS system, and the XLHRIS system estimates the XLHRIS side angle parameter and distance parameter of the XLHRIS-BS channel using the same method as step 1; Step 3: Each user equipment resends an uplink orthogonal pilot sequence to the XLHRIS system. The XLHRIS system reflects the sequence signal to the base station and designs a reconfigurable phase for each XLHRIS unit to maximize the base station received signal power. The base station uses the received multi-user signals to jointly estimate the BS side angle using a joint compressed sensing algorithm. The base station reconstructs the cascade channel between the user and the base station by using the estimated multi-user multi-path spatial parameters, including: UE-XLHIRS channel side angle parameter and distance parameter, XLHRIS-BS channel XLHRIS side angle parameter and distance parameter and BS side angle; Step 4: In the subsequent channel estimation phase, the user equipment sends an uplink orthogonal pilot sequence. The XLHIRS system extrapolates the UE-XLHIRS channel angle parameters and distance parameters at the current moment based on the UE-XLHIRS channel angle parameters and distance parameters estimated at the previous moment, and uses time correlation to quickly reconstruct the cascade channel at the current moment.

2. The cascade channel estimation method based on time correlation for the XLHRIS system according to claim 1, characterized in that: The specific process of step 1 is as follows: At the initial moment of the channel estimation phase, each user equipment sends two uplink orthogonal pilot sequences to the XLHRIS system. The length of the orthogonal pilot sequence is equal to the number of user equipment. XLHRIS is set to active mode. The first uplink orthogonal pilot sequence model received by XLHRIS is: Among them, Y UR is the first uplink orthogonal pilot sequence received by XLHRIS, P is the transmit power of the user equipment, H UR is the uplink channel between the user equipment and the base station, Y is the position index of the XLHRIS active unit on the entire array, (H UR ) Υ,: is the channel between the XLHRIS active unit included in Y and all users, N is the noise; the uplink channel H between the kth user equipment and the base station UR,k It is expressed as: Among them, L UR,k is the number of propagation paths of the kth UE-XLHIRS channel, is the gain of the l1th path in the kth UE-XLHIRS channel, w(·) is the XLHRIS unit array response, is the direction angle of the l1th path in the kth UE-XLHIRS channel, is the distance of the l1th path in the kth UE-XLHIRS channel; The XLHRIS system uses the first received uplink pilot signal and adopts the compressed sensing algorithm to detect the received signal Y UR After processing and calculation, we get The propagation path Group azimuth parameter estimates, each group of parameter estimates includes is the estimated kth user channel The direction angle of the path; The XLHRIS system uses the estimated XLHRIS side angle parameters to readjust the position of the XLHRIS system active unit and evenly divide the XLHRIS array into multiple sub-arrays, where the number of sub-arrays is equal to the number of XLHRIS active units N. s , an active unit is selected in each subarray. The principle of selecting the active unit is to minimize the statistical Cramer-Rao lower bound of the maximum energy path distance. The position of the active unit selected in the nth subarray is It is expressed as: in, The active antenna unit position index selected for the nth subarray, is the number of cells in each sub-array, w n,m (·) is the mth element of the nth subarray unit array response, n=1,…,Ns, m=1,…,N sub , N s is the number of XLHRIS active units, r s Represents the sth sampling point of the distance parameter, r s =(s / N sub )d R , d R is the Rayleigh distance; Multiple subarrays use the compressed sensing algorithm to estimate the XLHRIS side distance parameters based on the received second uplink pilot signal. The parameter estimation includes are the estimated kth UE-XLHIRS channel The distance and gain of each path, 3. The cascade channel estimation method based on time correlation for XLHRIS system according to claim 1, characterized in that: The specific process of step 2 is as follows: The base station sends two downlink pilot signals to the XLHRIS system. The XLHRIS is set to active mode. The first uplink pilot signal model received by the XLHRIS is: Among them, L RB is the number of propagation paths of the XLHRIS-BS channel, is the gain of the l2th path, is the direction angle of the l2th path, is the distance of the l2th path, w(·) is the near-field channel steering vector; The XLHRIS system estimates the XLHRIS side angle parameter of the XLHRIS-BS channel based on the first received downlink pilot signal, namely is the first estimated value on the XLRIS side in the XLRIS-BS channel The receiving azimuth and elevation angle of each path; the position of the active unit of the XLHRIS system is readjusted using the estimated XLHRIS side angle parameter, and the XLHRIS side distance parameter is estimated according to the received second downlink pilot signal, that is, are the first estimated values ​​on the XLRIS side in the XLRIS-BS channel. The distance and gain of each path, Indicates the number of XLHRIS-BS channel estimation paths.

4. The XLHRIS system-oriented cascade channel estimation method based on time correlation according to claim 3, characterized in that: The specific process of step 3 is as follows: Each user equipment resends an uplink orthogonal pilot sequence to the XLHRIS system. The XLHRIS is set to passive mode. The XLHRIS system reflects the sequence signal to the base station. According to the UE-XLHIRS channel side angle parameter and distance parameter estimated in step 1 and the XLHRIS-BS channel XLHRIS side angle parameter and distance parameter estimated in step 2, a reconfigurable phase is designed for each XLHRIS unit to maximize the base station received signal power and ensure that the base station estimated path sequence is consistent with the XLHRIS estimated path sequence in step 2. The reconfigurable phase Ω is designed as: Oh=Oh RB Oh UR Among them, Ω UR Indicates beamforming for the maximum eigenvector of the UE-XLHRIS multi-user channel, Ω RB Indicates weighted beamforming for XLHRIS-BS channel multipath, Ω RB The design is as follows: Where n = 1, ..., N, N is the number of XLHRIS units, w n is the nth element of the near-field steering vector w, (·) H represents conjugate transpose; After receiving the multi-user signal, the base station performs orthogonal decomposition. The signal model received by the base station is expressed as: Where a(·) is the base station antenna array vector, is the BS side angle of the l2th path of the XLHRIS-BS channel, l2=1,...,L RB ; The base station uses the received multi-user signals to jointly estimate the BS side angle using a joint compressed sensing algorithm. Each set of estimated parameters includes Among them The estimated value of the BS side angle parameter of each path is: Among them, Y r represents the multi-user signal received at the BS side, Γ is the DFT sampling dictionary of the angle parameter at the BS side, The XLHRIS-BS channel is the BS side Path azimuth; The base station reconstructs the cascade channel between the user and the base station using the estimated multi-user multipath spatial parameters, including: UE-XLHIRS channel side angle parameter and distance parameter, XLHRIS-BS channel XLHRIS side angle parameter and distance parameter, and BS side angle: in, It is a multi-user cascade channel between user equipment and base station. It is a multi-user channel between user equipment and XLHRIS.

5. The cascade channel estimation method based on time correlation for XLHRIS system according to claim 1, characterized in that: In step 4, In the subsequent channel estimation phase, the user equipment sends an uplink orthogonal pilot sequence. The XLHRIS system establishes a low-dimensional sub-dictionary based on the UE-XLHRIS channel parameter information estimated at the previous moment to extrapolate the current user equipment mobile position, and detects the common path information and the newly appeared path information. Due to the slowly changing movement characteristics of the user and the scatterer, the relationship between the channel parameters at adjacent moments is expressed as: in, is the change of channel parameters at adjacent moments, θ UR,k,l,t+1 ,r UR,k,l,t+1 are the azimuth, elevation and distance from the kth user to the lth path in the XLHRIS channel at time t+1, θ UR,k,l,t ,r UR,k,l,t are the azimuth, elevation and distance from the kth user to the lth path in the XLHRIS channel at the tth time; Based on the channel parameter estimation at the previous moment, XLHRIS uses a low-dimensional sampling dictionary to quickly extrapolate the channel parameters at the current moment, which can be expressed as: in, are the azimuth, elevation and distance of the kth user to the lth path estimated in the XLHRIS channel at time t+1, ψ represents the low-dimensional sampling dictionary near the channel parameter estimate at the previous moment, y UR,k,t+1 It means that at the t+1th time, XLHRIS receives the pilot signal from the kth user; Based on the extrapolated angle and distance parameters, XLHRIS recalculates the path gain at the current moment using the least squares method, thereby quickly reconstructing the time-varying UE-XLHRIS channel at the current moment and updating the cascade channel.

6. A computer device comprising a memory, a processor, and a computer program stored in the memory and capable of running on the processor, characterized in that: When the processor executes the computer program, the steps of the XLHRIS system-oriented cascade channel estimation method based on time correlation are implemented as described in any one of claims 1 to 5.

7. A computer-readable storage medium storing a computer program, characterized in that: When the computer program is executed by a processor, the steps of the time-correlation-based cascade channel estimation method for the XLHRIS system as claimed in any one of claims 1 to 5 are implemented.

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