Channel estimation method, data transmission method, device, system and medium

Abstract

The present disclosure provides a channel estimation method, a data transmission method, a device, a system and a medium, relating to the technical field of communication, which is used to solve the problem of how to effectively perform channel estimation of an IRS wireless communication system under relatively low pilot signal overhead. The method comprises: obtaining configuration parameters of pilot signals transmitted by a BS-UE channel and a BS-IRS-UE channel in a wireless communication system; establishing a double-channel input-output model of the pilot signals transmitted in the wireless communication system according to the configuration parameters, wherein the double-channel input-output model includes a BS-UE channel component and a BS-IRS-UE channel component; and solving the double-channel input-output model to obtain a BS-UE channel component estimation result and a BS-IRS-UE channel component estimation result. By solving the BS-UE channel component and the BS-IRS-UE channel component, the present disclosure reduces the pilot overhead and provides an effective channel estimation method for an IRS wireless communication system.

Description

TECHNICAL FIELD

[0001] The present disclosure relates to the technical field of communication, in particular to a channel estimation method, a data transmission method, a channel estimation device, a data transmission device, a wireless communication system and a computer readable storage medium. BACKGROUND

[0002] Intelligent reflecting surface (IRS) as a technology to enhance communication in wireless communication system has significant advantages in expanding wireless communication coverage, improving data transmission rate and improving system energy efficiency. In order to enable IRS to achieve high beamforming gain, complete channel state information needs to be obtained, so channel estimation is an important problem to be solved in IRS wireless communication system.

[0003] The size of the complex channel of the IRS wireless communication system increases linearly with the number of reflecting units. The actual IRS usually configures a large number of reflecting units, and the increase in the number of channels increases the complexity of channel estimation. The channel estimation method applied to the wireless communication system without IRS usually estimates the entire channel by using the signal of the receiving end, and estimating the entire channel in the IRS wireless communication system will produce a very large pilot signal overhead.

[0004] DISCLOSURE

[0005] The technical problem to be solved by the present disclosure is to provide a channel estimation method, a data transmission method, a channel estimation device, a data transmission device, a wireless communication system and a computer readable storage medium to solve the problem of how to effectively perform channel estimation of IRS wireless communication system under relatively low pilot signal overhead.

[0006] In a first aspect, the present disclosure provides a channel estimation method, the method comprising:

[0007] obtaining configuration parameters of a pilot signal transmitted through a BS-UE channel and a BS-IRS-UE channel in a wireless communication system;

[0008] establishing a double-channel input-output model of the pilot signal transmitted in the wireless communication system according to the configuration parameters, wherein the double-channel input-output model includes a BS-UE channel component and a BS-IRS-UE channel component;

[0009] solving the double-channel input-output model to obtain a BS-UE channel component estimation result and a BS-IRS-UE channel component estimation result;

[0010] Wherein, IRS is an intelligent reflecting surface, BS is a base station, and UE is a user equipment.

[0011] In a second aspect, the disclosure provides a data transmission method, which transmits data through a data transmission protocol, and the data transmission protocol is used for:

[0012] The coherence time of the wireless communication system is divided into three stages;

[0013] In the first stage, the pilot signal is transmitted through the BS-UE channel and the BS-IRS-UE channel in the wireless communication system, and the channel estimation method described above is used to obtain the BS-UE channel component estimation result and the BS-IRS-UE channel component estimation result;

[0014] In the second stage, the reflection coefficient is optimized based on the BS-IRS-UE channel component estimation result;

[0015] In the third stage, the data is transmitted based on the optimized reflection coefficient, the BS-UE channel component estimation result and the BS-IRS-UE channel component estimation result.

[0016] In a third aspect, the disclosure provides a channel estimation device, comprising:

[0017] The acquisition configuration module is configured to acquire configuration parameters of the pilot signal transmitted through the BS-UE channel and the BS-IRS-UE channel in the wireless communication system;

[0018] The model establishment module is connected with the acquisition configuration module, and is configured to establish a double-channel input-output model of the pilot signal transmitted in the wireless communication system according to the configuration parameters, wherein the double-channel input-output model includes the BS-UE channel component and the BS-IRS-UE channel component;

[0019] The solution result module is connected with the model establishment module, and is configured to solve the double-channel input-output model to obtain the BS-UE channel component estimation result and the BS-IRS-UE channel component estimation result;

[0020] Wherein, IRS is an intelligent reflecting surface, BS is a base station, and UE is a user equipment.

[0021] In a fourth aspect, the disclosure provides a data transmission device, which sets a data transmission protocol, and the data transmission protocol is used for:

[0022] The coherence time of the wireless communication system is divided into three stages;

[0023] In the first stage, the pilot signal is transmitted through the BS-UE channel and the BS-IRS-UE channel in the wireless communication system, and the channel estimation method described above is used to obtain the BS-UE channel component estimation result and the BS-IRS-UE channel component estimation result;

[0024] In the second stage, the reflection coefficients are optimized based on the BS-IRS-UE channel component estimation results;

[0025] In the third stage, data is transmitted based on the optimized reflection coefficients, the BS-UE channel component estimation results and the BS-IRS-UE channel component estimation results.

[0026] In the fifth aspect, the present disclosure provides a wireless communication system, comprising:

[0027] The BS is configured to receive the pilot signal transmitted by the UE, obtain the BS-UE channel component estimation results and the BS-IRS-UE channel component estimation results by performing the channel estimation method as described above based on the pilot signal, optimize the reflection coefficients based on the BS-IRS-UE channel component estimation results, and transmit the optimized reflection coefficients to the IRS controller.

[0028] The IRS controller is connected with the BS, configured to receive the optimized reflection coefficients transmitted by the BS, and control the IRS according to the optimized reflection coefficients.

[0029] The IRS is connected with the IRS controller, configured to adjust the reflection coefficients of each reflection unit of the IRS according to the control of the IRS controller.

[0030] The BS and the IRS transmit data through the BS-IRS-UE channel based on the BS-IRS-UE channel component estimation results and the optimized reflection coefficients, and the BS transmits data through the BS-UE channel based on the BS-UE channel component estimation results.

[0031] In the sixth aspect, the present disclosure provides a computer readable storage medium, wherein a computer program is stored in the computer readable storage medium, and when the computer program is run by a processor, the channel estimation method as described in the first aspect or the data transmission method as described in the second aspect is realized.

[0032] The present disclosure provides a channel estimation method, a data transmission method, a channel estimation device, a data transmission device, a wireless communication system and a computer readable storage medium, by establishing an input-output model of the pilot signal with respect to the BS-UE channel and the BS-IRS-UE channel, converting the estimation object into two components of the BS-UE channel and the BS-IRS-UE channel, solving the model to obtain the estimation results of the BS-UE channel and the BS-IRS-UE channel respectively, and reducing the pilot overhead, an effective channel estimation method for the IRS wireless communication system is proposed. BRIEF DESCRIPTION OF DRAWINGS

[0033] Figure 1 is a scene diagram of an IRS wireless communication system according to an embodiment of the present disclosure;

[0034] Figure 2is a schematic diagram of a channel transmission protocol according to an embodiment of the present disclosure;

[0035] Figure 3 is a flow chart of a channel estimation method according to an embodiment of the present disclosure;

[0036] Figure 4 is a flow chart of another channel estimation method according to an embodiment of the present disclosure;

[0037] Figure 5 is a schematic diagram of grouping of reflecting units of an IRS according to an embodiment of the present disclosure;

[0038] Figure 6 is a structural schematic diagram of a channel estimation device according to an embodiment of the present disclosure. DETAILED DESCRIPTION

[0039] In order for those skilled in the art to better understand the technical solutions of the present disclosure, the embodiments of the present disclosure will be further described in detail below with reference to the accompanying drawings.

[0040] It can be understood that the specific embodiments and the accompanying drawings described herein are only used to explain the present disclosure, but not to limit the present disclosure.

[0041] It can be understood that the embodiments in the present disclosure and the features in the embodiments can be combined with each other without conflict.

[0042] It can be understood that, for the convenience of description, only parts related to the present disclosure are shown in the drawings of the present disclosure, and parts unrelated to the present disclosure are not shown in the drawings.

[0043] It can be understood that each unit and module involved in the embodiments of the present disclosure can only correspond to one entity structure, or can be composed of multiple entity structures, or multiple units and modules can be integrated into one entity structure.

[0044] It can be understood that, without conflict, the functions and steps marked in the flowcharts and block diagrams of the present disclosure can occur in an order different from that marked in the drawings.

[0045] It can be understood that, in the flowcharts and block diagrams of the present disclosure, the architecture, functions and operations of possible implementations of the systems, devices, apparatuses and methods according to the embodiments of the present disclosure are shown. Each block in the flowchart or block diagram can represent a unit, module, program segment, code, which contains executable instructions for implementing the specified functions. Moreover, each block or combination of blocks in the block diagram and flowchart can be implemented by a hardware-based system for implementing the specified functions, or by a combination of hardware and computer instructions.

[0046] It can be understood that the units and modules involved in the embodiments of the present disclosure can be implemented in software or hardware, for example, the units and modules can be located in a processor.

[0047] In order to facilitate understanding of the present disclosure, first introduce the main inventive idea of the present disclosure.

[0048] As shown in Figure 1 , the IRS wireless communication system includes a base station (Base Station, BS), an IRS, and user equipment (User Equipments, UEs), the IRS includes a plurality of reflection units and an IRS controller, the IRS reflects signals with adjustable coefficients (amplitude ω and phase θ) using a large number of reflection elements, thereby effectively improving the propagation environment, the IRS controller can control the reflection coefficient of each reflection unit, the channel of the IRS wireless communication system includes BS-UE link (also called direct link) and BS-IRS-UE link (also called cascaded link), the link is also the channel.

[0049] In the IRS wireless communication system based on orthogonal frequency division multiplexing (Orthogonal Frequency Division Multiplexing, OFDM), due to the existence of multipath delay diffusion, the number of channel coefficients will increase, which makes the channel estimation problem more challenging. Unlike traditional OFDM communication systems, the IRS wireless communication system based on OFDM needs to perform channel estimation on the IRS cascaded link at the same time, and the number of IRS cascaded channel coefficients increases linearly with the number of reflection elements, and actual IRS involves thousands of reflection elements.

[0050] The coherence time is the maximum time difference range in which the channel of the wireless communication system remains constant, the same signal at the transmitting end reaches the receiving end within the coherence time, and the fading characteristics of the signal are completely similar, and the receiving end considers it as one signal, as Figure 2 shown, the process of transmitting a signal based on the OFDM IRS wireless communication system channel, each coherence time includes three stages, wherein the coherence time is normalized to the OFDM symbol duration, the first stage is pilot transmission and channel estimation, the second stage is feedback delay, and the third stage is data transmission. The traditional channel estimation method will require a large amount of pilot signal transmission and feedback delay, thereby compressing the data transmission.

[0051] Due to the above problems, some channel estimation methods for narrowband communication systems are difficult to apply in wideband OFDM systems due to the large computational complexity. Some other methods proposed for wideband OFDM systems include IRS semi-passive to assist channel estimation, an algorithm to compensate for less pilot signal overhead through iteration, and a deep learning algorithm, or the need to install receiving RF chains or sensors on the IRS, which has high implementation cost and energy consumption, or requires a large amount of training data set and validation data set, while the IRS communication system can be flexibly applied to various scenarios, and it is currently difficult to provide data sets required by complex scenarios.

[0052] Since the IRS is a passive device and does not need to install any receiving RF chain or sensor, the present disclosure is based on the OFDM input-output model, converts the estimation object from the entire channel to the BS-UE channel and the BS-IRS-UE channel component, obtains the values of the BS-UE channel and the BS-IRS-UE channel coefficients by the least square estimation method, reduces the number of pilot transmission and feedback delay, and has low implementation cost and energy consumption, without the need for a large amount of training data set and validation data set.

[0053] In addition, for some scenarios with high delay requirements, there is a problem that the number of pilots cannot meet the unique solution of least square estimation, and the present disclosure utilizes the distribution characteristics of the IRS cascade channel coefficient matrix array vector, and proposes a method of reducing the dimension of the channel coefficient matrix to estimate the channel for the problem that the number of pilots cannot meet the unique solution of least square estimation.

[0054] In general, the present disclosure proposes an effective channel estimation method for an OFDM-based IRS communication system, which can effectively reduce the pilot signal overhead and can be flexibly applied to scenarios with different signal delay requirements. For more detailed implementation, see the following embodiments.

[0055] Embodiment 1:

[0056] As shown in Figure 3 , the present disclosure provides a channel estimation method, which comprises:

[0057] S11, obtaining the configuration parameters of the pilot signal transmitted through the BS-UE channel and the BS-IRS-UE channel in the wireless communication system;

[0058] S12, establishing a double-channel input-output model of the pilot signal transmitted in the wireless communication system according to the configuration parameters, which includes the BS-UE channel component and the BS-IRS-UE channel component;

[0059] S13, solving the double-channel input-output model to obtain the BS-UE channel component estimation result and the BS-IRS-UE channel component estimation result;

[0060] Wherein, IRS is an intelligent reflecting surface, BS is a base station, and UE is a user equipment.

[0061] Specifically, in the embodiment, the IRS is used to enhance the communication between the BS and the UEs, signals (data) are transmitted through the BS-UE channel and the BS-IRS-UE channel, the channel estimation is performed by establishing the input-output model of the pilot signals with respect to the BS-UE channel and the BS-IRS-UE channel, the estimation object is converted into two components of the BS-UE channel and the BS-IRS-UE channel, and the estimation results of the BS-UE channel and the BS-IRS-UE channel are obtained by solving the model, thereby reducing the pilot overhead, providing an effective channel estimation method for the IRS wireless communication system, and the method is proposed for the passive intelligent reflecting surface system, has lower implementation cost and energy consumption, the model solving method has lower solving complexity, and does not require a large number of training data sets and validation data sets.

[0062] In an embodiment, the configuration parameters of the transmission of the pilot signals through the BS-UE channel and the BS-IRS-UE channel in the wireless communication system are obtained, and specifically include:

[0063] For the transmission of the C pilot signals through the BS-UE channel and the BS-IRS-UE channel in the wireless communication system, the reflection coefficients of the N IRS reflecting units of the wireless communication system to the C pilot signals are configured Wherein Ω represents a set of reflection coefficients of the N reflecting units to one signal, and the configuration parameters including Ω are obtained.

[0064] Wherein, Ω represents an NxC complex set, Ω represents an N complex set.

[0065] Specifically, in the embodiment, as shown in Figure 1 , the IRS has N passive reflecting units, which are arranged in a two-dimensional grid, and the number of rows and columns correspond to N row and N column , N=N row *N column , the IRS is connected with an IRS controller, the IRS controller can adjust the reflection coefficient of each reflecting unit, and the length (number) of the C control pilot signals can be controlled by inputting the C control pilot signals. Figure 4The step S101 is shown, according to C, N, the Ω is configured, and then step S102 is executed, the double channel input and output model of the pilot signal is established, the estimation object is converted from the whole channel to the BS-UE channel and BS-IRS-UE channel component by Ω, the channel can be estimated according to the different pilot signal quantity of system transmission, thereby reducing the pilot cost and the complexity of subsequent model solving.

[0066] In an embodiment, a double channel input and output model of a pilot signal transmitted in a wireless communication system is established according to configuration parameters, wherein the double channel input and output model includes a BS-UE channel component and a BS-IRS-UE channel component, and specifically includes:

[0067] For each signal transmitted in the wireless communication system, a single signal system input and output model is established based on OFDM, wherein the single signal system input and output model includes FIR related terms, and the FIR is composed of a BS-UE channel response and a BS-IRS-UE channel response.

[0068] According to the correlation between the BS-IRS-UE channel response and Ω, the single signal system input and output models corresponding to the C pilot signals are combined, and the BS-UE channel component, the BS-IRS-UE channel component and the Ω term are extracted, to obtain a double channel input and output model.

[0069] Wherein, OFDM is Orthogonal Frequency Division Multiplexing, and FIR is Finite Impulse Response.

[0070] Specifically, in the embodiment, considering a multi-user antenna system based on orthogonal frequency division multiplexing, a single signal system input and output model can be established similar to a conventional OFDM system, and then the FIR related terms in the single signal system input and output model are represented as a BS-UE channel component and a BS-IRS-UE channel component, thereby establishing a double channel input and output model.

[0071] In an embodiment, for each signal transmitted in the wireless communication system, a single signal system input and output model is established based on OFDM, wherein the single signal system input and output model includes FIR related terms, and the FIR is composed of a BS-UE channel response and a BS-IRS-UE channel response, and specifically includes:

[0072] The bandwidth served by the wireless communication system for each user is divided into K orthogonal subcarriers, the transmitted signal is represented as a discrete time signal {x[k], k = 1,..., K}, and the received signal is represented as:

[0073]

[0074] Wherein, {h θ [l]: l = 0,..., M-1} represents FIR coefficients describing a wideband channel in the time domain, M is the number of taps, the tap index l = {0, 1,..., M-1}, and {w[k]} is noise at the receiver.

[0075] Among them, represents the BS-UE channel response in the time domain, represents the BS-IRS-UE channel response in the time domain, represents the BS-IRS-UE channel component in the time domain;

[0076] By adding a cyclic prefix with length N cp to perform DFT on Equation (1), the channel transmission signal is converted into K parallel sub-channel transmission signals to obtain the input-output model of a single-signal system established based on OFDM:

[0077]

[0078] Abbreviate Equation (2) as

[0079]

[0080] where, N cp +1 < K, DFT is the discrete Fourier transform, represents the column vector composed of K received signals

[0081] signals, represents the column vector composed of K FIR coefficients, represents the column vector composed of K transmitted signals, represents the column vector composed of K noises.

[0082] Specifically, in this embodiment, the OFDM-IRS communication system has a bandwidth of B for each user service, which is divided into K orthogonal subcarriers and transmitted through a sinc (sine wave) filter. The set of signals (continuous-time signals) transmitted on the base station is represented as discrete-time signals {x[k], k = 1,..., K}. On most digital signal microprocessors, FIR calculations can be completed by looping a single instruction. Taking the sinc filter as the FIR filter, the filter coefficient sequence h θ [l], the input sample x[k], and the sequence are convolved to output the z[k] sequence. The signal of the UE receiver is where, {h θ [l]: l = 0,…, M - 1} represents the FIR describing the wideband channel in the time domain, the number of taps is M, and one tap is a coefficient / delay pair. In practical applications, the more taps, the better the filter implementation effect. The noise at the receiver is represented by {w[k]}, which is circularly symmetric complex Gaussian noise. The impulse response h θ [l] is composed of the BS-UE channel and the BS-IRS-UE channel response, which is represented as corresponding to tap index l = {0, 1, …, M-1}, h d [l] is a BS-UE channel coefficient, is a coefficient of a channel cascaded by each of N reflecting units (a BS-IRS-UE channel including an IRS), denotes a set of reflection coefficients of each reflecting unit of an IRS surface, denotes an N-dimensional complex set, and a length-N cp cyclic prefix (N cp +1<K) is added in front of a time-domain signal (a discrete-time signal), the channel is converted into K parallel sub-channel transmissions by a Discrete Fourier Transform (DFT), and an input-output model of a single-signal system established based on OFDM is obtained.

[0083] In an embodiment, according to FIR, the single-signal system input-output model corresponding to C pilot signals is combined and BS-UE channel components, BS-IRS-UE channel components, and Ω terms are extracted to obtain a double-channel input-output model, wherein the BS-IRS-UE channel response is related to Ω, and the FIR is composed of a BS-UE channel response and a BS-IRS-UE channel response, and the specific steps include:

[0084] According to formula (3), the single-signal system input-output model corresponding to the cth pilot signal is obtained:

[0085]

[0086] According to FIR, the FIR is composed of a BS-UE channel response and a BS-IRS-UE channel response, and:

[0087]

[0088] wherein F is a DFT matrix, K×M in size, indicating K-point DFT on the BS-UE channel response and the BS-IRS-UE channel response, the BS-UE channel component h d = [h d [0], …, h d [N cp ]] T , and the BS-IRS-UE channel component T represents the transpose of a matrix, denotes an N×M-dimensional complex set;

[0089] According to formula (4) and (5), the single-signal system input-output model corresponding to C pilot signals is combined and BS-UE channel components, BS-IRS-UE channel components, and Ω terms are extracted to obtain a double-channel input-output model:

[0090]

[0091] wherein, [1,…,1] represents h d without IRS reflection,

[0092] Specifically, in the present embodiment, during the pilot signal transmission process, for example, the transmission power P = 1 W, the bandwidth (symbol rate) B = 10 MHz, the provided parameters are determined by the communication system, for reference only, when the c-th pilot signal is transmitted, the IRS is configured as The power of a signal transmitted by one orthogonal subcarrier is to obtain formula (4); in order to estimate the channel components BS-UE channel (h d = [h d [0],…,h d [N cp ]] T ) and BS-IRS-UE channel, to obtain formula (5); when the length of the pilot signal is C, the system transmits C pilot signals, and the IRS is configured as The received pilot transmission signal is represented by formula (6) using the channel components BS-UE channel h d and BS-IRS-UE channel V, thereby completing the conversion of the entire channel into two components.

[0093] In an embodiment, the double-channel input-output model is solved to obtain the BS-UE channel component estimation result and the BS-IRS-UE channel component estimation result, specifically including:

[0094] In response to C≥N+1, the least square estimation method is used to solve the double-channel input-output model to obtain the BS-UE channel component estimation result and the BS-IRS-UE channel component estimation result;

[0095] Alternatively, in response to C<N+1, the dimensionality of N is reduced to The BS-IRS-UE channel component and the Ω term in the double-channel input-output model are reduced to The least square estimation method is used to solve the reduced double-channel input-output model to obtain the BS-UE channel component estimation result and the reduced BS-IRS-UE channel component estimation result.

[0096] Specifically, in the embodiment, the IRS unit introduces a phase shift on the incident signal, and the phase difference between the units is 180°. Since each IRS element has two states of "ON" and "OFF", we use "+1" and "-1" to represent the two states respectively, so the pilot matrix can be represented by a Hadamard matrix (Hadamard matrix, which is composed of +1 and -1 elements and satisfies Hn*Hn'=nI) of column vectors orthogonal n order square matrix, Hn' is the transpose of Hn, and I is the unit matrix) N , which satisfies and H N is the conjugate transpose, and I N represents the N-order unit matrix, that is, all pilot signals can be represented as:

[0097]

[0098] The system presets the reflection coefficient as Ω, and the pilot transmission matrix according to formula (6) is:

[0099]

[0100] When Ω pilot is full rank, that is, Using the least square estimation method, the unique channel estimation value of the system is obtained, that is, as shown in Figure 4 Step S103 is performed to determine whether C≥N+1, if yes, Ω pilot is full rank, otherwise, step S104 needs to be performed on N to reduce the dimension to so that the pilot transmission matrix after dimension reduction is full rank, and then step S105 is performed to calculate the reduced Ω de , in formula (6), step S106 is performed, N=N de , Ω=Ω de , and then step S107 is performed to solve the double channel input-output model by the least square method, and finally step S108 is performed to output the double channel estimation result.

[0101] In an embodiment, in response to C≥N+1, the least square estimation method is used to solve the double channel input-output model to obtain the BS-UE channel component estimation result and the BS-IRS-UE channel component estimation result, specifically including:

[0102] In response to C≥N+1, the least square estimation method is used to process formula (6) to obtain:

[0103]

[0104] According to W is negligible, and the following is obtained:

[0105]

[0106] wherein, is the BS-UE channel component estimation result, is the BS-IRS-UE channel component estimation result.

[0107] Specifically, in the present embodiment, generally, in the least square estimation process, W does not contain negligible; denotes the estimation result of [h d ,V T ]; i.e. the calculation result, the calculation process includes filter signal processing and DFT calculation, and the actual number is the result after simulation; the reflection coefficient is an important parameter of the IRS, and the transmitted signal is reflected by the N elements of the IRS, and the phase and amplitude change.

[0108] In an embodiment, in response to C < N+1, dimension reduction is performed on N to the BS-IRS-UE channel component and the Ω term in the double-channel input-output model are dimensionally reduced to The least square estimation method is used to solve the dimensionally reduced double-channel input-output model to obtain the BS-UE channel component estimation result and the dimensionally reduced BS-IRS-UE channel component estimation result, specifically including:

[0109] In response to C < N+1, dimension reduction is performed on N:

[0110]

[0111] wherein i∈{1,2,…,N}, i starts from 1 and is valued until the condition a reflection group is formed by adjacent (i+1) reflection units, and reflection groups are obtained;

[0112] for each reflection group, the reflection coefficient of one of the reflection units is randomly selected as the reflection coefficient of each reflection unit in the group, and reflection coefficients of wherein denotes a set of reflection coefficients of

[0113] Ω de is substituted into equation (6) to obtain:

[0114]

[0115] least square estimation is performed on equation (9) to obtain:

[0116]

[0117] wherein V de is the reduced dimension BS-IRS-UE channel component, is the BS-UE channel component estimation result, is the reduced dimension BS-IRS-UE channel component estimation result.

[0118] Specifically, in the present embodiment, when the pilot length C < N+1, Ω pilot cannot satisfy the full rank condition, we cannot obtain the solution of the channel component by least square estimation, and the length of the pilot signal refers to transmitting C pilot signals, and the IRS needs to be configured C times: Consider channel estimation by dimension reduction method, since the volume of each IRS element on the IRS surface is very small, consider ignoring the multipath fading difference between adjacent elements of the IRS, and regard it as the same channel gain, a method of reducing the size of the channel matrix is proposed, as shown in Figure 5 , multiple reflecting elements are regarded as a reflecting group, and each group contains (i+1) elements, represents the number of elements after dimension reduction of the IRS, and the original number of elements of the IRS is N, and the number of elements of the IRS is now And randomly take the reflection coefficient of an element in the reflecting group as the reflection coefficient of all elements in the group, so that the elements in each reflecting group have the same reflection coefficient, and the reduced dimension IRS configuration is represented as Ω de , substitute equation (6) into equation (9) to obtain equation (9), and solve equation (9) by using the least square estimation method to obtain equation (10).

[0119] Embodiment 2:

[0120] As shown in Figure 2 , the present embodiment 2 provides a data transmission method, which transmits data through a data transmission protocol, and the data transmission protocol is used to:

[0121] Divide the coherence time of the wireless communication system into three stages;

[0122] In the first stage, make the pilot signal transmitted through the BS-UE channel and the BS-IRS-UE channel in the wireless communication system, and obtain the BS-UE channel component estimation result and the BS-IRS-UE channel component estimation result by using the channel estimation method as described in embodiment 1;

[0123] In the second stage, optimize the reflection coefficient based on the BS-IRS-UE channel component estimation result;

[0124] In the third stage, data is transmitted based on the optimized reflection coefficients, the BS-UE channel component estimation result and the BS-IRS-UE channel component estimation result.

[0125] In an embodiment, the coherence time is normalized to the OFDM symbol duration, the pilot signals are C pilot signals transmitted by the UE, the channel estimation method is performed by the BS based on the received C pilot signals, the reflection coefficients are optimized by the BS based on the BS-IRS-UE channel component estimation result and transmitted to the IRS controller, the adjustment of the reflection coefficients of each reflection unit of the IRS is controlled by the IRS controller based on the optimized reflection coefficients, data is transmitted by the BS and the IRS through the BS-IRS-UE channel based on the BS-IRS-UE channel component estimation result and the optimized reflection coefficients, and data is transmitted by the BS through the BS-UE channel based on the BS-UE channel component estimation result.

[0126] Specifically, in this embodiment, pilot transmission and channel estimation are performed in the first stage of the coherence time, specifically, C pilot signals are transmitted by the user to the BS and reflected by the IRS, the pilot signals are transmitted for channel estimation, and through this pilot signal transmission process, the BS estimates the BS-UE channel and the BS-IRS-UE channel based on the received signals, and embodiment 1 is mainly to perform the channel estimation of this stage; the second stage is the feedback delay, the BS optimizes the reflection coefficients based on the estimated channel and feeds back to the IRS controller, and the feedback delay is τ; the third stage is data transmission, the system transmits data based on the optimized reflection coefficients and the estimated channel, and the pilot signals and the transmitted data pass through the same channel. In theory, the base station can also transmit pilot signals.

[0127] The channel estimation methods proposed in embodiments 1 and 2 can be applied to an IRS wireless communication system based on OFDM, different numbers of pilot signals can be transmitted by the system to estimate the channel, the pilot signals are repeatedly transmitted, and the BS-UE channel and the BS-IRS-UE channel are estimated by the least square method at the receiving end. At the same time, a data transmission protocol is proposed to support the channel estimation method.

[0128] Embodiment 3:

[0129] As shown in Figure 6 , the present disclosure embodiment 3 provides a channel estimation device, which comprises:

[0130] The acquisition configuration module 11 is used to acquire the configuration parameters of the pilot signals transmitted through the BS-UE channel and the BS-IRS-UE channel in the wireless communication system;

[0131] The model establishing module 12 is connected with the configuration obtaining module 11, and is configured to establish a dual-channel input-output model of the pilot signals transmitted in the wireless communication system according to the configuration parameters, wherein the dual-channel input-output model includes a BS-UE channel component and a BS-IRS-UE channel component.

[0132] The result solving module 13 is connected with the model establishing module 12, and is configured to solve the dual-channel input-output model to obtain the BS-UE channel component estimation result and the BS-IRS-UE channel component estimation result.

[0133] Wherein, the IRS is an intelligent reflecting surface, the BS is a base station, and the UE is a user equipment.

[0134] In an embodiment, the configuration obtaining module 11 is specifically configured to:

[0135] The C pilot signals are transmitted in the wireless communication system through the BS-UE channel and the BS-IRS-UE channel, and the reflection coefficients of the N IRS reflecting units of the wireless communication system to the C pilot signals are configured as Ω Wherein Ω represents a set of reflection coefficients of the N reflecting units to one signal, and the configuration parameters including Ω are obtained.

[0136] Wherein, Ω represents an N×C-dimensional complex set, Ω represents an N-dimensional complex set.

[0137] In an embodiment, the model establishing module 12 specifically includes:

[0138] The first model unit is configured to establish a single-signal system input-output model for each signal transmitted in the wireless communication system based on OFDM, wherein the single-signal system input-output model includes FIR related terms, and the FIR is composed of a BS-UE channel response and a BS-IRS-UE channel response;

[0139] The second model unit is configured to combine the single-signal system input-output models corresponding to the C pilot signals and extract the BS-UE channel component, the BS-IRS-UE channel component and the Ω term according to the BS-IRS-UE channel response related to Ω, so as to obtain the dual-channel input-output model.

[0140] Wherein, the OFDM is orthogonal frequency division multiplexing, and the FIR is a finite-length unit impulse response.

[0141] In an embodiment, the result solving module 13 specifically includes:

[0142] The direct solving unit is configured to, in response to C≥N+1, solve the dual-channel input-output model by using a least square estimation method to obtain the BS-UE channel component estimation result and the BS-IRS-UE channel component estimation result.

[0143] a dimension reduction solving unit configured to reduce dimensions of N to reduce dimensions of BS-IRS-UE channel components and Ω terms in the two-channel input-output model to solving the reduced two-channel input-output model by using a least square estimation method to obtain BS-UE channel component estimation results and reduced BS-IRS-UE channel component estimation results.

[0144] Embodiment 4:

[0145] As shown in Figure 2 Embodiment 4 of the present disclosure provides a data transmission device, which sets a data transmission protocol, and the data transmission protocol is used for:

[0146] dividing a coherence time of a wireless communication system into three stages;

[0147] in the first stage, transmitting a pilot signal through a BS-UE channel and a BS-IRS-UE channel in the wireless communication system, and obtaining BS-UE channel component estimation results and BS-IRS-UE channel component estimation results by using the channel estimation method as described in Embodiment 1;

[0148] in the second stage, optimizing a reflection coefficient based on the BS-IRS-UE channel component estimation results;

[0149] in the third stage, transmitting data based on the optimized reflection coefficient, the BS-UE channel component estimation results and the BS-IRS-UE channel component estimation results.

[0150] Embodiment 5:

[0151] As shown in Figure 1 Embodiment 5 of the present disclosure provides a wireless communication system, which comprises:

[0152] a BS configured to receive a pilot signal transmitted by a UE, obtain BS-UE channel component estimation results and BS-IRS-UE channel component estimation results by using the channel estimation method as described in Embodiment 1, optimize a reflection coefficient based on the BS-IRS-UE channel component estimation results, and transmit the optimized reflection coefficient to an IRS controller;

[0153] an IRS controller connected with the BS, configured to receive the optimized reflection coefficient transmitted by the BS, and control the IRS according to the optimized reflection coefficient;

[0154] an IRS connected with the IRS controller, configured to adjust reflection coefficients of each reflection unit of the IRS according to the control of the IRS controller;

[0155] The BS and IRS transmit data through the BS-IRS-UE channel based on the BS-IRS-UE channel component estimation results and optimized reflection coefficients, while the BS transmits data through the BS-UE channel based on the BS-UE channel component estimation results.

[0156] Example 6:

[0157] Embodiment 6 of this disclosure provides a computer-readable storage medium storing a computer program that, when executed by a processor, implements the channel estimation method as described in Embodiment 1 or the data transmission method as described in Embodiment 2.

[0158] The computer-readable storage medium includes volatile or non-volatile, removable or non-removable media implemented in any method or technology for storing information (such as computer-readable instructions, data structures, computer program modules, or other data). Computer-readable storage media include, but are not limited to, RAM (Random Access Memory), ROM (Read-Only Memory), EEPROM (Electrically Erasable Programmable Read-Only Memory), flash memory or other memory technologies, CD-ROM (Compact Disc Read-Only Memory), DVD or other optical disc storage, cartridges, magnetic tapes, disk storage or other magnetic storage devices, or any other medium that can be used to store desired information and is accessible to a computer.

[0159] In addition, this disclosure may also provide a computer device including a memory and a processor, wherein the memory stores a computer program, and when the processor runs the computer program stored in the memory, the processor executes the channel estimation method as described in Embodiment 1 or the data transmission method as described in Embodiment 2.

[0160] The memory is connected to the processor. The memory can be flash memory, read-only memory or other types of memory. The processor can be a central processing unit or a microcontroller.

[0161] Embodiments 1-6 of the present disclosure provide a channel estimation method, a data transmission method, a channel estimation device, a data transmission device, a wireless communication system and a computer readable storage medium. By establishing an input-output model of a pilot signal about a BS-UE channel and a BS-IRS-UE channel, the estimation object is converted into two components of the BS-UE channel and the BS-IRS-UE channel, and the estimation results of the BS-UE channel and the BS-IRS-UE channel are obtained by solving the model, thereby reducing the pilot overhead and providing an effective channel estimation method for an IRS wireless communication system.

[0162] It can be understood that the above embodiments are only exemplary embodiments adopted for illustrating the principles of the present disclosure, and the present disclosure is not limited thereto. Various modifications and improvements can be made by those of ordinary skill in the art without departing from the spirit and essence of the present disclosure, and these modifications and improvements are also considered as the protection scope of the present disclosure.

Claims

1. A method of channel estimation, characterized by, The method comprises: Obtaining configuration parameters of pilot signals transmitted through BS-UE channels and BS-IRS-UE channels in a wireless communication system; According to the configuration parameters, a double-channel input-output model of the pilot signals transmitted in the wireless communication system is established, which includes BS-UE channel components and BS-IRS-UE channel components, and specifically comprises: For each signal transmitted in the wireless communication system, a single-signal system input-output model is established based on OFDM, which includes FIR related terms, and the FIR is composed of BS-UE channel responses and BS-IRS-UE channel responses, According to the fact that the BS-IRS-UE channel response is related to Ω, the single-signal system input-output models corresponding to the C pilot signals are combined and the BS-UE channel components, BS-IRS-UE channel components and Ω terms are extracted to obtain a double-channel input-output model; Solving the double-channel input-output model to obtain BS-UE channel component estimation results and BS-IRS-UE channel component estimation results. Wherein, IRS is an intelligent reflecting surface, BS is a base station, UE is a user equipment, OFDM is orthogonal frequency division multiplexing, FIR is a finite-length unit impulse response, Ω is the reflection coefficient of N IRS reflecting elements of the wireless communication system to C pilot signals, and the C pilot signals are transmitted through BS-UE channels and BS-IRS-UE channels in the wireless communication system.

2. The method of claim 1, wherein, Obtaining configuration parameters of pilot signals transmitted through BS-UE channels and BS-IRS-UE channels in a wireless communication system, specifically comprising: The reflection coefficients of N IRS reflecting units of the wireless communication system on the C pilot signals are configured wherein denotes a set of reflection coefficients of N reflecting units on one signal, and the configuration parameters including Ω are obtained; wherein, denotes the set of N x C complex numbers, denotes the set of N complex numbers.

3. The method of claim 2, wherein, For each signal transmitted in the wireless communication system, a single-signal system input-output model is established based on OFDM, which includes FIR related terms, and the FIR is composed of BS-UE channel responses and BS-IRS-UE channel responses, specifically comprising: Divide the bandwidth served by the wireless communication system for each user into K orthogonal subcarriers, represent the transmitted signal as a discrete-time signal {x[k], k = 1,..., K}, and represent the received signal as: where {h θ [l]:l = 0,..., M - 1} represent FIR coefficients describing the wideband channel in the time domain, M is the number of taps, the tap index l = {0, 1,..., M - 1}, {w[k]} is the noise at the receiver, wherein, h d [l] denotes the BS-UE channel response in the time domain, denotes the BS-IRS-UE channel response in the time domain, denotes the BS-IRS-UE channel component in the time domain; The DFT of equation (1) is performed by adding a cyclic prefix of length N cp to convert the channel transmission signal into K parallel sub-channel transmission signals to obtain a single-signal system input-output model based on OFDM: Simplify formula (2) to where N cp +1 < K, DFT is a discrete Fourier transform, denotes a column vector consisting of K received signals, denotes a column vector consisting of K FIR coefficients, denotes a column vector consisting of K transmitted signals, denotes a column vector consisting of K noises.

4. The method of claim 3, wherein, According to the fact that the FIR is composed of BS-UE channel responses and BS-IRS-UE channel responses, and the BS-IRS-UE channel response is related to Ω, the single-signal system input-output models corresponding to the C pilot signals are combined and the BS-UE channel components, BS-IRS-UE channel components and Ω terms are extracted to obtain a double-channel input-output model, specifically comprising: According to formula (3), the single-signal system input-output model corresponding to the cth pilot signal is obtained: where c = 1,..., C, P is the transmit power, B is the bandwidth, is the power of a quadrature subcarrier transmission signal; According to the fact that the FIR is composed of BS-UE channel responses and BS-IRS-UE channel responses, let: where F is a DFT matrix of size K x M, representing K-point DFT on the BS-UE channel response and the BS-IRS-UE channel response, BS-UE channel components BS-IRS-UE channel components denotes the transpose of a matrix, denotes a set of N x M complex numbers; According to formula (4) and (5), the single-signal system input-output models corresponding to the C pilot signals are combined and the BS-UE channel components, BS-IRS-UE channel components and Ω terms are extracted to obtain a double-channel input-output model: wherein, [1,...,1] denotes h d no IRS reflection, 5. The method of claim 4, wherein, Solving the double-channel input-output model to obtain BS-UE channel component estimation results and BS-IRS-UE channel component estimation results, specifically comprising: In response to C≥N+1, a least square estimation method is used to solve the double-channel input-output model to obtain BS-UE channel component estimation results and BS-IRS-UE channel component estimation results; Or, in response to C < N+1, reduce dimensionality to N Reduce dimensionality of the BS-IRS-UE channel component and the Ω term in the dual-channel input-output model to Solve the reduced dimensionality dual-channel input-output model using least squares estimation method to obtain BS-UE channel component estimation result and reduced dimensionality BS-IRS-UE channel component estimation result.

6. The method of claim 5, wherein, In response to C≥N+1, a least square estimation method is used to solve the double-channel input-output model to obtain BS-UE channel component estimation results and BS-IRS-UE channel component estimation results, specifically including: In response to C≥N+1, a least square estimation method is used to solve the double-channel input-output model to obtain BS-IRS-UE channel component estimation results and BS-IRS-UE channel component estimation results, specifically including: According to W is negligible, resulting in: wherein, is a BS-UE channel component estimate, is a BS-IRS-UE channel component estimate.

7. The method of claim 5, wherein, In response to C < N+1, reduce dimensionality to Reduce dimensionality of BS-IRS-UE channel components and Ω terms in the dual-channel input-output model to Solve the reduced dimensionality dual-channel input-output model using least squares estimation method to obtain BS-UE channel component estimation results and reduced dimensionality BS-IRS-UE channel component estimation results, specifically including: In response to C<N+1, dimensionality reduction is performed on N: wherein i∈{1,2,…,N}, i takes value from 1 until the condition A reflection group is formed by adjacent (i+1) reflection units, and the following is obtained reflection groups The reflection coefficient of one of the reflection units in each reflection group is randomly selected as the reflection coefficient of each reflection unit in the group, and the reflection coefficient of the reflection group is obtained wherein represents a set of reflection coefficients of one signal by the reflection group​ Substituting equation (6) into equation (5) gives: de Substituting equation (6) into equation (5) gives: A least square estimation is performed on formula (9) to obtain: wherein V de is the reduced dimension BS-IRS-UE channel component, is the BS-UE channel component estimate, is the reduced dimension BS-IRS-UE channel component estimate.

8. A data transmission method, characterized by, The method transmits data through a data transmission protocol, and the data transmission protocol is used to: Divide the coherence time of the wireless communication system into three stages; In the first stage, the pilot signal is transmitted through the BS-UE channel and the BS-IRS-UE channel in the wireless communication system, and the BS-IRS-UE channel component estimation results and the BS-IRS-UE channel component estimation results are obtained by using the channel estimation method according to any one of claims 1-7; In the second stage, the reflection coefficient is optimized based on the BS-IRS-UE channel component estimation results; In the third stage, data is transmitted based on the optimized reflection coefficient, the BS-IRS-UE channel component estimation results and the BS-IRS-UE channel component estimation results.

9. The method of claim 8, wherein, The coherence time is normalized to the OFDM symbol duration, the pilot signal is C pilot signals sent by the UE, the channel estimation method is performed by the BS based on the received C pilot signals, the reflection coefficient is optimized by the BS based on the BS-IRS-UE channel component estimation results and is sent to the IRS controller, the reflection coefficient of each reflection unit of the IRS is adjusted by the IRS controller based on the optimized reflection coefficient, and data is transmitted by the BS and the IRS through the BS-IRS-UE channel based on the BS-IRS-UE channel component estimation results and the optimized reflection coefficient. The BS transmits data through the BS-UE channel based on the BS-UE channel component estimation results.

10. A channel estimation apparatus characterized by comprising: Comprise: An acquisition configuration module is configured to acquire configuration parameters of a pilot signal transmitted through a BS-UE channel and a BS-IRS-UE channel in a wireless communication system; A model establishment module is connected with the acquisition configuration module and is configured to establish a double-channel input-output model of the pilot signal transmitted in the wireless communication system according to the configuration parameters, wherein the double-channel input-output model includes BS-UE channel components and BS-IRS-UE channel components, and specifically includes: For each signal transmitted in the wireless communication system, a single-signal system input-output model is established based on OFDM, wherein the single-signal system input-output model includes FIR related terms, and the FIR is composed of BS-UE channel responses and BS-IRS-UE channel responses, According to the correlation between the BS-IRS-UE channel response and Ω, the single-signal system input-output models corresponding to the C pilot signals are combined, and the BS-UE channel components, the BS-IRS-UE channel components and the Ω terms are extracted to obtain a double-channel input-output model; The solving result module is connected with the model establishing module, and is configured to solve the double-channel input-output model to obtain BS-UE channel component estimation results and BS-IRS-UE channel component estimation results. In the formula, IRS is an intelligent reflecting surface, BS is a base station, UE is a user equipment, OFDM is orthogonal frequency division multiplexing, FIR is a finite-length unit impulse response, and Ω is a reflection coefficient of N IRS reflecting units of a wireless communication system to C pilot signals, and the C pilot signals are transmitted through a BS-UE channel and a BS-IRS-UE channel in the wireless communication system.

11. A data transmission apparatus, characterized by comprising: The device sets a data transmission protocol, and the data transmission protocol is used for: Dividing a coherence time of the wireless communication system into three stages; In the first stage, the pilot signals are transmitted through the BS-UE channel and the BS-IRS-UE channel in the wireless communication system, and the BS-UE channel component estimation results and the BS-IRS-UE channel component estimation results are obtained by using the channel estimation method in any one of claims 1-7; In the second stage, the reflection coefficient is optimized based on the BS-IRS-UE channel component estimation results; In the third stage, the data is transmitted based on the optimized reflection coefficient, the BS-UE channel component estimation results and the BS-IRS-UE channel component estimation results.

12. A wireless communication system, characterized by The method comprises: The BS is configured to receive the pilot signals transmitted by the UE, obtain the BS-UE channel component estimation results and the BS-IRS-UE channel component estimation results by using the channel estimation method in any one of claims 1-7, optimize the reflection coefficient based on the BS-IRS-UE channel component estimation results, and transmit the optimized reflection coefficient to the IRS controller; The IRS controller is connected with the BS, and is configured to receive the optimized reflection coefficient transmitted by the BS, and control the IRS according to the optimized reflection coefficient; The IRS is connected with the IRS controller, and is configured to adjust the reflection coefficient of each reflecting unit of the IRS according to the control of the IRS controller; The BS and the IRS transmit data through the BS-IRS-UE channel based on the BS-IRS-UE channel component estimation results and the optimized reflection coefficient, and the BS transmits data through the BS-UE channel based on the BS-UE channel component estimation results.

13. A computer-readable storage medium, characterized in that, The computer readable storage medium stores a computer program, and when the computer program is run by a processor, the channel estimation method in any one of claims 1-7 or the data transmission method in any one of claims 8-9 is implemented.

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