Estimation device, wireless communication system including the same, and program for causing a computer to execute the same

Abstract

To provide an estimation device capable of suppressing a deviation caused by a lag between an estimated time and a transmission time in a propagation path between a transmitter and a receiver.SOLUTION: Upon receiving a reception signal of a pilot signal from communication means 32, estimation means 41 estimates a frequency response FQR_0 of a propagation path at a time point, in which the reception signal is received, based on the received reception signal of the pilot signal and estimates G pieces of frequency responses FQR_1-FQR_G, which are frequency responses at G pieces of time points of future time points from a time point, in which a receiver 3 receives the reception signal, using an autoregression model based on the estimated frequency response FQR_0. Optimization means 42 optimizes reflection coefficients of N pieces of reflection elements of IRS and transmission weights of MT pieces of antennas of a transmitter using the frequency response FQR_0 and G pieces of frequency responses FQR_1-FQR_G.SELECTED DRAWING: Figure 2

Description

[Technical Field]

[0001] The present invention relates to an estimation device, a wireless communication system including the same, and a program to be executed by a computer. [Background technology]

[0002] Next-generation communications standards call for the creation of a communications infrastructure that will enable access to all people, information, and things anywhere, both domestically and internationally, by utilizing high-frequency bands such as millimeter waves and terahertz waves, while enhancing the high speed, large capacity, low latency, and multiple connection capabilities that are characteristic of fifth-generation mobile communications systems (5G).

[0003] High-frequency radio waves cannot be expected to propagate beyond line-of-sight, resulting in weak spots. For this reason, there has been active research into technology that solves the problem of high-frequency radio waves by using an intelligent reflecting surface (IRS), which is made up of multiple passive reflecting elements whose reflection characteristics can be dynamically changed (Non-Patent Document 1). By appropriately changing the reflection characteristics of each element and creating a radio wave propagation path that bypasses obstacles, stable communication can be achieved even beyond line-of-sight.

[0004] IRS basically acts as an electromagnetic wave reflector and does not have high-frequency circuits, so it has the advantage of consuming significantly less power than conventional multi-hop communications for expanding coverage. [Prior art documents] [Non-patent literature]

[0005] [Non-Patent Document 1] Q. Wu and R. Zhang, “Towards Smart and Reconfigurable Environment: Intelligent Reflecting Surface Aided Wireless Network,” IEEE Commun. Mag., vol. 58, no. 1, pp. 106-112, 2020. [Non-patent document 2] E. Basar, M. Di Renzo, J. De Rosny, M. Debbah, MS Alouini, and R. Zhang, “Wireless Communications Through Reconfigurable Intelligent Surfaces,” IEEEAccess, vol. 7, no. June 2018, pp. 116753-116773, 2019. [Non-patent document 3] Y. Yang, B. Zheng, S. Zhang, and R. Zhang, “Intelligent reflecting surface meets OFDM: Protocol design and rate maximization,” 2019.[Online]. Available: https: / / arxiv.org / abs / 1906.09956. [Non-patent document 4] B. Zheng and R. Zhang, “Intelligent Reflecting Surface-Enhanced OFDM: Channel Estimation and Reflection Optimization,” IEEE Wirel. Commun. Lett., vol. 9, no. 4, pp. 518-522, 2020. [Non-patent document 5] Q.-U.-A. Nadeem, H. Alwazani, A. Kammoun, A. Chaaban, M.Debbah, and M.-S. Alouini, “Intelligent Reflecting Surface-Assisted Multi-User MISO Communication: Channel Estimation and Beamforming Design,” IEEE Open J. Commun. Soc., vol. 1, no. March, pp. 661-680, 2020. [Non-patent document 6] B. Zheng, C. You, and R. Zhang, “Fast Channel Estimation for IR-S Assisted OFDM,” IEEE Wirel. Commun. Lett., vol. 10, no. 3, pp.580-584, 2021. [Non-Patent Document 7] W. Jiang and H. Di. Schotten, “A Comparison of Wireless Channel Predictors: Artificial Intelligence Versus Kalman Filter,” IEEE Int. Conf. Commun., 2019. [Non-patent document 8] Y. Yang, B. Zheng, S. Zhang, and R. Zhang, “Intelligent Reflecting Surface Meets OFDM: Protocol Design and Rate Maximization,” IEEE Trans. Commun., vol. 68, no. 7, pp. 4522-4535, Jul. 2020. Summary of the Invention [Problem to be solved by the invention]

[0006] However, in a wireless communication system using an IRS (an IRS-assisted system), in order to optimize the reflection coefficients for all reflecting elements on the IRS, it is necessary to estimate a huge number of propagation paths, which exist as many as the combinations of the transmitting antenna, each reflecting element, and the receiving antenna (Non-Patent Documents 2 to 6).

[0007] Although channel estimation is typically performed using a known training signal between the transmitter and receiver, in an IRS-assistant system, a long training period is required to estimate the channel group due to the large number of channel groups. Furthermore, since the receiver must feed back the channel group estimates or the reflection pattern information calculated from the estimates to the IRS, a longer lag is likely to occur between the time channel estimation (channel estimation) is performed and data transmission compared to systems without IRS. When a wireless terminal moves, the channel inevitably fluctuates, and if the lag from the time of estimation is large, controlling the IRS based on past channel estimates (channel estimation values) will not maximize its performance.

[0008] Therefore, according to an embodiment of the present invention, an estimation device is provided that can suppress the discrepancy due to the lag between the estimated time of the propagation path between the transmitter and the receiver and the transmission time.

[0009] Furthermore, according to an embodiment of the present invention, there is provided a wireless communication system including an estimation device capable of suppressing the discrepancy due to the lag between the estimated time of the propagation path between the transmitter and the receiver and the transmission time.

[0010] Furthermore, according to an embodiment of the present invention, there is provided a program for causing a computer to suppress possible deviation due to lag between the estimated time of the propagation path between the transmitter and receiver and the transmission time. [Means for solving the problem]

[0011] (Configuration 1) According to an embodiment of the present invention, the estimation device T (M Ta transmitter having N (N is an integer of 2 or more) antennas, an IRS which is an electromagnetic wave reflector having N (N is an integer of 2 or more) reflecting elements whose reflection characteristics can be dynamically changed, and M R (M R In a wireless communication space in which a transmitter and a receiver each having (an integer equal to or greater than 2) antennas are non-linearly arranged, when the transmitter transmits a pilot signal, which is a known signal, to the receiver, the estimation device is configured to estimate, at the receiver, the frequency response of a propagation path between the transmitter and the receiver, the estimation device comprising an estimation means and an optimization means. When the estimation means receives a received signal of the pilot signal, the estimation means estimates a frequency response FQR_0 of the propagation path at the time the received signal is received based on the received signal, and executes an estimation process based on the estimated frequency response FQR_0 using an autoregressive model to estimate G frequency responses FQR_1 to FQR_G, which are frequency responses at G (G is an integer equal to or greater than 1 and is the total number of times at which the frequency responses of the propagation path are estimated) time points in the future from the time the receiver receives the received signal. The optimization means uses the frequency response FQR_0 and the G frequency responses FQR_1 to FQR_G to optimize the reflection coefficients of N reflecting elements and M T An optimization process is performed to optimize the transmit weights of the antennas.

[0012] (Configuration 2) In configuration 1, in the estimation process, the estimation means sets the estimated frequency response FQR_0 as the initial value of the frequency response, estimates the first frequency response FQR_1 from the initial value, and then executes the estimation process to estimate the gth (g is an integer satisfying 1≦g≦(G−1))th frequency response FQR_g to the (g+1)th frequency response FQR_g+1 sequentially for all g=1 to (G−1), thereby estimating G frequency responses FQR_1 to FQR_G.

[0013] (Configuration 3) In configuration 2, frequency response FQR_0 and each of the g frequency responses FQR_1 to FQR_g consist of a first frequency response that indicates the frequency response of a direct link, which is the propagation path when radio waves reach the receiver directly from the transmitter, and a second frequency response that indicates the frequency response of an indirect link, which is the propagation path when radio waves reach the receiver from the transmitter via an IRS, and each of the first frequency response and second frequency response of frequency response FQR_0 is set to an initial value. Then, in the estimation process, the estimation means estimates a first first frequency response from the initial value of the first frequency response of the estimated frequency response FQR_0 and estimates a first second frequency response from the initial value of the second frequency response of the estimated frequency response FQR_0, then estimates a (g+1)th first frequency response from the gth first frequency response, estimates a (g+1)th second frequency response from the gth second frequency response, estimates a gth frequency response FQR_g consisting of the gth first frequency response and the gth second frequency response, and estimates a (g+1)th frequency response FQR_g+1 consisting of the (g+1)th first frequency response and the (g+1)th second frequency response, and estimates G frequency responses FQR_1 to FQR_G by sequentially executing this process for all g=1 to (G-1).

[0014] (Configuration 4) In any one of the configurations 1 to 3, the estimation means is configured to estimate the T Only one antenna among the antennas is used to transmit a pilot signal, and antennas other than the one antenna are not used to transmit a pilot signal. T By index modulation, pilot signals are assigned to the antenna patterns of (N+1)M antennas and transmitted. T When pilot signals are sequentially transmitted to the receiver, in the estimation process, each time one pilot signal is received, a process of estimating one column of a frequency response matrix indicating the frequency response of the propagation path is performed for all columns of the frequency response matrix to estimate the frequency response matrix, and a frequency response FQR_0 consisting of the estimated frequency response matrix is ​​estimated.

[0015] (Configuration 5) In configuration 4, (N+1)M by index modulation T The transmission of pilot signals is performed by the transmitter using M T The antenna patterns of the antennas are (N+1)M T Sequentially change to (N+1)M antenna patterns T This is done by sequentially transmitting pilot signals.

[0016] (Configuration 6) In the configuration 4 or 5, the estimation means performs matrix interpolation on the estimated frequency response matrix in the estimation process to interpolate between elements of the frequency response matrix, and estimates the frequency response matrix after matrix interpolation as the frequency response FQR_0.

[0017] (Configuration 7) In configuration 6, the estimation means generates a Hankel matrix from the estimated frequency response matrix in the estimation process, decomposes the generated Hankel matrix into a product of a first and a second matrix by singular value decomposition, and performs updating of the first matrix, updating of the second matrix, and updating of the Hankel matrix a predetermined number of times, thereby performing matrix interpolation.

[0018] (Configuration 8) In any of configurations 1 to 7, the N reflecting elements are grouped into c (c is an integer equal to or greater than 1) clusters, each of which has the same frequency response of the propagation path. The reflecting elements included in each of the c clusters are controlled to have the same reflection characteristics.

[0019] (Configuration 9) In any one of configurations 1 to 8, the estimation device further comprises a feedback means. The feedback means receives the reflection coefficients of the N reflecting elements optimized by the optimization means and M T The transmit weights of the antennas are fed back to the IRS and the transmitter, respectively.

[0020] (Configuration 10) According to an embodiment of the present invention, a wireless communication system includes a receiver including the estimation device according to any one of configurations 1 to 9, a transmitter, and an IRS.

[0021] (Configuration 11) Further, according to an embodiment of the present invention, the program T (M T a transmitter having N (N is an integer of 2 or more) antennas, an IRS which is an electromagnetic wave reflector having N (N is an integer of 2 or more) reflecting elements whose reflection characteristics can be dynamically changed, and M R (M R is a program for causing a computer to execute, in an estimation device of a receiver, an estimation of a frequency response of a propagation path between a transmitter and a receiver, when the transmitter transmits a pilot signal, which is a known signal, to the receiver in a wireless communication space in which the transmitter and the receiver have antennas (an integer equal to or greater than 2) arranged non-linearly, a first step of executing an estimation process in which, when an estimation means receives a received signal of a pilot signal, it estimates a frequency response FQR_0 of the propagation path at the time when the received signal is received based on the received signal, and, based on the estimated frequency response FQR_0, it uses an autoregressive model to estimate G frequency responses FQR_1 to FQR_G which are frequency responses at G time points (G is an integer equal to or greater than 1 and is the total number of time points at which the frequency responses of the propagation path are estimated) that are future time points from the time when the receiver receives the received signal; The optimization means calculates the reflection coefficients of the N reflecting elements and M using the frequency response FQR_0 and the G frequency responses FQR_1 to FQR_G. T and a second step of performing an optimization process to optimize the transmit weights of the antennas.

[0022] (Configuration 12) In configuration 11, in the estimation process of the first step, the estimation means sets the estimated frequency response FQR_0 as the initial value of the frequency response, estimates the first frequency response FQR_1 from the initial value, and then executes the estimation process to estimate the gth (g is an integer satisfying 1≦g≦(G−1))th frequency response FQR_g to the (g+1)th frequency response FQR_g+1 sequentially for all g=1 to (G−1), thereby estimating G frequency responses FQR_1 to FQR_G.

[0023] (Configuration 13) In configuration 12), the frequency response FQR_0 and each of the g frequency responses FQR_1 to FQR_g consist of a first frequency response that indicates the frequency response of a direct link, which is the propagation path when radio waves reach the receiver directly from the transmitter, and a second frequency response that indicates the frequency response of an indirect link, which is the propagation path when radio waves reach the receiver from the transmitter via an IRS, and each of the first frequency response and the second frequency response of the frequency response FQR_0 is set to an initial value. In the estimation process of the first step, the estimation means estimates a first first frequency response from the initial value of the first frequency response of the estimated frequency response FQR_0 and estimates a first second frequency response from the initial value of the second frequency response of the estimated frequency response FQR_0, then estimates a (g+1)th first frequency response from the gth first frequency response, estimates a (g+1)th second frequency response from the gth second frequency response, estimates a gth frequency response FQR_g consisting of the gth first frequency response and the gth second frequency response, and estimates a (g+1)th frequency response FQR_g+1 consisting of the (g+1)th first frequency response and the (g+1)th second frequency response, and repeats this process for all g=1 to (G-1) to estimate G frequency responses FQR_1 to FQR_G.

[0024] (Configuration 14) In any one of the 11th to 13th configurations, the estimation means is configured to estimate the frequency of the signal transmitted from the transmitter by T Only one antenna among the antennas is used to transmit a pilot signal, and antennas other than the one antenna are not used to transmit a pilot signal.T By index modulation, pilot signals are assigned to the antenna patterns of (N+1)M antennas and transmitted. T When pilot signals are sequentially transmitted to the receiver, in the estimation process of the first step, each time one pilot signal is received, a process of estimating one column of a frequency response matrix indicating the frequency response of the propagation path is performed for all columns of the frequency response matrix to estimate the frequency response matrix, and a frequency response FQR_0 consisting of the estimated frequency response matrix is ​​estimated.

[0025] (Configuration 15) In the configuration 14, (N+1)M by index modulation T The transmission of pilot signals is performed by the transmitter using M T The antenna patterns of the antennas are (N+1)M T Sequentially change to (N+1)M antenna patterns T This is done by sequentially transmitting pilot signals.

[0026] (Configuration 16) In configuration 14 or 15, the estimation means performs matrix interpolation on the estimated frequency response matrix in the estimation process of the first step to interpolate between elements of the frequency response matrix, and estimates the frequency response matrix after matrix interpolation as the frequency response FQR_0.

[0027] (Configuration 17) In configuration 16, in the estimation process of the first step, the estimation means generates a Hankel matrix from the estimated frequency response matrix, decomposes the generated Hankel matrix into a product of a first and a second matrix by singular value decomposition, and performs matrix interpolation by updating the first matrix, updating the second matrix, and updating the Hankel matrix a predetermined number of times.

[0028] (Configuration 18) In any of configurations 11 to 17, the N reflecting elements are grouped into c (c is an integer equal to or greater than 1) clusters, each of which has the same frequency response of the propagation path. The reflecting elements included in each of the c clusters are controlled to have the same reflection characteristics.

[0029] (Configuration 19) In any of configurations 11 to 18, the program further comprises: a feedback means for receiving the reflection coefficients of the N reflective elements optimized by the optimization means and M T The computer further executes a third step of feeding back the transmit weights of the antennas to the IRS and the transmitter, respectively. [Effects of the Invention]

[0030] This makes it possible to suppress the discrepancy caused by the lag between the estimated time of the propagation path between the transmitter and receiver and the transmission time. [Brief explanation of the drawings]

[0031] [Figure 1] 1 is a schematic diagram of a wireless communication system in accordance with embodiment 1 of the present invention. [Figure 2] FIG. 2 is a schematic diagram of the receiver shown in FIG. [Figure 3] FIG. 1 is a conceptual diagram illustrating transmission of a pilot signal. [Figure 4] 10 is a timing chart showing the operations of the transmitter 1, the IRS 2, and the receiver 3 when estimating the frequency response of the propagation path. [Figure 5] FIG. 10 is a diagram for explaining the effect of performing eigenvalue decomposition on a channel matrix. [Figure 6] 3 is a flowchart illustrating the operation of the estimation device shown in FIG. 2. [Figure 7] 7 is a flowchart for explaining the detailed operation of step S6 in FIG. 6. [Figure 8] 7 is a flowchart for explaining the detailed operation of step S8 in FIG. 6. [Figure 9]8 is a flowchart for explaining the detailed operation of step S11 in FIG. 7. [Figure 10] 10 is a diagram illustrating a comparison between the relationship between the conventional estimated time and the current time and the relationship between the estimated time and the current time according to the first embodiment. FIG. [Figure 11] FIG. 10 is a schematic diagram of a wireless communication system according to a second embodiment. [Figure 12] FIG. 12 is a schematic diagram of the receiver shown in FIG. [Figure 13] FIG. 1 is a conceptual diagram showing a matrix representation of a received signal, a frequency response, a transmitted signal, and white noise. [Figure 14] FIG. 10 is a conceptual diagram showing the state of a matrix when a reflective element is switched on / off. [Figure 15] FIG. 1 is a conceptual diagram showing the transition of matrices H(t) and g(t) during the training period. [Figure 16] FIG. 1 is a conceptual diagram showing components of a matrix g(t). [Figure 17] FIG. 16 is a diagram for explaining a problem that occurs when estimating a matrix H(t) of a frequency response of a channel by the method shown in FIG. [Figure 18] FIG. 10 is a diagram for explaining a method for extracting elements of an estimated matrix H(t). [Figure 19] FIG. 1 is a conceptual diagram illustrating matrix decomposition. [Figure 20] FIG. 1 illustrates an optimization algorithm. [Figure 21] FIG. 10 is a diagram illustrating a selection matrix. [Figure 22] FIG. 10 is a diagram for explaining a method for restoring a time series from an interpolated Hankel matrix R. [Figure 23] 13 is a flowchart for explaining the operation of the estimation device shown in FIG. 12. [Figure 24] 24 is a flowchart for explaining the detailed operation of step S21 in FIG. 23. [Figure 25] 24 is a flowchart for explaining the detailed operation of step S23 in FIG. 23. DETAILED DESCRIPTION OF THE INVENTION

[0032] DETAILED DESCRIPTION OF THE PREFERRED EMBODIMENTS An embodiment of the present invention will be described in detail with reference to the drawings. In the drawings, the same or corresponding parts are designated by the same reference numerals and description thereof will not be repeated.

[0033] [Embodiment 1] 1 is a schematic diagram of a wireless communication system according to embodiment 1 of the present invention. Referring to Fig. 1, a wireless communication system 10 according to embodiment 1 of the present invention includes a transmitter 1, an IRS 2, and a receiver 3. The receiver 3 includes an estimation device 4.

[0034] Transmitter 1, IRS2, and receiver 3 are arranged in a wireless communication space. Transmitter 1, IRS2, and receiver 3 are arranged in positions where the arrangement [transmitter 1-IRS2-receiver 3] is not on a straight line. More specifically, when the line connecting transmitter 1 and IRS2 is L1 and the line connecting IRS2 and receiver 3 is L2, transmitter 1, IRS2, and receiver 3 are arranged so that the angle α formed by line L1 and line L2 is greater than 0. In other words, transmitter 1, IRS2, and receiver 3 are arranged non-linearly in the wireless communication space.

[0035] Transmitter 1 is M T (M T is an integer equal to or greater than 2), and the receiver 3 has M R (M R has antennas (an integer equal to or greater than 2). T is M R may be the same as M R may be different from.

[0036] In this way, since the transmitter 1 and the receiver 3 have multiple antennas, the wireless communication system 10 transmits and receives signals by MIMO (multiple-input and multiple-output) transmission.

[0037] The IRS 2 includes N (N is an integer equal to or greater than 2) reflecting elements 21 and an IRS controller 22. The N reflecting elements 21 are arranged, for example, in a grid pattern. That is, the N reflecting elements 21 are arranged at equal intervals.

[0038] Transmitter 1 is M T The IRS 2 transmits signals using N antennas. In the IRS 2, the IRS controller 22 controls the reflection coefficients of the N reflecting elements 21 to control the reflection angle and phase of the radio waves by the N reflecting elements 21. The N reflecting elements 21 then reflect the radio waves incident from the transmitter 1 toward the receiver 3. As a result, the radio waves reflected by the N reflecting elements 21 reach the receiver 3.

[0039] The receiver 3 receives the radio waves transmitted from the transmitter 1. In the wireless communication system 10, the propagation path between the transmitter 1 and the receiver 3 consists of a direct link where the radio waves from the transmitter 1 reach the receiver 3 directly, and an indirect link where the radio waves from the transmitter 1 reach the receiver 3 via the IRS 2.

[0040] When there is no obstacle OBT between the transmitter 1 and the receiver 3, the receiver 3 receives the radio waves transmitted from the transmitter 1 using a direct link and an indirect link.

[0041] On the other hand, if an obstacle OBT exists between the transmitter 1 and the receiver 3, the receiver 3 receives the radio waves transmitted from the transmitter 1 using an indirect link.

[0042] Therefore, in the wireless communication system 10, even if an obstacle OBT exists between the transmitter 1 and the receiver 3, radio waves can be transmitted from the transmitter 1 to the receiver 3 by passing through the IRS2.

[0043] In the embodiment of the present invention, it is assumed that IRS is used in a high frequency band, and OFDM (Orthogonal Frequency Division Multiplexing) transmission, which is robust against frequency selective fading, is performed.

[0044] In the wireless communication system 10, when estimating the propagation path from the transmitter 1 to the receiver 3, the transmitter 1 transmits a pilot signal, which is a known signal, by OFDM transmission.

[0045] Then, the receiver 3 receives the pilot signal transmitted from the transmitter 1 and detects the received signal y(t) of the received pilot signal.

[0046] When the receiver 3 detects the received signal y(t) of the pilot signal, the estimation device 4 in the receiver 3 estimates the frequency response FQR_0 of the propagation path between the transmitter 1 and the receiver 3 at the time t0 when the receiver 3 receives the received signal y(t) based on the received signal y(t) using a method described below.

[0047] Then, the estimation device 4 uses the estimated frequency response FQR_0 to estimate the frequency response of the propagation path at G future points in time from point t0 (G is an integer equal to or greater than 1, and is the total number of points in time at which the frequency response of the propagation path is to be estimated), by a method to be described later. G G frequency responses FQR_1 to FQR_G of the propagation paths in are estimated.

[0048] Thereafter, the estimation device 4 uses the estimated frequency response FQR_0 and G frequency responses FQR_1 to FQR_G to calculate the time period from time t0 to t G N reflection coefficients θ of N reflecting elements 21 and M of transmitter 1 T The estimation device 4 then uses the communication function of the receiver 3 to feed back the N reflection coefficients θ of the N reflecting elements 21 to the IRS controller 22 of the IRS 2, and optimizes the M T The transmit weights W of the antennas are fed back to the transmitter 1.

[0049] Transmitter 1 is M T The transmit weights W of the antennas are received from the estimator 4, and the received M TThe signal is transmitted by MIMO transmission using transmission weights W of the antennas.

[0050] The IRS controller 22 receives the N reflection coefficients θ of the N reflecting elements 21 from the estimation device 4, and controls the N reflection coefficients of the N reflecting elements 21 based on the received N reflection coefficients θ of the N reflecting elements 21 to control the reflection angle and phase of the radio waves by the N reflecting elements 21.

[0051] Fig. 2 is a schematic diagram of the receiver 3 shown in Fig. 1. Referring to Fig. 2, the receiver 3 includes an antenna 31, a communication means 32, and an estimation device 4. The estimation device 4 includes an estimation means 41 and an optimization means 42.

[0052] Antenna 31 is M R The communication means 32 receives a received signal y(t) of the pilot signal via the antenna 31 and outputs the received signal y(t) of the pilot signal to the estimation means 41 of the estimation device 4.

[0053] The communication means 32 communicates with the G The reflection coefficients RLT_0 to RLT_G of the N reflecting elements 21 optimized in T The communication means 32 receives the transmission weights W_0 to W_G of the antennas from the optimization means 42 of the estimation device 4. Then, the communication means 32 receives the transmission weights W_0 to W_G of the antennas from the optimization means 42 of the estimation device 4. T The transmit weights W_0 to W_G of the antennas are transmitted to the transmitter 1, and the reflection coefficients RLT_0 to RLT_G of the N reflecting elements 21 are transmitted to the IRS controller 22.

[0054] The estimation means 41 receives the received signal y(t) of the pilot signal from the communication means 32, estimates the frequency response FQR_0 at time t0 based on the received signal y(t) of the pilot signal by a method to be described later, and calculates the frequency response FQR_0 at time t1 to time t2 using the estimated frequency response FQR_0. GThen, the estimation means 41 outputs the estimated frequency response FQR_0 and the G frequency responses FQR_1 to FQR_G to the optimization means .

[0055] The optimization means 42 receives the frequency response FQR_0 and G frequency responses FQR_1 to FQR_G from the estimation means 41, and calculates the frequency response FQR_0 and G frequency responses FQR_1 to FQR_G at the time points t0, t1 to t2 by a method to be described later. G N reflection coefficients θ of N reflecting elements 21 and M of transmitter 1 T The optimization means 42 then optimizes the reflection coefficients RLT_0, RLT_1 to RLT_G and M of the N reflecting elements 21. T The transmission weights W_0, W_1 to W_G of the antennas are output to the communication means 32.

[0056] 3 is a conceptual diagram of transmitting a pilot signal. Referring to FIG. 3, the transmitter 1 transmits a pilot signal. T M antennas and receiver 3 R is the number of combinations with antennas (M T ×M R ) pilot signals are transmitted by OFDM transmission. T ×M R ) pilot signals are modulated by OFDM modulation.

[0057] FIG. 4 is a timing chart showing the operations of the transmitter 1, the IRS 2, and the receiver 3 when estimating the frequency response of the propagation path.

[0058] 4, the transmitter 1 notifies the IRS 2 of the transmission of the pilot signal. Then, the transmitter 1 transmits the pilot signals x(1), x(1), . . . , x(M T ) are sent sequentially.

[0059] After the period PD_1, the transmitter 1 transmits the signal for periods PD_2 to PD_M.R In each of the pilot signals x(1), x(1), , x(M T ) in sequence. T ×M R ) pilot signals are transmitted.

[0060] IRS2 receives pilot signals x(1), x(1), . . . , x(M T ) are transmitted sequentially, the modes of the N reflection coefficients of the N reflection elements 21 are set to mode Ω(1), and the periods PD_2 to PD_M R In each of the pilot signals x(1), x(1), , x(M T ) are transmitted in sequence, the modes of the N reflection coefficients of the N reflecting elements 21 are set to modes Ω(2) to Ω(N+1), respectively.

[0061] Receiver 3 is in the period PD_1~PD_M R Sent in (M T ×M R ) pilot signals (M T ×M R ) received signals y(t), the estimator 4 in the receiver 3 calculates (M T ×M R ) received signals y(t), a frequency response FQR_0 at time t0 is estimated by a method described later, and the estimated frequency response FQR_0 is used to calculate the frequency response FQR_0 at G times t1 to t G G frequency responses FQR_1 to FQR_G are estimated and the frequency response H D ,D C The estimation of the frequency response H D is the frequency response of the direct link between transmitter 1 and receiver 3, and the frequency response H C is the frequency response of the indirect link between transmitter 1 and receiver 3.

[0062] In an embodiment of the present invention, specific examples of the number of antennas, OFDM symbol length, and number of reflecting elements of transmitter 1 during the training period for estimating the frequency response of the propagation path between transmitter 1 and receiver 3, when the wireless communication system is IEEE802.11n (Wi-Fi), are, for example, the number of antennas (maximum) of transmitter 1 = 4, OFDM symbol length (bandwidth: 20 MHz) = 4 μs, and the number of reflecting elements = 100, respectively.

[0063] In the first embodiment, a method for estimating the frequency response of the propagation path between the transmitter 1 and the receiver 3 will be described.

[0064] [Estimation of the frequency response of the propagation path at time t0 when the received signal y(t) is received] Assuming that there is no fluctuation in the propagation path while observing the received signal y(t) (assuming that the frequency response H does not have (t)), and since beamforming is not performed in transmitter 1, the transmission weight W in transmitter 1 is omitted, the received signal y(t) can be expressed by the following equation.

[0065]

number

[0066] In equation (1), Θ is a matrix indicating N reflection coefficients of N reflecting elements 21, and n(t) represents additive complex white noise.

[0067] The received signal y(t) is T The observed M T By arranging the received signals y(t), the following equation is obtained:

[0068]

number

[0069] Then, in equation (2), multiplying Y(t) by the inverse matrix of X(t) from the right gives the following equation:

[0070]

number

[0071] In the last line of equation (3), H is the frequency response of the direct link H D and the frequency response H in the indirect link C and [H D H C ], and Ω is made up of a matrix in which an identity matrix I and Θ (the reflection coefficient matrix of N reflecting elements 21) are arranged vertically.

[0072] Then, when the modes of the N reflecting elements 21 are switched (that is, when the patterns of the N reflection coefficients of the N reflecting elements 21 are switched), the following equation is obtained.

[0073]

number

[0074] However, in equation (4), t = iM T As a result, t satisfies the relationship between the periods PD_1 to PD_M shown in FIG. R In each of x(1)~x(M T ) represents the timing of transmission, and t=iM T "i" in represents Ω(1) to Ω(N+1) shown in FIG.

[0075] When N+1 G(i)s in equation (4) are observed and N G(i)s are arranged, the following equation is obtained.

[0076]

number

[0077] Then, multiplying g in equation (5) by the inverse matrix of R from the right side gives the following equation:

[0078]

number

[0079] According to equation (5), R is made up of [Ω(1) Ω(N+1)], which is known because it is made up of N+1 modes of reflection coefficients (i.e., patterns of N+1 reflection coefficients) of N reflecting elements 21. Therefore, the inverse matrix of R can be calculated.

[0080] Also, G(t) = Y(t)X in equation (3) -1 g in equation (6) can be calculated using (t), Y(t) is a signal received by the receiver 3 when the pilot signal is received, so it is known, and X(t) is a signal transmitted by the transmitter 1, so it is known. As a result, "gR" in equation (6) can be calculated using -1 " can be calculated.

[0081] Furthermore, in the embodiment of the present invention, it is assumed that "the amount of fluctuation in the propagation path is sufficiently larger than the noise power (the signal-to-noise ratio SN is high)." In this case, "N" in equation (6) can be ignored, and H in equation (6) D ,H C respectively, H D ≒[H D ]^(H D hat) and H C ≒[H C ]^(H C (Hat) in Eq. (6) D ,H C Therefore, in the following, the estimated value of the frequency response H will also be expressed as “H”.

[0082] In this way, "N" in equation (6) can be ignored, so gR -1 and N.R. -1 By calculating the frequency response H D ,H C can be calculated independently. Frequency response H D is the frequency response of the direct link between transmitter 1 and receiver 3, and the frequency response H C is the frequency response of the indirect link between transmitter 1 and receiver 3.

[0083] As a result, using the above-mentioned equations (1) to (6), the frequency response [H D H C ](=FQR_0) can be estimated.

[0084] When receiving the received signal y(t), the estimation means 41 of the estimation device 4 calculates the frequency response [H D H C ] is estimated.

[0085] [Estimation of the frequency response of the propagation path from reception time t0 to future times] M T The transmission symbols of the k-th subcarrier transmitted from all antennas are denoted by x(k)∈C. MT Then, the received signal y(k) is expressed by the following equation:

[0086]

number

[0087] In equation (7), the total number of subcarriers k is K. The delay due to the propagation path is assumed not to exceed the guard interval. Also, H(k)∈C MR×MT is a channel matrix representing the frequency response of the k-th subcarrier, where the rows and columns correspond to the receiving antennas and the transmitting antennas, respectively. Furthermore, n(k) has a mean of 0 and a variance of σ 2 represents additive complex white noise.

[0088] The elements of the channel matrix shown in equation (7) can be decomposed into a direct link component that reaches the receiver 3 directly from the transmitter 1 and an indirect link component that passes through the IRS 2, as shown in the following equation.

[0089]

number

[0090] In equation (8), the first term on the right-hand side corresponds to the direct link, and the second term corresponds to the indirect link via IRS2.

[0091] And h D mR,mT (k) is the mth T mth antenna from the transmitting antenna R represents the frequency response of the kth subcarrier to the receiving antenna, and h IU mR,n (k) is the nth element to the mth element of IRS2 R represents the frequency response of the kth subcarrier to the receiving antenna, and h BI n,mT (k) is the mth T represents the frequency response of the k-th subcarrier from the transmit antenna to the n-th element of IRS2.

[0092] Also, θ n represents the reflection coefficient at the nth element of IRS2. Furthermore, these are collected in vector form, and h IU mR (k)=[h IU mR,1 (k),···,h IU mR,N (k)] T ,h BI mT (k)=[h BI 1,mT (k),···,h BI N,mT (k)] T ,θ=[θ1,···,θ N ] T In this definition, "T" stands for transpose.

[0093] The channel formed by superimposing the channels from transmitter 1 to IRS2 and from IRS2 to receiver 3 is called a cascaded channel, and its frequency response is expressed as h IU mR (k) and h BI mT It is obtained as the Hadamard product of (k) as shown in equation (9).

[0094]

number

[0095] Substituting equation (8) into equation (7) gives the following equation:

[0096]

number

[0097] H in Eq. (10) D (k) is expressed by the following equation:

[0098]

number

[0099] Also, H in Eq. (10) C (k) is expressed by the following equation:

[0100]

number

[0101] Furthermore, Θ in equation (10) is expressed by the following equation:

[0102]

number

[0103] In the embodiment of the present invention, it is assumed that the frequency response of a propagation path can be expressed by a linear combination of P past data (P is an integer equal to or greater than 1) (Non-Patent Document 7). Therefore, the time series of the frequency response matrix of the frequency response of the propagation path is expressed as an AR model (Autoregressive model), i.e., an autoregressive model, as shown in the following equation.

[0104] In the following, only the cascaded channel (the frequency response of the propagation path from the transmitter 1 to the receiver 3 via the IRS 2) will be described, but the same applies to the direct link from the transmitter 1 to the receiver 3.

[0105]

number

[0106] In equation (14), h C mR,mT,n (k,t) is the cascade channel h C mR,mT (k), P is the AR order, t is an index representing time, and ε(t) is a noise term representing the error in fitting the AR model.

[0107] AR coefficient (regression coefficient) a p By calculating (14), it becomes possible to estimate the channel estimation value at a future time (the left side of equation (14)) from the past channel estimation value (the right side of equation (14)). The AR coefficients can be estimated by solving the following Yule-Walker equation.

[0108]

number

[0109] In equation (15), γ^(p) is C mR,mT,n (k) is the sample autocovariance of (k) and is expressed by the following equation: Note that the notation "γ̂(p)" indicates that "̂" is placed above γ, as shown in equation (15).

[0110]

number

[0111] In equation (16), "*" represents a complex conjugate. μ in equation (16) is expressed by the following equation.

[0112]

number

[0113] In equation (17), T is the number of training samples.

[0114] By solving equation (15), the estimated AR coefficient a^ p We obtain "a^ p The notation " indicates that a "^" is placed above a. The estimated value of this AR coefficient a^ p From the past channel estimation values ​​and the channel prediction value at the current time, the channel prediction value can be expressed as follows:

[0115]

number

[0116] Equation (18) represents the predicted value of the channel at the current time for the cascaded channel, but when equations (14), (16), and (17) for the cascaded channel are expressed for the channel in the direct link, they become equations (19), (20), and (21).

[0117]

number

[0118]

number

[0119]

number

[0120] And for the channel in the direct link, the AR coefficient a p When calculating, equations (15), (20), and (21) are used.

[0121] AR coefficient a p By solving for , the predicted value of the channel at the current time for the direct link can be realized as follows:

[0122]

number

[0123] Furthermore, when estimating the frequency response of a propagation path at multiple times (multiple time points) in the future, the predicted value obtained by equation (18) is substituted for the observed value on the right side of equation (18) for the frequency response of the cascaded channel, and estimation by equation (18) is sequentially calculated, thereby making it possible to estimate the frequency response at any future time (future point in time).

[0124] Similarly, for the frequency response of the channel in the direct link, the predicted value obtained by equation (22) is substituted for the observed value on the right side of equation (22), and by sequentially calculating the estimation by equation (22), it is possible to estimate it at any future time (future point in time).

[0125] Therefore, by using equations (18) and (22), it is possible to estimate the frequency response of the propagation path (a propagation path consisting of a direct link and an indirect link) between transmitter 1 and receiver 3 at any time in the future.

[0126] The estimation means 41 of the estimation device 4 uses equations (7) to (22) to estimate the frequency response of the propagation path (a propagation path consisting of a direct link and an indirect link) between the transmitter 1 and the receiver 3 at any point in time in the future.

[0127] [Optimization of the reflection coefficients of the reflecting elements and the transmit weights at transmitter 1] The optimization of the N reflection coefficients θ of the N reflecting elements 21 and the optimization of the transmission weights W in the transmitter 1 will be described.

[0128] The optimization means 42 of the estimation device 4 optimizes the N reflection coefficients θ and the transmission weights W by alternating optimization so that the transmission capacity sum_rate of the signal transmitted by the transmitter 1 is maximized.

[0129] That is, the optimization problem is expressed by the following equation:

[0130]

number

[0131] In equation (23), γ mR is M R is the signal to interference and noise ratio (SINR) of the antenna, which is a function of the reflection coefficient θ and the transmit weight W. Also, ω mR is a parameter that indicates the priority of each receiving antenna. In particular, if no priority is given to the antennas, ω1 = ω2 = = ω MR =1 / M R This can be considered.

[0132] Equation (23) represents the determination of the reflection coefficient θ and the transmission weight W when the right-hand side is maximized.

[0133] The optimization means 42 (I) Reflection coefficient θ n , the propagation path matrix is ​​calculated, and the transmission weight W is obtained by performing eigenvalue decomposition on the calculated propagation path matrix. n Calculate, and (II) The calculated transmission weight W n Calculate the transmission capacity sum_rate_n using That is, n=1~Q N Execute about (III)Q N Transmission capacity sum_rate_1~sum_rate_Q N The reflection coefficient θ when the maximum transmission capacity sum_rate_max is obtained opt and the transmission weight W optwhere Q is the number of possible reflection coefficients for each reflecting element.

[0134] In (I), the optimization means 42 optimizes the frequency response H D (k,t),H C Using (k,t), [H D (k,t)+H C (k,t)Θ]W to calculate the propagation path matrix. In this case, the frequency response H D (k,t),H C (k, t) is estimated by the estimation means 41, and “Θ” is the Q of the N reflecting elements 21. N The optimization means 42 calculates the Q of the N reflecting elements 21. N Q as a pattern of reflection coefficients N Since the codebook including the patterns is shared with the IRS2 in advance, the optimization means 42 can optimize the channel matrix [H D (k,t)+H C (k,t)Θ]W can be calculated.

[0135] Therefore, the optimization means 42 selects one pattern θ consisting of N reflection coefficients from the codebook. n Detect one detected pattern θ n Substituting into "Θ", the propagation path matrix [H D (k,t)+H C (k,t)Θ]W is calculated.

[0136] Then, the optimization means 42 calculates the calculated channel matrix [H D (k,t)+H C The transmission weight W is calculated by performing eigenvalue decomposition on [(k, t)Θ]W.

[0137] In (II), the optimization means 42 calculates M using the transmission weight W calculated in (I). R M antennas R Priority ω for each sending rate mR Multiply by M RThe sum of the multiplication results is calculated to calculate the transmission capacity sum_rate. R M antennas R The transmission rate is expressed as log2(1+γ mR ) is calculated as “γ mR The method for determining " will be described later.

[0138] Furthermore, in (III), if there are a plurality of maximum transmission capacities sum_rate_max, the optimization means 42 extracts any one of the plurality of maximum transmission capacities sum_rate_max and calculates a reflection coefficient θ opt and the transmission weight W opt Determine.

[0139] In (I), the effect of performing eigenvalue decomposition on the channel matrix will be explained.

[0140] FIG. 5 is a diagram for explaining the effect of performing eigenvalue decomposition on a channel matrix.

[0141] The transmitter 1 multiplies (pre-codes) the transmission signal of each antenna by a coefficient matrix based on the information on the propagation path matrix obtained from the estimation device 4, so that the propagation paths of the antenna pair become independent.

[0142] Therefore, the transmitter 1 determines the coefficient matrix by the following equation.

[0143]

number

[0144] In equation (24), matrix T is a transmission weight matrix, which corresponds to the above-mentioned transmission weight W. Furthermore, matrix A is a K×K diagonal matrix, where K is the number of streams, and p1, . . . , p K are the transmission powers allocated to streams 1 to K, respectively.

[0145] When the transmitted signal s is multiplied by the matrices T and A, the received signal y is expressed by the following equation.

[0146]

number

[0147] T to the received signal y H H H Multiplying by gives the following equation:

[0148]

number

[0149] ∧A in the last line of equation (26) is a diagonal matrix. Each diagonal element of ∧A (M R The result of dividing the noise power (or estimated noise power) of each antenna is γ1, γ2, . . . , γ MR Therefore, each diagonal element of ∧A (M R The result of dividing the noise power (or estimated noise power) of each antenna is γ mR Substituting into M R M antennas R Calculate the sending rate of M R M antennas R The transmission capacity sum_rate is calculated using these transmission rates.

[0150] Referring to FIG. 5, when no precoding is performed, a communication path is formed between each transmitting antenna and a receiving antenna, in which communication paths due to a plurality of transmitting antennas are superimposed (see (a) of FIG. 5).

[0151] On the other hand, when precoding is performed, it is possible to form a plurality of independent communication paths between the transmitting antenna and the receiving antenna (see (b) of FIG. 5).

[0152] As a result, by performing eigenvalue decomposition on the channel matrix, in the above (II), the optimization means 42 calculates M using the transmission weight W calculated in (I). R M antennas R Priority ω for each sending rate mR Multiply by M R By calculating the sum of the multiplication results, the transmission capacity sum_rate reaching the antenna of the receiver 3 can be calculated.

[0153] That is, for one receiving antenna, one transmission capacity for one communication path is calculated, and the calculation results are added up for the number of receiving antennas to calculate the transmission capacity sum_rate. As a result, the amount of calculation required to calculate the transmission capacity sum_rate can be reduced.

[0154] Fig. 6 is a flowchart for explaining the operation of the estimation device 4 shown in Fig. 2. Referring to Fig. 6, when the operation of the estimation device 4 starts, the estimation means 41 of the estimation device 4 receives a received signal y(t) of a pilot signal from the communication means 32 of the receiver 3 (step S1).

[0155] Then, the estimation means 41 derives the equation (6) using the equations (1) to (5) based on the received signal y(t) (step S2).

[0156] Then, the estimation means 41 uses the equation (6) to calculate the frequency response H D ,H C is calculated to estimate the frequency response FQR_0 of the propagation path at the time t0 when the received signal y(t) is received (step S3).

[0157] Subsequently, the estimation means 41 calculates the AR coefficient a p_C is calculated (step S4).

[0158] Then, the estimation means 41 calculates the AR coefficient a p_D is calculated (step S5).

[0159] Then, the estimation means 41 calculates the AR coefficient a p_C ,a p_D Using the above, the frequency response FQR_1 is estimated from the frequency response FQR_0 by using equations (18) and (22) (step S6).

[0160] Then, the estimation means 41 sets g=1 (step S7) and calculates the AR coefficient a p_C ,a p_D Using this, at time t g Frequency response FQR_g at time t g A time t in the future g+1 The frequency response FQR_g+1 at is estimated (step S8).

[0161] Then, the estimation means 41 determines whether g=G-1 or not (step S9).

[0162] If it is determined in step S9 that g is not equal to G-1, the estimation means 41 sets g to g+1 (step S10). Thereafter, the operation of the estimation device 4 proceeds to step S8, and steps S8 to S10 are repeatedly executed until it is determined in step S9 that g is equal to G-1.

[0163] Then, when it is determined in step S9 that g=G−1, the estimation means 41 outputs the frequency responses FQR_0 to FQR_G to the optimization means .

[0164] The optimization means 42 receives the frequency responses FQR_0 to FQR_G from the estimation means 41, and optimizes the reflection coefficient Θ and the transmission weight W based on the received frequency responses FQR_0 to FQR_G (step S11).

[0165] Then, the optimization means 42 feeds back the optimized reflection coefficient Θ to the IRS 2 via the communication means 32 of the receiver 3, and feeds back the optimized transmission weight W to the transmitter 1 (step S12). This completes the operation of the estimation device 4.

[0166] In the flowchart shown in FIG. 6, when step S8 is executed for the first time, the estimation means 41 calculates the AR coefficient a p_C ,a p_D Using equations (18) and (22), the frequency response FQR_2 is estimated from the frequency response FQR_1 estimated in step S6.

[0167] Then, when step S8 is executed for the second time, the estimation means 41 estimates the AR coefficient a p_C ,a p_D Using equations (18) and (22), the frequency response FQR_3 is estimated from the frequency response FQR_2.

[0168] Next, when step S8 is executed for the third time, the estimation means 41 estimates the AR coefficient a p_C ,a p_D Using equations (18) and (22), the frequency response FQR_4 is estimated from the frequency response FQR_3.

[0169] Thereafter, in the same manner, when step S8 is executed for the (G-2)th time, the estimation means 41 calculates the AR coefficient a p_C ,a p_D Using equations (18) and (22), the frequency response FQR_G-1 is estimated from the frequency response FQR_G-2.

[0170] Then, when step S8 is executed for the (G-1)th time, the estimation means 41 calculates the AR coefficient a p_C ,a p_D Using equations (18) and (22), the frequency response FQR_G is estimated from the frequency response FQR_G-1.

[0171] Therefore, by executing step S8 (G-1) times, frequency responses FQR_2 to FQR_G can be estimated.

[0172] As a result, according to the flowchart shown in FIG. 6, the frequency response FQR_0 at the time t0 of reception of the received signal y(t) (see step S3) and the frequency response FQR_0 at the time t1 to t2 of reception of the received signal y(t) are compared. GThe frequency responses FQR_1 to FQR_G (see steps S6, S8 to S10) in the waveforms can be estimated.

[0173] Fig. 7 is a flowchart for explaining the detailed operation of step S6 in Fig. 6. Referring to Fig. 7, after step S5 in Fig. 6, the estimation means 41 estimates the frequency response H C 0 and AR coefficient a p_C Substituting this into the right side of equation (18), the frequency response H at time t1 in the future than the reception time t0 is obtained by equation (18). C 1 is estimated (step S61).

[0174] Then, the estimation means 41 estimates the frequency response H D 0 and AR coefficient a p_D Substituting this into the right side of equation (22), the frequency response H at time t1 in the future than the reception time t0 is obtained by equation (22). D 1 is estimated (step S62).

[0175] Then, the estimation means 41 calculates the frequency response H C 1 and frequency response H D 6. Then, the operation of the estimation device 4 proceeds to step S7 in FIG.

[0176] In this way, the estimation means 41 estimates the frequency response H C 0,H D 0 to the frequency response H C 1,H D Estimate 1.

[0177] Fig. 8 is a flowchart for explaining the detailed operation of step S8 in Fig. 6. Referring to Fig. 8, after step S7 or step S10 in Fig. 6, the estimation means 41 estimates the frequency response H C g and AR coefficient a p_C Substituting into the right side of equation (18), we obtain the time tg A time t in the future g+1 Frequency response in H C g+1 is estimated (step S81).

[0178] Then, the estimation means 41 estimates the frequency response H D g and AR coefficient a p_D Substituting into the right side of equation (22), we obtain the time t g A time t in the future g+1 Frequency response in H D g+1 is estimated (step S82).

[0179] Then, the estimation means 41 calculates the frequency response H C g+1 and frequency response H D g+1 At time t g+1 Then, the operation of the estimation device 4 proceeds to step S9 in FIG.

[0180] In this way, the estimation means 41 estimates the frequency response H C g ,H D g Then, the frequency response H C g+1 ,H D g+1 Estimate.

[0181] Then, when g=1, in step S81, the frequency response H of the frequency response FQR_1 is C Frequency response H from 1 to frequency response FQR_2 C 2 is estimated, and in step S82, the frequency response H of the frequency response FQR_1 is calculated. D Frequency response H from 1 to frequency response FQR_2 D 2 is estimated.

[0182] Then, in step S83, the frequency response H C 2 and frequency response H D 2, a frequency response FQR_2 is generated.

[0183] The same applies to g=2 to G-1. As a result, according to the flowchart shown in FIG. C 2 and frequency response H D 2 and the frequency response FQR_2, the frequency response H C 3 and frequency response H D 3 and the frequency response FQR_3, the frequency response H C 4 and frequency response H D 4 and the frequency response FQR_4,..., the frequency response H C G and frequency response H D G A frequency response FQR_G consisting of

[0184] Fig. 9 is a flowchart for explaining the detailed operation of step S11 in Fig. 7. Referring to Fig. 9, when it is determined that g=G-1 in step S9 in Fig. 6, optimization means 42 sets g=0 (step S111) and sets n=1 (step S112).

[0185] Then, the optimization means 42 calculates the reflection coefficient θ n_g is detected, and the detected reflection coefficient θ n_g , the frequency response H estimated by the estimation means 41 D (k,t),H C (k,t), the propagation path matrix [H D (k,t)+H C (k, t)Θ]W_n_g is calculated (step 113).

[0186] Thereafter, the optimization means 42 optimizes the propagation path matrix [H D (k,t)+H C (k,t)Θ]W_n_g and perform eigenvalue decomposition to obtain the transmission weight W n_g is calculated (step S114).

[0187] Subsequently, the optimization means 42 calculates the transmission weights W n_g The transmission capacity sum_rate_n_g is calculated using (step S115).

[0188] Then, the optimization means 42 calculates n=Q N It is determined whether or not this is the case (step S116).

[0189] In step S116, n=Q N If it is determined that n is not the case, the optimization means 42 sets n=n+1 (step S17). After that, the operation of the estimation device 4 proceeds to step S113, and in step S116, n=Q N Steps S113 to S117 are repeatedly executed until it is determined that the above condition is met.

[0190] Then, in step 116, n=Q N If it is determined that Q N Transmission capacity sum_rate_1_g~sum_rate_Q N The reflection coefficient θ when the maximum transmission capacity sum_rate_max_g is obtained among _g opt_g and the transmission weight W opt_g is determined (step S118).

[0191] Thereafter, the optimization means 42 determines whether or not g=G (step S119). If it is determined in step S119 that g=G is not true, the optimization means 42 sets g=g+1 (step S120). Thereafter, the operation of the estimation device 4 proceeds to step S112, and steps S112 to S120 are repeatedly executed until it is determined in step S119 that g=G is true.

[0192] Then, in step S119, if it is determined that g=G, the optimization means 42 performs the optimization G The reflection coefficient θ optimized at opt_0 ~θ opt_G and the transmission weight Wopt_0 ~W opt_G (Step S121). After that, the operation of the estimation device 4 proceeds to Step S12 in FIG.

[0193] In step S121, the optimization means 42 optimizes the reflection coefficient θ opt_0 ~θ opt_G and the transmission weight W opt_0 ~W opt_G , in step S12 of FIG. 6, the transmission weight W opt_0 ~W opt_G are respectively at time t0 to t G and feeds it back to the transmitter 1 in correspondence with the reflection coefficient θ opt_0 ~θ opt_G are respectively at time t0 to t G and feeds it back to IRS2.

[0194] [Table 1]

[0195] [Table 2]

[0196] According to the flowchart shown in FIG. 6 (including the flowcharts shown in FIGS. 7 to 9), the estimation device 4 estimates the frequency response FQR_0 of the propagation path at the time t0 of reception of the received signal y(t) based on the received signal y(t) (see steps S2 and S3), estimates the frequency response FQR_1 of the propagation path at a time t1 that is later than the time t0 of reception from the frequency response FQR_0 of the propagation path (see step S6), estimates the frequency response FQR_2 of the propagation path from the frequency response FQR_1 of the propagation path, estimates the frequency response FQR_3 of the propagation path from the frequency response FQR_2 of the propagation path, estimates the frequency response FQR_4 of the propagation path from the frequency response FQR_3 of the propagation path, ...and similarly estimates the frequency response FQR_G of the propagation path from the frequency response FQR_G-1 of the propagation path (see steps S8 to S10).

[0197] In steps S8 to S10, the estimation device 4 uses the frequency response FQR_1 of the propagation path as an initial value and calculates the frequency response FQR_1 between two adjacent time points t g ,t g+1 At time t g Frequency response FQR_g at time t g+1 The frequency response FQR_g+1 at time t2 to t3 is estimated repeatedly using equations (18) and (22). G The frequency responses FQR_2 to FQR_G are estimated.

[0198] Therefore, from time t1 to t G When a signal is transmitted, the deviation due to the lag between the estimated time of the propagation path between the transmitter 1 and the receiver 3 and the transmission time can be suppressed by setting the time at the time of transmission.

[0199] According to the flowchart shown in FIG. 6 (including the flowcharts shown in FIGS. 7 to 9), the estimation device 4 estimates the frequency response FQR_0 at the time of reception t0 based on the received signal y(t) by adding the frequency response FQR_0 at the time of reception t0 to the frequency response FQR_0 at the time of reception t1 to t2. G The estimated frequency responses FQR_1 to FQR_G are added to optimize the reflection coefficients Θ and the transmission weights W.

[0200] The estimation device 4 then calculates the optimized transmission weights W opt_0 ~W opt_G are respectively at time t0 to t G and feeds back to the transmitter 1 the optimized reflection coefficient θ opt_0 ~θ opt_G are respectively at time t0 to t G The data is fed back to IRS2 in association with the above (see Table 2).

[0201] Therefore, the transmitter 1 uses the fed back transmit weight W opt_0 ~W opt_G and IRS2 transmits a signal using the feedback reflection coefficient θ opt_0 ~θ opt_GSince the transmitted signal from the transmitter 1 is reflected by the reflection, the signal can be transmitted to the receiver 3 using a propagation path (frequency response) in which the deviation from the estimated propagation path (frequency response) is suppressed.

[0202] FIG. 10 is a diagram illustrating a comparison between the conventional relationship between the estimated time and the current time and the relationship between the estimated time and the current time according to the first embodiment.

[0203] Referring to (a) of FIG. 10, in the past, the frequency response of the propagation path was estimated using information up to the estimated time, and the reflection coefficient θ and the transmission weight W were optimized using the estimated frequency response. Therefore, there was a delay between the estimated time and the current time due to the estimation process, optimization process, and feedback of the optimized reflection coefficient θ and transmission weight W.

[0204] On the other hand, in the first embodiment, as shown in FIG. 10(b), the frequency response FQR_0 at the time of reception t0 is estimated based on the received signal y(t) at the conventional estimation time, and the estimated frequency response FQR_0 is used to calculate the frequency response FQR_0 at times t1 to t2 in the future from the time of reception t0. G The frequency responses FQR_1 to FQR_G in are estimated sequentially using equations (18) and (22), and the estimated frequency responses FQR_0 to FQR_G are used to optimize the reflection coefficient θ and the transmission weight W, so that the reflection coefficient θ and the transmission weight W can be optimized using the information up to the current time.

[0205] As a result, it is possible to suppress the discrepancy due to the lag between the estimated time of the propagation path between the transmitter and receiver and the transmission time.

[0206] In the first embodiment, the operation of the estimation device 4 may be realized by software. In this case, the estimation device 4 includes a CPU (Central Processing Unit), a ROM (Read Only Memory), and a RAM (Random Access Memory). The ROM stores a program Prog_A consisting of the steps of the flowchart shown in FIG. 6 (including the flowcharts shown in FIGS. 7 to 9).

[0207] The CPU reads the program Prog_A from the ROM, executes the read program Prog_A, and executes the program Prog_A from time t0 to time t G The frequency responses FQR_0 to FQR_G at time t0 to t are estimated, and the frequency responses FQR_0 to FQR_G are used to estimate the frequency responses FQR_0 to FQR_G at time t0 to t G The RAM optimizes the transmission weights W and reflection coefficients θ of the N reflecting elements 21 and feeds back the optimized transmission weights W and reflection coefficients θ to the transmitter 1 and the IRS 2, respectively. N A codebook containing patterns of reflection coefficients is temporarily stored.

[0208] Furthermore, the program Prog_A may be recorded on a recording medium such as a CD or DVD and distributed. When the recording medium on which the program Prog_A is recorded is inserted into a computer, the computer reads and executes the program Prog_A from the recording medium, and executes the program Prog_A from time t0 to time t G The frequency responses FQR_0 to FQR_G at time t0 to t are estimated, and the frequency responses FQR_0 to FQR_G are used to estimate the frequency responses FQR_0 to FQR_G at time t0 to t G The transmit weight W and the reflection coefficient θ in the IRS 1 are optimized, and the optimized transmit weight W and the reflection coefficient θ are fed back to the transmitter 1 and the IRS 2, respectively.

[0209] Therefore, the recording medium on which the program Prog_A is recorded is a computer-readable recording medium.

[0210] When the number of antennas in the transmitter 1 is small, the indirect links that pass through several adjacent reflecting elements will have the same propagation path value. Therefore, by classifying reflecting elements with the same propagation path value into clusters and performing the same control on the reflecting elements in each cluster, the overhead of propagation path estimation can be reduced.

[0211] When estimating a propagation path in combination with clustering, estimation is only required for the representative reflecting element of each cluster.

[0212] Therefore, the amount of calculation required for estimation can be reduced.

[0213] When clustering N reflecting elements 21, the N reflecting elements 21 are classified into c (c is an integer equal to or greater than 1) clusters, each of which has the same frequency response of the propagation path. Then, c representative reflecting elements are selected from the c clusters. In this case, for example, among the reflecting elements included in one cluster, a reflecting element whose arrangement position is the center of the arrangement positions of the reflecting elements is selected as the representative reflecting element.

[0214] The reflective elements included in each of the c clusters are controlled so that they have the same reflective characteristics.

[0215] [Embodiment 2] Fig. 11 is a schematic diagram of a wireless communication system according to embodiment 2. Referring to Fig. 11, wireless communication system 10A according to embodiment 2 is the same as wireless communication system 10, except that IRS 2 of wireless communication system 10 shown in Fig. 1 is replaced with IRS 2A and receiver 3 is replaced with receiver 3A.

[0216] The transmitter 1, the IRS 2A, and the receiver 3A are arranged in a wireless communication space. The transmitter 1, the IRS 2A, and the receiver 3A are arranged non-linearly in the wireless communication space, similar to the transmitter 1, the IRS 2, and the receiver 3 in the first embodiment.

[0217] The IRS2A is the same as the IRS2 except that the IRS controller 22 of the IRS2 shown in FIG. 1 is replaced with an IRS controller 22A.

[0218] The receiver 3A is the same as the receiver 3 shown in FIG. 1 except that the estimation device 4 of the receiver 3 is replaced with an estimation device 4A.

[0219] When the estimator 4A of the receiver 3 estimates the frequency response of the propagation path between the transmitter 1 and the receiver 3A, the IRS controller 22A estimates the frequency response of (N+1)M TThe reflection pattern caused by N reflecting elements 21 when pilot signals are sequentially transmitted from the transmitter 1 is expressed as (N+1)M T The N reflecting elements 21 are controlled to switch sequentially among the patterns.

[0220] At this time, the IRS controller 22A controls the one reflective element to be turned "ON" so that only one reflective element out of the N reflective elements is turned "ON" and the other (N-1) reflective elements are turned "OFF" so that the one reflective element to be turned "ON" is switched sequentially in a predetermined order.

[0221] When receiving a received signal y(t) of one pilot signal from the communication means 32, the estimation device 4A of the receiver 3A calculates a frequency response matrix [H D H C ], and receives a received signal y(t+1) of another pilot signal from the communication means 32, the frequency response matrix [H D H C ], we estimate a column CLM_c+1 adjacent to a column CLM_c, and T Pilot signals y(1) to y((N+1)M T ) and calculate the frequency response matrix [H D H C ] is estimated.

[0222] Then, the estimation device 4A calculates (N+1)M T Pilot signals y(1) to y((N+1)M T ) based on the frequency response matrix [H D H C ] is estimated, the frequency response matrix [H D H C ] to obtain a complete frequency response matrix [H D H C ] is estimated as the frequency response FQR_0 at time t0.

[0223] Thereafter, the estimation device 4A, like the estimation device 4 in the first embodiment, calculates the frequency response FQR_0 from time t1 to time t G The frequency responses FQR_1 to FQR_G at

[0224] Then, like the estimation device 4 in embodiment 1, the estimation device 4A optimizes the reflection coefficient θ and the transmission weight W using the estimated frequency responses FQR_0 to FQR_G, feeds back the optimized transmission weight W to the transmitter 1, and feeds back the optimized reflection coefficient θ to the IRS2A.

[0225] Fig. 12 is a schematic diagram of receiver 3A shown in Fig. 11. Referring to Fig. 12, receiver 3A is the same as receiver 3 except that estimation device 4 of receiver 3 shown in Fig. 2 is replaced with estimation device 4A.

[0226] The estimation device 4A is the same as the estimation device 4 except that the estimation means 41 of the estimation device 4 shown in FIG.

[0227] The estimation means 41A estimates the frequency response FQR_0 of the propagation path at the time t0 of reception of the received signal y(t) by a method to be described later. Then, the estimation means 41A uses the estimated frequency response FQR_0 to estimate the frequency response FQR_0 from time t1 to time t2 in the future from the time t0 of reception. G The estimation means 41A estimates frequency responses FQR_1 to FQR_G in the frequency domain by the same method as the estimation means 41. Thereafter, the estimation means 41A outputs the estimated frequency responses FQR_0 to FQR_G to the optimization means .

[0228] [Estimation of the frequency response of the propagation path at time t0 when the received signal y(t) is received] To take into account the fluctuations in the propagation path during the training period, which is the period for estimating the frequency response of the propagation path, and during the data transmission period, we employ estimation by ON / OFF switching of N reflecting elements 21, which can estimate each column of the propagation path matrix H(t) at OFDM symbol intervals (Non-Patent Document 8). When a reflecting element is turned off, the reflection coefficient of the turned-off reflecting element can be set to "0".

[0229] FIG. 13 is a conceptual diagram showing a matrix representation of the received signal, frequency response, transmitted signal, and white noise.

[0230] Referring to Figure 13, the received signal y(t) is expressed by Equation (Eq). In Equation (Eq), the matrix H(t) is the frequency response matrix H D (t) and the frequency response matrix H of the indirect link C (t), and the matrix g(t) is the product of the reflection coefficient matrix Θ and the transmitted signal matrix x(t).

[0231] And the matrix H(t) is M R row(N+1)M T The matrix g(t) is a column matrix, and the matrix g(t) is T matrix with 1 row and 1 column, and the matrix n(t) is M R It is a matrix with 1 row and 1 column.

[0232] 14 is a conceptual diagram showing the state of the matrix when the reflecting elements are switched ON / OFF. Referring to FIG. 14, when transmitter 1 transmits a pilot signal using one antenna and turns all N reflecting elements 21 OFF (=0), the elements in the first row of matrix g(t) become "1" (see the hatching in matrix g(t)), and the elements in the second row to the (N+1)th row become "1" (see the hatching in matrix g(t)). T The element in the th row is "0".

[0233] As a result, the received signal y(t) is the sum of a matrix H(t) consisting of the elements in the first column and a matrix n(t) representing white noise. When the signal-to-noise ratio (SN) is high, the influence of white noise is small and can be ignored. Therefore, when all reflecting elements are turned off (=0) and a pilot signal is transmitted from one antenna of the transmitter 1, the estimation means 41A estimates the elements in the first column of the matrix H(t) by receiving the received signal y(t) via the antenna 31 and the communication means 32. Because the transmitter 1 transmits a pilot signal using one antenna and the IRS2A reflects the pilot signal with one reflecting element, the path from the transmitter 1 to the IRS2 to the receiver 3A consists of one path, the matrix H(t) consists of one column element, and one column element of the matrix H(t) corresponds to one antenna of the transmitter 1.

[0234] In IRS2A, by switching one reflective element to ON (=1) in a predetermined order, the elements of the second column to the (N+1)Mth column of the matrix H(t) are T The elements of the column can be estimated sequentially.

[0235] In the second embodiment, the transmitter 1 transmits pilot signals using one antenna at intervals of an OFDM symbol length (for example, 4 μs).

[0236] FIG. 15 is a conceptual diagram showing the transition of the matrices H(t) and g(t) during the training period.

[0237] Referring to FIG. 15, at t=1, the elements of the first row of the matrix g(t) become “1” (see the hatching of the matrix g(t)), and the elements of the second row to the (N+1)Mth row of the matrix g(t) become “1” (see the hatching of the matrix g(t)). T When the elements of the rows become "0", the estimation means 41A estimates the elements of the first column of the matrix H(t) by receiving a pilot signal transmitted from one antenna of the transmitter 1.

[0238] Then, at t=2, when the elements of the second row of the matrix g(t) become “1” (see the hatching of the matrix g(t)) and the elements of the rows other than the second row become “0”, the estimation means 41A estimates the elements of the second column of the matrix H(t) by receiving a pilot signal transmitted from one antenna of the transmitter 1.

[0239] Similarly, t=M T In this case, the Mth T The elements of the row become "1" (see the hatching of the matrix g(t)), and the Mth T When the elements of rows other than the row become "0", the estimation means 41A receives a pilot signal transmitted from one antenna of the transmitter 1 and estimates the M-th element of the matrix H(t). T Estimate the elements of a column.

[0240] Next, t=M T +1~2M T In the matrix g(t), the first and second rows of T +1) line~Mth T Row and 2nd M T The elements of the rows become "1" sequentially (see the hatching of the matrix g(t)), and the first row and the (M T +1) line~Mth T Row and 2nd M T When the elements other than the row become "0" sequentially, the estimation means 41A calculates the superposition elements H 1,MT+1 ,H 2,MT+2 ,···,H MT,2MT Estimate.

[0241] Superposition element H 1,MT+1 is the first column element of the matrix H(t) and the (M T +1) element and the overlap element H 2,MT+2 is the second column element of the matrix H(t) and the (M T +2) column is an overlapping element, and similarly, the overlapping element H MT,2MT is the Mth element of the matrix H(t). T Column elements and the second M T The elements of the columns and the elements of the columns are overlapping elements.

[0242] Then, the estimation means 41 calculates the superposition element H1 of the first column that has already been estimated. 1,MT+1 Subtract from the Mth T Element H in the +1st column MT+1 and the already estimated element H2 of the second column is superimposed on the element H 2,MT+2 Subtract from the Mth T +Element H in column 2 MT+2 Similarly, the Mth T Column element H MT The superposition element H MT,2MT Subtract from the second M T Column element H 2MT Estimate.

[0243] Then, in the same way, t=NM T +1~(N+1)M T In each case, the (NM T +1) line~(N+1)M T The elements of the rows become "1" sequentially (see the hatching of the matrix g(t)), and T +1) line~(N+1)M T When the elements other than the row become "0" sequentially, the estimation means 41A calculates the superposition elements H 1,NMT+1 ,H 2,NMT+2 ,···,H MT,(N+1)MT Estimate.

[0244] Superposition element H 1,NMT+1 is the first column element of the matrix H(t) and the (NM T +1) element and the overlap element H 2,NMT+2 is the element of the second column of the matrix H(t) and the (NM T +2) column is an overlapping element, and similarly, the overlapping element H MT,(N+1)MT is the Mth element of the matrix H(t). T The elements of the column and the (N+1)Mth T The elements of the columns and the elements of the columns are overlapping elements.

[0245] Then, the estimation means 41 calculates the overlapping element H1 of the first column that has already been estimated. 1,NMT+1 Subtract from the NMT Element H in the +1st column NMT+1 and the already estimated element H2 of the second column is superimposed on the element H 2,NMT+2 Subtract from the NM T +Element H in column 2 NMT+2 Similarly, the Mth T Column element H MT The superposition element H MT,(N+1)MT Subtract from the (N+1)Mth T Column element H (N+1)MT Estimate.

[0246] Fig. 16 is a conceptual diagram showing the components of matrix g(t). Referring to Fig. 16, matrix g(t) is made up of a unit matrix I and a reflection coefficient matrix Θ arranged vertically, [I^T Θ^T]^T.

[0247] The identity matrix I is a matrix whose diagonal elements are 1. The reflection coefficient matrix Θ is a matrix whose diagonal elements are reflection coefficients θ.

[0248] In Figure 15, t=M T +1~(N+1)M T In the above equation, two elements of the matrix g(t) are "1", and the reason for this is as follows.

[0249] t=1 to M shown in Figure 15 T In this case, the elements of the matrix g(t) that are "1" are the first to M T As a result, the elements of the matrix g(t) that become "1" are switched sequentially along the diagonal elements of the unit matrix I shown in FIG.

[0250] And, t=M shown in Figure 15 T +1~(N+1)M T In this case, the elements of the matrix g(t) that become "1" are the first and second columns of T +1) column elements]~[Mth T Column and (N+1)Mth T column] element.

[0251] The identity matrix I shown in Figure 16 is MT Row M T Since it is a column matrix, t=M as shown in Figure 15 T +1~(N+1)M T In this case, the elements of the matrix g(t) that become "1" are switched sequentially along the diagonal elements of the reflection coefficient matrix Θ shown in FIG.

[0252] As a result, t=M T In +1, if the element θ (reflection coefficient element) in the first row and first column of the reflection coefficient matrix Θ is set to "1", then there is a "1" in the unit matrix I in the same first column. And since the "1" in the unit matrix I cannot be controlled by IRS2A, T +1, the elements of the first column of the matrix g(t) and the T +1)th element of column t becomes "1". T +2~(N+1)M T For the same reason, two elements of the matrix g(t) become "1".

[0253] Therefore, the estimation means 41A calculates t=M T +1~(N+1)M T From the estimated values ​​at t=1~M, T In this case, subtract the estimated value and use the subtraction result as t=M T +1~(N+1)M T It is estimated as an estimate at .

[0254] FIG. 17 is a diagram for explaining a problem that occurs when estimating the matrix H(t) of the frequency response of the propagation path by the method shown in FIG.

[0255] 17, when the matrix H(t) is estimated by the method shown in FIG. 15, the acquisition time of the estimated value EST_1_1 of the propagation path in the first column of the matrix H(t) is the (N+1)Mth of the matrix H(t) in the training period TRN_1. T Estimated propagation path of the sequence EST_(N+1)M TUnlike the acquisition time of _1, the acquisition time of the propagation path estimate EST_1_2 in the first column of the matrix (t) in the training period TRN_2 is the (N+1)Mth of the matrix (t). T Estimated propagation path of the sequence EST_(N+1)M T This is different from the acquisition time of _2 (see (a) of Figure 17).

[0256] Furthermore, when using a method that does not always use all transmit antennas, such as index modulation, there are situations where estimates cannot be obtained for specific OFDM symbols or radio frames. Index modulation is a modulation method that assigns information to the selection pattern when selecting a specific element from an arbitrary set and transmits it.

[0257] In the second embodiment, the transmitter 1 is T When one antenna is selected from the antennas and one pilot signal is transmitted using the selected antenna, T The antenna patterns of the (N+1)M antennas can be changed by changing one antenna used to transmit the pilot signal. T Change it to (N+1)M antenna patterns T The pilot signals are transmitted sequentially.

[0258] As a result, (N+1)M T Each of the pilot signals is T Only one of the antennas will be assigned to the antenna pattern used to transmit the pilot signal.

[0259] Therefore, transmitter 1 can obtain (N+1)M T The pilot signals are transmitted sequentially.

[0260] Then, in the training period TRN_1, t=1~(N+1)M T Even if an estimate is obtained at t=(N+1)M in the training period TRN_2, TIn other words, elements of the matrix H(t) estimated by the method shown in FIG. 15 may be missing.

[0261] Therefore, matrix interpolation is applied to the matrix H(t) estimated by the method shown in Fig. 15. Since the missing elements in the matrix H(t) are random, a method is adopted in which the entire matrix H(t) is estimated from randomly missing time series data.

[0262] Note that index modulation is M T Only one antenna among the antennas is used to transmit a pilot signal, and antennas other than the one antenna are not used to transmit a pilot signal. T The aim is to assign pilot signals to the antenna patterns of the antennas and transmit them.

[0263] FIG. 18 is a diagram for explaining a method for extracting elements of the estimated matrix H(t). Referring to FIG. 18, in the time series data D_chr, the estimated values ​​of the matrix H(t) are indicated by black circles (●). Among the data indicated by black circles (●), the data for t=M T +1~(N+1)M T The data estimated at time 1 is composed of the subtraction result obtained by subtracting the overlapped elements, as described above.

[0264] The estimation means 41A moves the sliding window in the direction of the arrow and extracts a part of data from the time series data D_chr using the sliding window for each t shown in FIG. 15 (t=1 to (N+1)M). T , and then extract (N+1)M T Generate a Hankel matrix R by stacking row vectors.

[0265] 19 is a conceptual diagram showing matrix decomposition. Referring to FIG. 19, the estimation means 41A decomposes the generated Hankel matrix R into a product PQ of a matrix P and a matrix Q.

[0266] If a matrix has low rank, it can be expressed as the product of two low-rank matrices, where, for example, the rank of a matrix is ​​1 / 10 of the smaller of the number of rows and the number of columns of the matrix.

[0267] element R of the Hankel matrix R i,j is the element P of matrix P i,: and element Q of matrix Q :,k Here, the notation "P i,: " represents the i-th row of the matrix P, and the notation "Q :,k ” represents the kth column of the matrix Q.

[0268] Then, the optimization problem shown in equation (27) is set.

[0269]

number

[0270] In equation (27A), J1(P,Q) is expressed by equation (27B), and J2(P,Q) is expressed by equation (27C). λ is a regularization parameter, for example, 10 -3 is.

[0271] λJ2(P,Q) is a regularization term to prevent overfitting. Also, on the right side of equation (27B), |R i,j -P i,: Q :,k is the error term for each element, and "Ψ" is the set of indices of known points. Furthermore, on the right side of equation (27C), "2" is the norm constraint, and "F" is the Frobenius norm, which indicates that all elements are squared and added together, and the square root of the sum is calculated.

[0272] The optimization shown in equation (27A) determines P and Q that minimize the error.

[0273] Fig. 20 shows the optimization algorithm. First, R(0), Ψ, L, λ, t max is set.

[0274] Then, in "2: to 4:", the initial values ​​of matrices P and Q are given by singular value decomposition. Also, in "7: to 12:", each row of matrix Q is updated. Furthermore, in "13: to 18:", each row of matrix P is updated. Furthermore, in "20: to 21:", matrix R is updated.

[0275] Furthermore, "11:" corresponds to performing interpolation in matrix Q, and "17:" corresponds to performing interpolation in matrix P.

[0276] And the above "update each row of matrix Q", "update each row of matrix P" and "update matrix R" are performed in t <t max When t=t, it is executed repeatedly. max The optimization algorithm terminates when t max is, for example, 200.

[0277] 21 is a diagram showing a selection matrix. Referring to FIG. 21, the selection matrix S k has one "1" in each row and the rest are "0". If matrix R contains four known parts, the selection matrix S k extracts only the four known parts of the kth column of the matrix R.

[0278] Selection matrix S k In the extraction of the known part using the above, the known part is extracted from the matrix P in "9:" of FIG. 20, and the extracted part is P part Then, in “10:”, the selection matrix S k The known part is extracted from the kth column of the matrix R using the above formula, and the extracted known part is defined as x. Then, in "11:", the rows of the matrix Q are updated.

[0279] The same applies to the selection matrix S i is used in "15:", "16:", and "17:".

[0280] Therefore, matrix interpolation is performed using the optimization algorithm shown in FIG.

[0281] FIG. 22 is a diagram for explaining a method for restoring a time series from an interpolated Hankel matrix R.

[0282] Referring to FIG. 22, the missing Hankel matrix R estimated by matrix interpolation is * The average of the multiple estimated values ​​contained in the diagonal element EL_1 of (t) is calculated, and the average of the calculated estimated values ​​is restored as the interpolated time series data, which is called the Hankel matrix H * This is performed for all of the anti-diagonal elements EL_1 to EL_V of (t), thereby restoring the interpolated time series.

[0283] Since each of the anti-diagonal elements EL_1 to EL_V is made up of elements at the same time point, the average value can be restored as an element at one time point in the time series.

[0284] The estimation means 41A estimates the (N+1)M T Receive the received signals of the pilot signals and calculate the matrix H(t) of (N+1)M T A matrix H(t) is estimated by estimating the number of columns, a Hankel matrix R is generated from the estimated matrix H(t), the generated Hankel matrix R is decomposed into a product PQ of matrices P and Q, and matrix interpolation is performed based on the decomposed product PQ to generate a Hankel matrix R with no missing elements. * (t) and obtain the Hankel matrix R * (t) is used to reconstruct the time series using the frequency response matrix H * It is estimated as (t).

[0285] Then, the estimation means 41A calculates the matrix H * (t), the estimated frequency response matrix H *(t) is the frequency response FQR_0 of the propagation path at the time of reception t0, and using the frequency response FQR_0, the following is calculated from time t1 to time t2 in the future from the time of reception t0 by the same method as the estimation means 41. G The frequency responses FQR_1 to FQR_G at the respective points are estimated, and the frequency responses FQR_0 to FQR_G are output to the optimization means 42.

[0286] Fig. 23 is a flowchart for explaining the operation of the estimation device 4A shown in Fig. 12. The flowchart shown in Fig. 23 is the same as the flowchart shown in Fig. 6, except that steps S1 to S3 of the flowchart shown in Fig. 6 are replaced with steps S21 to S23.

[0287] Referring to FIG. 23, when the operation of the estimation device 4A is started, the estimation means 41A of the estimation device 4A calculates the M T The antenna patterns of the antennas are (N+1)M T Sequentially change to (N+1)M antenna patterns T When pilot signals are transmitted sequentially, (N+1)M T (N+1)M of pilot signals T By sequentially receiving received signals from the communication means 32 of the receiver 3A, (N+1)M of the frequency response matrix H(t) indicating the frequency response of the propagation path between the transmitter 1 and the receiver 3A are obtained. T columns are estimated sequentially (step S21).

[0288] Then, the estimation means 41A generates a Hankel matrix R from the frequency response matrix H(t) by the above-mentioned method (step S22). After that, the estimation means 41A decomposes the Hankel matrix R into a product PQ of matrices P and Q, and performs matrix interpolation using the decomposed product PQ to obtain the Hankel matrix R after matrix interpolation. * The restored time series is converted into a frequency response matrix H * (t) and the frequency response matrix H * (t) is estimated as the frequency response FQR_0 at the time of reception t0 (step S23).

[0289] Thereafter, the estimation means 41A sequentially executes the above-mentioned steps S4 to S10, and the optimization means 42 sequentially executes the above-mentioned steps S11 and S12, thereby completing the operation of the estimation device 4A.

[0290] Fig. 24 is a flowchart for explaining the detailed operation of step S21 in Fig. 23. Referring to Fig. 23, when the operation of the estimation device 4A starts, the estimation means 41A of the estimation device 4A sets t=1 (step S211).

[0291] Then, the estimation means 41A receives one received signal r_t from the communication means 32 of the receiver 3A and estimates the element h_t of the t-th column of the frequency response matrix H(t) (step S212).

[0292] Thereafter, the estimation means 41A estimates whether t≧M T It is determined whether or not the value is +1 (step S213).

[0293] In step S213, t≧M T If it is determined that t is not +1, the estimation means 41A sets t=t+1 (step S214). After that, the operation of the estimation device 4A proceeds to step S212, and in step S213, it is determined whether t≧M T Steps S212 to S214 are repeatedly executed until it is determined that the value is +1.

[0294] Then, in step S213, t≧M T +1, the estimation means 41A calculates q=mod(t,M T ) is calculated (step S215). Here, q is calculated by dividing "t" into "M T " is the remainder when divided by ".

[0295] Thereafter, the estimation means 41A determines whether q=0 (step S216). If it is determined in step S216 that q=0 is not true, the estimation means 41A obtains an estimated value h_q of the qth column from the estimated values ​​already estimated, subtracts the estimated value h_q of the qth column from the superposition element h_sip_t of the tth column, and estimates the subtraction result as the element h_t of the tth column (step S217).

[0296] On the other hand, when it is determined in step S216 that q=0, the estimation means 41A calculates the Mth value from the already estimated values. T Column estimate h_M T and calculate the convolution element h_sip_t of the t-th column to the M-th T Column estimate h_M T and estimates the subtraction result as the element h_t of the t-th column (step S218).

[0297] After step S217 or step S218, the estimation means 41A calculates the time t=(N+1)M T It is determined whether or not this is the case (step S219).

[0298] In step S219, t=(N+1)M T If it is determined that t is not the case, the estimation means 41A sets t=t+1 (step S220). After that, the operation of the estimation device 4A proceeds to step S212, and in step S219, t=(N+1)M T Until it is determined that the answer is "YES" in steps S212 and S213, and steps S215 to S220 are repeatedly executed.

[0299] Then, in step S219, t=(N+1)M T If it is determined that this is the case, the operation of the estimating device 4A proceeds to step S22 in FIG.

[0300] In the flowchart shown in FIG. 24, t=1 to M T If so, steps S212, S213 (NO), and S214 are repeatedly executed. In step S212, the first to Mth columns of the frequency response matrix H(t) areT Column elements h_1~h_M T is estimated (t=1 to M in Fig. 15). T reference).

[0301] And t ≥ M T If +1, in step S212, the estimated element h_t of the t-th column is made up of a superimposed element in which two elements are superimposed.

[0302] Therefore, in step S213, t≧M T When it is determined that the value is +1, q=mod(t,M T ) is calculated, and when q is not 0, that is, when q is 1 to M T -1, t=M T +1 is the Mth T The element h_q in the q (=1) column is subtracted from the overlap element h_sip_t in the +1 column, and the subtraction result is estimated as the element h_t in the t column (see step S217). T +2~2M T If it is -1, the element h_t of the t-th column is estimated in the same way.

[0303] Also, in Figure 15, t=NM T +1~(N+1)M T If it is -1, the element h_t of the t-th column is estimated in the same way.

[0304] On the other hand, when q=0, t=2M T The second M T From the overlap element h_sip_t of the column to the qth (=M T ) element h_q(=M T ) and estimate the subtraction result as the element h_t of the t-th column (see step S218). T Similarly, when the element h_t of the t-th column is estimated, the element h_t of the t-th column is estimated.

[0305] This results in t=M in Figure 15. T +1~(N+1)M T The result of subtracting the superimposed estimated value is T +1st column~(N+1)MT It can be estimated as an element of the column.

[0306] FIG. 25 is a flowchart for explaining the detailed operation of step S23 in FIG.

[0307] 25, after step S22 in Fig. 23, the estimation means 41A performs singular value decomposition (svd(R)) on the Hankel matrix R to decompose it into a product PQ of matrices P and Q, and provides initial values ​​for the matrices P and Q (step S231). More specifically, the estimation means 41A sequentially executes "2:" to "4:" in Fig. 20 to provide initial values ​​for the matrices P and Q.

[0308] Then, the estimation means 41A calculates t up = 0 (step S232). up is an index indicating the number of times to update matrices P, Q, and R, and 1≦t up ≦t up max are integers that satisfy the following. up max is the maximum number of times that matrices P, Q, and R are updated.

[0309] After step S232, the estimation means 41A sequentially executes “7:” to “12:” in FIG. 20 to update the matrix Q (step S233), sequentially executes “13:” to “18:” in FIG. 20 to update the matrix P (step S234), and sequentially executes “20:” to “21:” in FIG. 20 to update the Hankel matrix R (step S235).

[0310] Subsequently, the estimation means 41A calculates t up =t up +1 (step S236). Then, the estimation means 41A sets t up <t up max It is determined whether or not this is the case (step S237).

[0311] In step S237, t up <t up maxWhen it is determined that t up <t up max Steps S233 to S237 are repeatedly executed until it is determined that the condition is not met.

[0312] Then, in step S237, t up <t up max If it is determined that the matrix is ​​not, the estimation means 41A calculates the Hankel matrix R after matrix interpolation by the above-mentioned method. * are restored in time series (step S238).

[0313] Then, the estimation means 41A converts the restored time series into a frequency response matrix H * (t) (step S239), and the frequency response matrix H * (t) is estimated as the frequency response FQR_0 at the time of reception t0 (step S240). After that, the operation of the estimation device 4A proceeds to step S4 in FIG.

[0314] According to the flowchart shown in FIG. 23 (including the flowcharts shown in FIGS. 7 to 9 and the flowcharts shown in FIGS. 24 and 25), the estimation device 4A estimates the M T The antenna patterns of the antennas are (N+1)M T Sequentially change to (N+1)M antenna patterns T When pilot signals are transmitted sequentially, (N+1)M T (N+1)M of pilot signals T By sequentially receiving received signals from the communication means 32 of the receiver 3A, (N+1)M of the frequency response matrix H(t) indicating the frequency response of the propagation path between the transmitter 1 and the receiver 3A are obtained. Tcolumns sequentially (see step S21), matrix interpolation is performed on the frequency response matrix H(t) to estimate the frequency response FQR_0 of the propagation path at the time of reception t0 (see step S23), the frequency response FQR_1 of the propagation path at a time t1 later than the time of reception t0 is estimated from the frequency response FQR_0 of the propagation path (see step S6), the frequency response FQR_2 of the propagation path is estimated from the frequency response FQR_1 of the propagation path, the frequency response FQR_3 of the propagation path is estimated from the frequency response FQR_2 of the propagation path, the frequency response FQR_4 of the propagation path is estimated from the frequency response FQR_3 of the propagation path, ...and similarly, the frequency response FQR_G of the propagation path is estimated from the frequency response FQR_G-1 of the propagation path (see steps S8 to S10).

[0315] Then, the estimation device 4A calculates the time t g Frequency response FQR_g at time t g+1 The frequency response FQR_g+1 at time t2 to t3 is estimated by using equations (18) and (22) repeatedly. G Then, frequency responses FQR_2 to FQR_G in the following order are estimated (see steps S8 to S10).

[0316] Therefore, from time t1 to t G When a signal is transmitted, it is possible to suppress the discrepancy due to the lag between the estimated time of the propagation path between the transmitter 1 and the receiver 3A and the transmission time.

[0317] Furthermore, the estimation device 4A estimates the frequency response FQR_0 by performing matrix interpolation on the frequency response matrix H(t), and therefore can estimate the frequency response FQR_0 without missing elements. As a result, the estimation device 4A can estimate the frequency responses FQR_1 to FQR_G without missing elements using the frequency response FQR_0.

[0318] In addition, the effects described in the first embodiment can be obtained.

[0319] In the second embodiment, the operation of the estimation device 4A may be realized by software. In this case, the estimation device 4A includes a CPU, a ROM, and a RAM. The ROM stores a program Prog_B consisting of the steps of the flowchart shown in FIG. 23 (including the flowcharts shown in FIGS. 7 to 9 and the flowcharts shown in FIGS. 24 and 25).

[0320] The CPU reads the program Prog_B from the ROM and executes the read program Prog_B from time t0 to time t G The frequency responses FQR_0 to FQR_G at time t0 to t are estimated, and the frequency responses FQR_0 to FQR_G are used to estimate the frequency responses FQR_0 to FQR_G at time t0 to t G The RAM optimizes the transmission weights W and reflection coefficients θ of the N reflecting elements 21 and feeds back the optimized transmission weights W and reflection coefficients θ to the transmitter 1 and the IRS 2A, respectively. N A codebook containing patterns of reflection coefficients is temporarily stored.

[0321] Furthermore, the program Prog_B may be recorded on a recording medium such as a CD or DVD and distributed. When the recording medium on which the program Prog_B is recorded is inserted into a computer, the computer reads and executes the program Prog_B from the recording medium, and executes the program Prog_B from time t0 to time t G The frequency responses FQR_0 to FQR_G at time t0 to t are estimated, and the frequency responses FQR_0 to FQR_G are used to estimate the frequency responses FQR_0 to FQR_G at time t0 to t G The transmit weight W and the reflection coefficient θ in the IRS 1 are optimized, and the optimized transmit weight W and the reflection coefficient θ are fed back to the transmitter 1 and the IRS 2A, respectively.

[0322] Therefore, the recording medium on which the program Prog_B is recorded is a computer-readable recording medium.

[0323] In the second embodiment, the classification of N reflecting elements 21 into c clusters described in the first embodiment may be applied.

[0324] In this case, when estimating each column of the frequency response matrix H(t) using the method described in Figure 15, the IRS controller 22A of the IRS2A controls the one representative reflecting element to be turned "ON" so that only one of the c representative reflecting elements of the c clusters is turned "ON" and the other (c-1) representative reflecting elements are turned "OFF" in a predetermined order.

[0325] Other aspects of the second embodiment are the same as those of the first embodiment.

[0326] In the first embodiment described above, the estimation device 4 uses the formulas (1) to (6) based on the received signal y(t) of the pilot signal received from the receiver 3 to calculate the frequency response H D ,H C is calculated to estimate the frequency response FQR_0 of the propagation path at the time t0 of reception of the received signal y(t), and the frequency response FQR_0 is used to calculate the frequency response FQR_0 at times t1 to t2 in the future from the time t0 of reception. G We explain how to estimate the frequency responses FQR_1 to FQR_G in the frequency domain.

[0327] In the second embodiment, the transmitter 1 uses M in index modulation. T The antenna patterns of the antennas are (N+1)M T Sequentially change to (N+1)M antenna patterns T When the pilot signals are transmitted sequentially, the estimation device 4A calculates (N+1)M T (N+1)M of pilot signals T By sequentially receiving received signals from the communication means 32 of the receiver 3A, (N+1)M of the frequency response matrix H(t) indicating the frequency response of the propagation path between the transmitter 1 and the receiver 3A are obtained. T columns are sequentially estimated, and matrix interpolation is performed on the frequency response matrix H(t) to estimate the frequency response FQR_0 of the propagation path at the time of reception t0. The estimated frequency response FQR_0 of the propagation path is then used to estimate the frequency response FQR_0 of the propagation path at times t1 to t2 that are later than the time of reception t0. GWe explain how to estimate the frequency responses FQR_1 to FQR_G in the frequency domain.

[0328] And (N+1)M T (N+1)M of pilot signals T By sequentially receiving received signals from the communication means 32 of the receiver 3A, (N+1)M T Sequentially estimating these columns corresponds to estimating the frequency response matrix H(t) based on the pilot signal.

[0329] Furthermore, even if matrix interpolation is not performed on the frequency response matrix H(t), it is possible to use the frequency response matrix H(t) before matrix interpolation as the frequency response FQR_0, and to sequentially estimate the frequency responses FQR_1 to FQR_G using the frequency response FQR_0 according to equations (18) and (22).

[0330] Therefore, the estimation device according to the embodiment of the present invention M T (M T a transmitter having N (N is an integer of 2 or more) antennas, an IRS which is an electromagnetic wave reflector having N (N is an integer of 2 or more) reflecting elements whose reflection characteristics can be dynamically changed, and M R (M R is an estimation device that estimates, in a wireless communication space where a transmitter and a receiver each having a number of antennas (an integer equal to or greater than 2) are non-linearly arranged, a frequency response of a propagation path between the transmitter and the receiver when the transmitter transmits a pilot signal, which is a known signal, to the receiver, an estimation means for, upon receiving a received signal of a pilot signal, estimating a frequency response FQR_0 of a propagation path based on the received signal, and using an autoregressive model to execute an estimation process for estimating G frequency responses FQR_1 to FQR_G, which are frequency responses at G future points in time from the point in time when the receiver receives the received signal (G is an integer equal to or greater than 1 and is the total number of points in time at which the frequency responses of the propagation path are estimated); Using the frequency response FQR_0 and G frequency responses FQR_1 to FQR_G, the reflection coefficients of N reflecting elements and M T and optimization means for performing optimization processing to optimize the transmit weights of the antennas.

[0331] If the estimation device includes an estimation means and an optimization means, the frequency response FQR_0 of the propagation path at the time of reception t0 and the frequency response FQR_0 at times t1 to t2 in the future from the time of reception t0 can be calculated. G The frequency responses FQR_1 to FQR_G of the propagation path in the T Since the transmit weights of the antennas are optimized, G This is because, at each point in time, the signal can be transmitted while suppressing the deviation due to the lag between the estimated time of the propagation path and the transmission time.

[0332] Furthermore, the program according to the embodiment of the present invention is M T (M T a transmitter having N (N is an integer of 2 or more) antennas, an IRS which is an electromagnetic wave reflector having N (N is an integer of 2 or more) reflecting elements whose reflection characteristics can be dynamically changed, and M R (M R is a program for causing a computer to execute, in an estimation device of a receiver, an estimation of a frequency response of a propagation path between a transmitter and a receiver, when the transmitter transmits a pilot signal, which is a known signal, to the receiver in a wireless communication space in which the transmitter and the receiver have antennas (an integer equal to or greater than 2) arranged non-linearly, a first step of executing an estimation process in which, when an estimation means receives a received signal of a pilot signal, it estimates a frequency response FQR_0 of the propagation path based on the received signal, and, based on the estimated frequency response FQR_0, it uses an autoregressive model to estimate G frequency responses FQR_1 to FQR_G, which are frequency responses at G future points in time from the point in time when the receiver receives the received signal (G is an integer equal to or greater than 1 and is the total number of points in time at which the frequency responses of the propagation path are estimated); The optimization means calculates the reflection coefficients of the N reflecting elements and M using the frequency response FQR_0 and the G frequency responses FQR_1 to FQR_G. T The computer may then execute a second step of performing an optimization process to optimize the transmit weights of the antennas.

[0333] If the program causes the computer to execute the first step and the second step, the frequency response FQR_0 of the propagation path at the time of reception t0 and the frequency response FQR_0 at the time of reception t0 from t1 to t G The frequency responses FQR_1 to FQR_G of the propagation path in the T Since the transmit weights of the antennas are optimized, G This is because, at each point in time, the signal can be transmitted while suppressing the deviation due to the lag between the estimated time of the propagation path and the transmission time.

[0334] In the embodiment of the present invention, the optimized transmission weights W shown in Table 1 are opt_0 ~W opt_G and the optimized reflection coefficient θ shown in Table 2. opt_0 ~θ opt_G The optimization means 42 that feeds back the above to the transmitter 1 and the IRS2 (or IRS2A), respectively, constitutes the "feedback means."

[0335] In addition, in the embodiment of the present invention, the matrix Q constitutes a "first matrix" and the matrix P constitutes a "second matrix."

[0336] Furthermore, in this embodiment of the present invention, in step S3 of FIG. 6, the frequency response H D constitutes the "first frequency response" of the frequency response FQR_0, and the frequency response H C constitutes a "second frequency response" of the frequency response FQR_0.

[0337] Furthermore, in this embodiment of the present invention, the frequency response H D g(g=1 to G-1) constitutes the "first frequency response" of the frequency response FQR_g (g=1 to G-1), and is the frequency response H C g (g=1 to G-1) constitutes a "second frequency response" of the frequency response FQR_g (g=1 to G-1).

[0338] Furthermore, in this embodiment of the present invention, the frequency response H D g+1 (g=1 to G-1) constitutes the "first frequency response" of the frequency response FQR_g+1 (g=1 to G-1), and is the frequency response H C g+1 (g=1 to G-1) constitutes a "second frequency response" of the frequency response FQR_g+1 (g=1 to G-1).

[0339] The embodiments disclosed herein should be considered to be illustrative in all respects and not restrictive. The scope of the present invention is defined by the claims, not by the description of the above embodiments, and is intended to include all modifications within the meaning and scope of the claims. [Industrial Applicability]

[0340] The present invention is applied to an estimation device, a wireless communication system including the same, and a program to be executed by a computer. [Explanation of symbols]

[0341] 1 transmitter, 2,2A IRS, 3,3A receiver, 4,4A estimator, 10 wireless communication system, 21 reflecting element, 22,22A IRS controller, 31 antenna, 32 communication means, 41,41A estimator, 42 optimization means.

Claims

1. M T (M T a transmitter having N (N is an integer of 2 or more) antennas, an IRS which is an electromagnetic wave reflector having N (N is an integer of 2 or more) reflecting elements whose reflection characteristics can be dynamically changed, and M R (M R an estimation device for estimating, in a wireless communication space in which a transmitter and a receiver having antennas (wherein the number of antennas is an integer equal to or greater than 2) are non-linearly arranged, a frequency response of a propagation path between the transmitter and the receiver when the transmitter transmits a pilot signal, which is a known signal, to the receiver, the estimation device comprising: an estimation means for executing an estimation process, when receiving a received signal of the pilot signal, estimating a frequency response FQR_0 of the propagation path at the time when the received signal was received based on the received signal, and estimating G frequency responses FQR_1 to FQR_G, which are the frequency responses at G time points (G is an integer equal to or greater than 1 and is the total number of time points at which the frequency responses of the propagation path are estimated) that are future time points from the time when the receiver received the received signal, using an autoregressive model based on the estimated frequency response FQR_0; The frequency response FQR_0 and the G frequency responses FQR_1 to FQR_G are used to calculate the reflection coefficients of the N reflecting elements and the M T and optimization means for performing an optimization process to optimize the transmit weights of the antennas.

2. 2. The estimation device according to claim 1, wherein, in the estimation process, the estimated frequency response FQR_0 is set as an initial value of the frequency response, and the first frequency response FQR_1 is estimated from the initial value. Then, the estimation means sequentially executes an estimation process for estimating g (g is an integer satisfying 1≦g≦(G−1))-th frequency responses FQR_g to (g+1)-th frequency responses FRQ_g+1 for all of g=1 to (G−1), thereby estimating the G frequency responses FQR_1 to FQR_G.

3. the frequency response FQR_0 and each of the G frequency responses FQR_1 to FQR_G include a first frequency response indicating a frequency response of a direct link, which is a propagation path when a radio wave reaches the receiver directly from the transmitter, and a second frequency response indicating a frequency response of an indirect link, which is a propagation path when the radio wave reaches the receiver from the transmitter via the IRS, and each of the first frequency response and the second frequency response of the frequency response FQR_0 is set as an initial value; 3. The estimation device according to claim 2, wherein, in the estimation process, the estimation means estimates a first first frequency response from an initial value of the first frequency response of the estimated frequency response FQR_0 and estimates a first second frequency response from an initial value of the second frequency response of the estimated frequency response FQR_0, then estimates the (g+1)th first frequency response from the gth first frequency response, estimates the (g+1)th second frequency response from the gth second frequency response, estimates the gth frequency response FQR_g consisting of the gth first frequency response and the gth second frequency response, and estimates the (g+1)th frequency response FQR_g+1 consisting of the (g+1)th first frequency response and the (g+1)th second frequency response, sequentially for all of g = 1 to (G-1), thereby estimating the G frequency responses FQR_1 to FQR_G.

4. The estimation means is configured to estimate the M T Only one antenna among the M antennas is used to transmit the pilot signal, and antennas other than the one antenna are not used to transmit the pilot signal. T The pilot signals are assigned to the antenna patterns of the (N+1)M antennas by index modulation. T 4. The estimation device according to claim 1, wherein when the pilot signals are sequentially transmitted to the receiver, in the estimation process, each time one of the pilot signals is received, a process of estimating one column of a frequency response matrix indicating a frequency response of the propagation path is performed for all columns of the frequency response matrix to estimate the frequency response matrix, and the frequency response FQR_0 consisting of the estimated frequency response matrix is ​​estimated.

5. The (N+1)M T The transmitter transmits the pilot signals by using the M T The antenna patterns of the (N+1)M antennas are T The (N+1)M antenna patterns are sequentially changed to T 5. The estimator of claim 4, wherein the estimator is implemented by sequentially transmitting pilot signals.

6. 6. The estimation device according to claim 4, wherein the estimation means, in the estimation process, performs matrix interpolation on the estimated frequency response matrix to interpolate between elements of the frequency response matrix, and estimates the frequency response matrix after the matrix interpolation as the frequency response FQR_0.

7. 7. The estimation device according to claim 6, wherein, in the estimation process, the estimation means generates a Hankel matrix from the estimated frequency response matrix, decomposes the generated Hankel matrix into a product of first and second matrices by singular value decomposition, and performs updating of the first matrix, updating of the second matrix, and updating of the Hankel matrix a predetermined number of times, thereby performing the matrix interpolation.

8. The N reflecting elements are classified into c clusters (c is an integer equal to or greater than 1), each of which has the same frequency response of the propagation path; The estimation device according to claim 1 , wherein the reflective elements included in each of the c clusters are controlled so that they have the same reflective characteristics.

9. The reflection coefficients of the N reflecting elements optimized by the optimization means and the M T The estimation device according to claim 1 , further comprising feedback means for feeding back transmission weights of the antennas to the IRS and the transmitter, respectively.

10. A wireless communication system comprising the receiver, the transmitter, and the IRS, the receiver comprising the estimation device according to any one of claims 1 to 9.

11. M T (M T a transmitter having N (N is an integer of 2 or more) antennas, an IRS which is an electromagnetic wave reflector having N (N is an integer of 2 or more) reflecting elements whose reflection characteristics can be dynamically changed, and M R (M R a receiver having a number of antennas (where the number is an integer equal to or greater than 2) arranged non-linearly in a wireless communication space, when the transmitter transmits a pilot signal, which is a known signal, to the receiver, the program causing a computer to execute an estimation device of the receiver to estimate a frequency response of a propagation path between the transmitter and the receiver, the program comprising: a first step of executing an estimation process in which, when a received signal of the pilot signal is received, a frequency response FQR_0 of the propagation path at the time the received signal is received is estimated based on the received signal, and an autoregressive model is used based on the estimated frequency response FQR_0 to estimate G frequency responses FQR_1 to FQR_G, which are the frequency responses at G time points (G is an integer equal to or greater than 1 and is the total number of time points at which the frequency responses of the propagation path are estimated) that are future time points from the time the received signal is received; The frequency response FQR_0 and the G frequency responses FQR_1 to FQR_G are used to calculate the reflection coefficients of the N reflecting elements and the M T and a second step of performing an optimization process in which the transmit weights of the antennas are optimized.

12. A program to be executed by a computer as described in claim 11, wherein in the estimation process of the first step, the estimated frequency response FQR_0 is set as an initial value of the frequency response, and when the first frequency response FQR_1 is estimated from the initial value, an estimation process is performed sequentially for all of g = 1 to (G-1) to estimate the (g+1)th frequency response FQR_g+1 from the gth (g is an integer satisfying 1≦g≦(G-1)) frequency response FQR_g, thereby estimating the G frequency responses FQR_1 to FQR_G.

13. the frequency response FQR_0 and each of the G frequency responses FQR_1 to FQR_G include a first frequency response indicating a frequency response of a direct link, which is a propagation path when a radio wave reaches the receiver directly from the transmitter, and a second frequency response indicating a frequency response of an indirect link, which is a propagation path when the radio wave reaches the receiver from the transmitter via the IRS, and each of the first frequency response and the second frequency response of the frequency response FQR_0 is set to an initial value; In the estimation process of the first step, when a first first frequency response is estimated from an initial value of the first frequency response of the estimated frequency response FQR_0 and a first second frequency response is estimated from an initial value of the second frequency response of the estimated frequency response FQR_0, the (g+1)-th first frequency response is estimated from the g-th first frequency response, and the (g+1)-th second frequency response is estimated from the g-th second frequency response, 13. The program for causing a computer to execute the program according to claim 12, wherein a process of estimating the gth frequency response FQR_g consisting of the gth first frequency response and the gth second frequency response and estimating the (g+1)th frequency response FQR_g+1 consisting of the (g+1)th first frequency response and the (g+1)th second frequency response is sequentially executed for all of g=1 to (G−1), thereby estimating the G frequency responses FQR_1 to FQR_G.

14. The transmitter is T Only one antenna among the M antennas is used to transmit the pilot signal, and antennas other than the one antenna are not used to transmit the pilot signal. T The pilot signals are assigned to the antenna patterns of the (N+1)M antennas by index modulation. T 14. The program for causing a computer to execute the program according to claim 11, wherein when the pilot signals are sequentially transmitted to the receiver, in the estimation process of the first step, each time one of the pilot signals is received, a process of estimating one column of a frequency response matrix indicating a frequency response of the propagation path is performed for all columns of the frequency response matrix, thereby estimating the frequency response matrix, and the frequency response FQR_0 consisting of the estimated frequency response matrix is ​​estimated.

15. The (N+1)M T The transmitter transmits the pilot signals by using the M T The antenna patterns of the (N+1)M antennas are T The (N+1)M antenna patterns are sequentially changed to T 15. The computer-executable program of claim 14, wherein the program is executed by sequentially transmitting pilot signals.

16. A program to be executed by a computer as described in claim 14 or claim 15, wherein in the estimation process of the first step, matrix interpolation is performed on the estimated frequency response matrix to interpolate between elements of the frequency response matrix, and the frequency response matrix after the matrix interpolation is estimated as the frequency response FQR_0.

17. A program to be executed by a computer as described in claim 16, wherein in the estimation process of the first step, a Hankel matrix is ​​generated from the estimated frequency response matrix, the generated Hankel matrix is ​​decomposed into a product of a first and a second matrix by singular value decomposition, and the matrix interpolation is performed by updating the first matrix, updating the second matrix, and updating the Hankel matrix a predetermined number of times.

18. The N reflecting elements are classified into c clusters (c is an integer equal to or greater than 1), each of which has the same frequency response of the propagation path; 18. The program for causing a computer to execute the program according to claim 11, wherein the reflective elements included in each of the c clusters are controlled so that the reflective characteristics are the same.

19. The optimized reflection coefficients of the N reflecting elements and the M T 19. The program for causing a computer to execute the program according to claim 11, further causing the computer to execute a third step of feeding back transmission weights of the antennas to the IRS and the transmitter, respectively.

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