Signal estimation device, signal estimation method, and computer program

Abstract

To provide a signal estimation device capable of reducing an amount of calculation required to estimate a transmission signal on the basis of a reception signal.SOLUTION: A signal estimation device (211) includes conversion means (211) that performs discrete Fourier transform processing on M×N reception signal components included in a reception signal (y) in units of N reception signal components, and estimation means (212) that estimates an estimated signal (xe) including M×N estimation signal components, which is an estimated value of M×N transmission signal components, on the basis of the reception signal subjected to the discrete Fourier transform processing, and when an estimated signal is newly estimated, the estimation means performs exclusion operation in which estimated values (xe(k)) of the M transmission signal components that make up a k-th transmission signal group from the newly estimated signal xe (where k is a variable indicating an integer greater than or equal to 0 and less than or equal to N-1) are excluded, and estimates again, the estimated signal (xe) by updating the estimated value (xe(k)) on the basis of an intermediate signal (xt(k)) obtained by the exclusion operation and the reception signal y.SELECTED DRAWING: Figure 6

Description

[Technical field]

[0001] The present invention relates to a signal estimation device and a signal estimation method for estimating a transmission signal transmitted by a transmitting device based on a received signal received by a receiving device, and to a computer program for executing the above-mentioned signal estimation method. [Background technology]

[0002] In recent years, research has been conducted into communication systems that transmit and receive signals using OAM-MIMO (Orbital Angular Momentum-Multiple Input Multiple Output) transmission technology. The OAM-MIMO transmission technology is a transmission technology that transmits signals multiplexed using multiple radio waves having different OAM modes from a transmitting device having multiple transmitting antennas to a receiving device having multiple receiving antennas. An example of a communication system that employs such an OAM-MIMO transmission technology is described in Non-Patent Document 1. Specifically, Non-Patent Document 1 describes a communication system that transmits signals multiplexed using multiple radio waves having different OAM modes between a transmitting device having multiple circular array antennas (UCA: Uniform Circular Array) including multiple antenna elements arranged at equal intervals in a circle, and a receiving device having multiple circular array antennas. Other prior art documents related to the present invention include Patent Documents 1 to 5 and Non-Patent Document 2. [Prior art documents] [Patent documents]

[0003] [Patent Document 1] International Publication No. 2019 / 059408 Brochure [Patent Document 2] Special Publication No. 2017-515337 [Patent Document 3] JP 2015-073260 A [Patent Document 4] Patent No. 6583292 [Patent Document 5] Patent No. 5317021 [Non-patent literature]

[0004] [Non-Patent Document 1] Hirofumi Sasaki et al., “Experiment on Over-100-Gbps Wireless Transmission with OAM-MIMO Multiplexing System in 28-GHz Band”, 2018 IEEE Global Communications Conference (GLOBECON), December 2018 [Non-Patent Document 2] Masashi Hirabe et al., “40mTransmission of OAM mode and Polarization Multiplexing in E-band”, 2019 IEEE Global Communications Conference (GLOBECON), December 2019 Summary of the Invention [Problem to be solved by the invention]

[0005] In a communication system employing OAM-MIMO transmission technology, a receiving device receives a transmission signal transmitted by a transmitting device as a received signal and estimates the transmission signal based on the received signal. Typically, the receiving device estimates the transmission signal based on a transmission path matrix (in other words, a channel matrix) indicating the state of the transmission path between the transmitting device and the receiving device and the received signal.

[0006] When the transmission signal is estimated in this manner, it is desirable to reduce the amount of calculation required to estimate the transmission signal. Here, when the multiple circular array antennas of the transmitting device and the multiple circular array antennas of the receiving device are arranged so as to be axially symmetric, the transmission channel matrix becomes a block diagonal matrix having a large gain only in the diagonal block components. As a result, the components other than the diagonal block components of the transmission channel matrix become zero, so that the amount of calculation required to estimate the transmission signal is reduced. Therefore, if the multiple circular array antennas of the transmitting device and the multiple circular array antennas of the receiving device are always arranged so as to be axially symmetric, it is possible to improve the estimation accuracy of the transmission signal.

[0007] However, in reality, the multiple circular array antennas of the transmitting device and the multiple circular array antennas of the receiving device are not always arranged so as to be axially symmetric. For example, the circular array antennas may be displaced due to wind and rain, so that the multiple circular array antennas of the transmitting device and the multiple circular array antennas of the receiving device may not be axially symmetric. As a result, the transmission channel matrix may not be a block diagonal matrix. In addition to the factor that the multiple circular array antennas of the transmitting device and the multiple circular array antennas of the receiving device are not axially symmetric, the transmission channel matrix may not be a block diagonal matrix due to other factors. For example, the transmission channel matrix may not be a block diagonal matrix due to fading caused by reflection of radio waves. In this way, the scenes in which a method of reducing the amount of calculations by utilizing the fact that the transmission channel matrix is ​​a block diagonal matrix can be used are limited. In addition, even in a communication system in which a signal multiplexed using a plurality of radio waves having different OAM modes is transmitted from a transmitting device having a single transmitting antenna to a receiving device having a single receiving antenna, it is still desirable to reduce the amount of calculation required to estimate the transmitted signal. However, the circular array antenna of the transmitting device and the circular array antenna of the receiving device are not always arranged to be axially symmetric. Therefore, even in a communication system having a single transmitting antenna and a single receiving antenna, there are only limited situations in which a method for reducing the amount of calculation by utilizing the fact that the transmission path matrix is ​​a block diagonal matrix can be used.

[0008] The present invention aims to provide a signal estimation device, a signal estimation method, and a computer program that can solve the above-mentioned technical problems. As an example, the present invention aims to provide a signal estimation device, a signal estimation method, and a computer program that can reduce the amount of calculation required to estimate a transmitted signal based on a received signal. [Means for solving the problem]

[0009] One aspect of the signal estimation device is a signal estimation device for estimating the transmission signal x from the reception signal y in a communication system including a transmission device that transmits a transmission signal x including N transmission signal groups each including M transmission signal components transmitted by M different transmission array antennas, using a transmission antenna in which M transmission array antennas each including N transmission antenna elements (where N is an integer equal to or greater than 1) arranged concentrically, the transmission antenna including N transmission antenna elements arranged at equal intervals on a circle, and a reception device that receives the transmission signal x transmitted by the transmission device as a reception signal y, using a reception antenna in which M reception array antennas each including N reception antenna elements arranged at equal intervals on a circle are arranged concentrically, the signal estimation device being configured to estimate the transmission signal x from the reception signal y. The signal estimation device includes a transform means for performing a discrete Fourier transform process on M×N received signal components included in the received signal y and received by the M×N receiving antenna elements, respectively, in units of the N received signal components received by each of the M receiving array antennas, and an estimation means for estimating an estimated signal xe including M×N estimated signal components that are estimates of the M×N transmitted signal components, based on the received signal y that has been subjected to the discrete Fourier transform process, and when the estimated signal xe is newly estimated, the estimation means estimates the estimated value xe of the M transmitted signal components constituting the kth (where k is a variable indicating an integer not less than 0 and not more than N−1)-th transmitted signal group from the newly estimated estimated signal xe. (k) and performing an exclusion operation to exclude intermediate signal xt (k) and the estimated value xe based on the received signal y. (k) The signal estimation device re-estimates the estimated signal xe by updating

[0010] One aspect of the signal estimation method is a signal estimation method for estimating the transmission signal x from the received signal y in a communication system including a transmission device that uses a transmission antenna in which M (where M is an integer equal to or greater than 1) transmission array antennas are arranged concentrically, the transmission array antennas including N (where N is an integer equal to or greater than 1) transmission antenna elements arranged at equal intervals on a circle to transmit a transmission signal x including N transmission signal groups each including M transmission signal components transmitted by the M different transmission array antennas, and a receiving device that receives the transmission signal x transmitted by the transmission device as a received signal y using a receiving antenna in which M receiving array antennas including N receiving antenna elements arranged at equal intervals on a circle are arranged concentrically, The signal estimation method includes a transforming step of performing a discrete Fourier transform process on M×N received signal components included in the received signal y and received by the M×N receiving antenna elements, respectively, in units of the N received signal components received by each of the M receiving array antennas, and an estimation step of estimating an estimated signal xe including M×N estimated signal components that are estimates of the M×N transmitted signal components, based on the received signal y that has been subjected to the discrete Fourier transform process, and the estimation step includes, when the estimated signal xe is newly estimated, estimating an estimate value xe of the M transmitted signal components constituting a k-th (where k is a variable indicating an integer not less than 0 and not more than N−1)-th transmitted signal group from the newly estimated estimated signal xe. (k) A first step of excluding the intermediate signal xt (k) and the estimated value xe based on the received signal y. (k) a second step of re-estimating the estimated signal xe by updating

[0011] One aspect of the computer program is a computer program that causes a computer to execute a signal estimation method, the signal estimation method being in a communication system including a transmitting device that transmits a transmitting signal x including N transmitting signal groups each including M transmitting signal components transmitted by M mutually different transmitting array antennas, using a transmitting antenna in which M transmitting array antennas (where M is an integer equal to or greater than 1) are arranged concentrically, each including N transmitting antenna elements (where N is an integer equal to or greater than 1), each including N transmitting antenna elements arranged at equal intervals on a circle, and a receiving device that receives the transmitting signal x transmitted by the transmitting device as a receiving signal y, using a receiving antenna in which M receiving array antennas (where N is an integer equal to or greater than 1) are arranged concentrically, each including N receiving antenna elements (where N is an integer equal to or greater than 1), a transform step of performing a discrete Fourier transform process on M×N received signal components included in the received signal y and received by the M×N receiving antenna elements, respectively, in units of the N received signal components received by each of the M receiving array antennas; and an estimation step of estimating an estimated signal xe including M×N estimated signal components that are estimates of the M×N transmitted signal components, based on the received signal y that has been subjected to the discrete Fourier transform process, wherein the estimation step includes, when the estimated signal xe is newly estimated, estimating an estimate value xe of the M transmitted signal components constituting the kth (where k is a variable indicating an integer not less than 0 and not more than N−1)-th transmitted signal group from the newly estimated estimated signal xe. (k) A first step of excluding the intermediate signal xt (k) and the estimated value xe based on the received signal y. (k) a second step of re-estimating the estimated signal xe by updating Effect of the Invention

[0012] According to each aspect of the above-described signal estimation device, signal estimation method, and computer program, it is possible to reduce the amount of calculation required to estimate a transmission signal based on a received signal. [Brief description of the drawings]

[0013] [Figure 1] FIG. 1 is a block diagram showing the configuration of a communication system according to the present embodiment. [Diagram 2] FIG. 2 is a vector showing a transmission signal transmitted by a transmitting device. [Diagram 3] FIG. 3 is a vector showing a received signal received by a receiving device. [Figure 4] FIG. 4 shows the relationship between the transmitted signal and the received signal. [Diagram 5] FIG. 5 shows a channel matrix which is a block diagonal matrix. [Figure 6] FIG. 6 is a block diagram showing a configuration of the first signal estimation unit. [Figure 7] FIG. 7 is a flowchart showing a flow of operations performed by the first signal estimation unit to estimate a transmitted signal. [Figure 8] FIG. 8 is a block diagram showing a configuration of the second signal estimation unit. [Figure 9] FIG. 9 is a flowchart showing a flow of an operation of the second signal estimation unit to estimate a transmitted signal. [Figure 10] FIG. 10 is a block diagram showing an example of the configuration of the basic arithmetic unit. [Figure 11] Each of FIG. 11(a) to FIG. 11(c) is a graph showing an example of a nonlinear function. [Figure 12] FIG. 12 is a block diagram showing a configuration of a communication system according to a modified example. DETAILED DESCRIPTION OF THE PREFERRED EMBODIMENTS

[0014] Hereinafter, with reference to the drawings, a description will be given of an embodiment of a signal estimation device, a signal estimation method, and a computer program using a communication system SYS to which the embodiment of the signal estimation device, the signal estimation method, and the computer program are applied. However, the present invention is not limited to the embodiment described below. <1> Configuration of the communication system SYS

[0015] First, the configuration of a communication system SYS of the present embodiment will be described with reference to Fig. 1. Fig. 1 is a block diagram showing the configuration of a communication system SYS of the first embodiment.

[0016] As shown in Fig. 1, the communication system SYS includes a transmitting device 1 and a receiving device 2. The transmitting device 1 transmits a transmission signal x to the receiving device 2 via a transmission path 3. The receiving device 2 receives the transmission signal x transmitted by the transmitting device 1 via the transmission path 3 as a received signal y. The transmission path 3 may include a wired transmission path (i.e., a communication network). The transmission path 3 may also include a wireless transmission path (i.e., a communication network).

[0017] The transmitting device 1 transmits a transmission signal x using an OAM (Orbital Angular Momentum) transmission technique. The OAM transmission technique is a technique for transmitting a signal multiplexed using a plurality of radio waves having different OAM modes from the transmitting device 1 to the receiving device 2. In order to transmit the transmission signal x using the OAM transmission technique, the transmitting device 1 includes a transmitting antenna 10, a signal processing device 11, and a storage device 12. The signal processing device 11 and the storage device 12 may be connected via a data bus 13.

[0018] The transmitting antenna 10 includes a plurality of uniform circular array antennas (UCA) 100 with different diameters. In the following description, the transmitting antenna 10 includes M (where M is an integer equal to or greater than 1) circular array antennas 100 (specifically, circular array antennas 100#0 to 100#M-1). When the transmitting antenna 10 includes two or more circular array antennas 100 (and further, when the receiving antenna 20 described below includes two or more circular array antennas 200), the OAM transmission technique may be referred to as OAM-MIMO (Multiple Input Multiple Output) transmission technique. The M circular array antennas 100 are arranged concentrically (i.e., coaxially). Specifically, the M circular array antennas 100 are arranged such that the circular array antennas 100#0 to 100#M-1 are arranged in this order from the center to the outside. Each circular array antenna 100 includes a plurality of antenna elements 101. 1, each circular array antenna 100 includes N (where N is an integer equal to or greater than 2) antenna elements 101 (specifically, antenna element 101#0 to antenna element 101#N-1). In FIG. 1, antenna elements 101#0 to 101#N-1 included in circular array antenna 100#p (where p is a variable indicating an integer equal to or greater than 0 and equal to or less than M-1) are represented as antenna elements 101#0(#p) to 101#N-1(#p), respectively.

[0019] Radio waves of different OAM modes are assigned to the N antenna elements 101 included in each circular array antenna 100 within the same frequency band. That is, in this embodiment, the transmitting device 1 multiplexes the transmission signal x using the N OAM modes. In this case, each circular array antenna 100 can transmit the transmission signal x in units of N transmission signal groups corresponding to the N OAM modes, respectively, using the N antenna elements 101. However, radio waves of the same OAM mode may be assigned to at least two antenna elements 101 included in each circular array antenna 100. That is, the number of OAM modes may be less than the number of antenna elements 101 included in each circular array antenna 100.

[0020] Furthermore, since the transmitting antenna 10 includes M circular array antennas 100, the N transmission signal groups can include M transmission signal components. Therefore, the transmitting device 1 can transmit a transmission signal (i.e., a transmission signal sequence) x in which a maximum of M×N transmission signal components are multiplexed. Hereinafter, the transmission signal component transmitted by the kth (where k is an integer not less than 0 and not more than N-1) antenna element 101#k of the circular array antenna 100#p will be referred to as "transmission signal x (k) (p) In this case, the transmission signal x can be expressed by a vector as shown in FIG. 2. In FIG. 2, "transmission signal x (k) " is M transmission signals x transmitted by M k-th antenna elements 101#k of M circular array antennas 100, respectively. (k) (0) Transmit signal from x (k) (M-1) In other words, "transmitted signal x (k) " corresponds to a transmission signal included in the k-th transmission signal group transmitted in the same OAM mode.

[0021] The signal processing device 11 may include at least one of a central processing unit (CPU), a graphic processing unit (GPU), and a field programmable gate array (FPGA). The signal processing device 11 may read a computer program. For example, the signal processing device 11 may read a computer program stored in a computer-readable recording medium using a recording medium reading device (not shown). The signal processing device 11 may acquire (i.e., download or read) a computer program from a device (not shown) disposed outside the transmitting device 1 via a communication device (not shown). The signal processing device 11 executes the read computer program. As a result, a logical function block for executing the operation to be performed by the transmitting device 1 is realized in the signal processing device 11. Specifically, a logical function block for executing the transmission operation of transmitting a transmission signal x is realized in the signal processing device 11. In other words, the signal processing device 11 can function as a controller for realizing a logical function block for executing the operation to be performed by the transmitting device 1.

[0022] Fig. 1 shows an example of logical functional blocks implemented in the signal processing device 11 to perform a transmission operation. As shown in Fig. 1, M conversion units 111 (specifically, conversion unit 111#0 to conversion unit 111#M-1) are implemented in the signal processing device 11.

[0023] Each conversion unit 111#p converts N transmission signals x (0) (p) Transmit signal from x (N-1) (p) In this embodiment, each transform unit 111#p performs pre-processing on N transmit signals x (0) (p)Transmit signal from x (N-1) (p) In this case, each transform unit 111#p may include an inverse discrete Fourier transformer of length N. The inverse discrete Fourier transform process is performed on N transmit signals x (0) (p) Transmit signal from x (N-1) (p) That is, the signal processing device 11 may perform at least a part of the process for OAM multiplexing M×N transmit signals x (k) (p) Each of the N transmit signals x (0) (p) Transmit signal from x (N-1) (p) The transmission signal x may be OAM multiplexed by dividing the signal x into M signal sequences including N, and performing an inverse discrete Fourier transform process on each of the M signal sequences. (0) (p) Transmit signal from x (N-1) (p) are transmitted to the receiving device 2 by the corresponding circular array antenna 100#p. In the following description, N transmission signals x (0) (p) Transmit signal from x (N-1) (p) , "Transmitted signal x' (0) (p) Transmit signal x' from (N-1) (p) ", the N transmit signals x before the inverse discrete Fourier transform processing is performed. (0) (p) Transmit signal from x (N-1) (p) Distinguish from.

[0024] The storage device 12 can store desired data. For example, the storage device 12 may temporarily store a computer program executed by the signal processing device 11. The storage device 12 may temporarily store data that is temporarily used by the signal processing device 11 when the signal processing device 11 is executing a computer program. The storage device 12 may store data that the transmitting device 1 stores for a long period of time. The storage device 12 may include at least one of a RAM (Random Access Memory), a ROM (Read Only Memory), a hard disk device, a magneto-optical disk device, an SSD (Solid State Drive), and a disk array device.

[0025] The receiving device 2 includes a receiving antenna 20, a signal processing device 21, and a storage device 22. The signal processing device 21 and the storage device 22 may be connected via a data bus 23.

[0026] The receiving antenna 20 is an antenna for receiving a transmission signal x transmitted using an OAM transmission technique as a reception signal y. In this embodiment, the receiving antenna 20 includes a plurality of circular array antennas 200 having different diameters. In the following description, the receiving antenna 20 includes M circular array antennas 200 (specifically, circular array antennas 200#0 to 200#M-1). The M circular array antennas 200 are arranged concentrically (i.e., coaxially). Specifically, the M circular array antennas 200 are arranged such that the circular array antennas 200#0 to 200#M-1 are arranged in this order from the center to the outside. Each circular array antenna 200 includes a plurality of antenna elements 201. In the example shown in FIG. 1, each circular array antenna 200 includes N antenna elements 201 (specifically, antenna element 201#0 to antenna element 201#N-1). In FIG. 1, antenna elements 201#0 to 201#N-1 included in circular array antenna 200#p are represented as antenna elements 201#0(#p) to 201#N-1(#p), respectively.

[0027] The circular array antenna 200#p uses N antenna elements #0(#p) to 201#N-1(#p) to receive N transmission signals x' transmitted by one circular array antenna 100#p corresponding to the circular array antenna 200#p. (0) (p) Transmit signal x' from (N-1) (p) , the received signal y (0) (p) Received signal from y (N-1) (p) Typically, the antenna element 201#k(#p) of the circular array antenna 200#p receives the transmission signal x' transmitted by the antenna element 101#k(#p) of the circular array antenna 100#p. (k) (p) , the received signal y (k) (p) Therefore, the received signal y can be expressed by the vector shown in FIG. 3. In FIG. 3, "received signal y (k) " is M received signals y received by M k-th antenna elements 201#k of M circular array antennas 200, respectively. (k) (0) Received signal from y (k) (M-1) That is, "received signal y (k) " is the received signal group received in the corresponding OAM mode (i.e., the transmitted signal x included in the corresponding transmitted signal group). (k) (corresponding to the received signal obtained by receiving the

[0028] The signal processing device 21 may include at least one of a CPU, a GPU, and an FPGA. The signal processing device 21 reads a computer program. For example, the signal processing device 21 may read a computer program stored in the storage device 22. For example, the signal processing device 21 may read a computer program stored in a computer-readable recording medium using a recording medium reading device (not shown). The signal processing device 21 may acquire (i.e., download or read) a computer program from a device (not shown) disposed outside the receiving device 2 via a communication device (not shown). The signal processing device 21 executes the read computer program. As a result, a logical function block for executing an operation to be performed by the receiving device 2 is realized in the signal processing device 21. Specifically, a logical function block for executing a receiving operation to receive the received signal y is realized in the signal processing device 21. In other words, the signal processing device 21 can function as a controller for realizing a logical function block for executing an operation to be performed by the receiving device 2.

[0029] 1 shows an example of logical functional blocks implemented in the signal processing device 21 to perform a receiving operation. As shown in FIG 1, the signal processing device 21 implements M transform units 211 (specifically, transform unit 211#0 to transform unit 211#M-1) and a signal estimation unit 212.

[0030] Each conversion unit 211#p converts N received signals y (0) (p) Received signal from y (N-1) (p) In this embodiment, each transform unit 211#p performs pre-processing on N received signals y (0) (p) Received signal from y (N-1) (p)In this case, each transform unit 211#p may include a discrete Fourier transformer of length N. The discrete Fourier transform process is carried out on the N OAM multiplexed received signals y (0) (p) Received signal from y (N-1) (p) That is, the signal processing device 21 may configure at least a part of the process for separating M×N received signals y (k) (p) Each of the received signals y (0) (p) Received signal from y (N-1) (p) In other words, the signal processing device 21 divides the M×N received signals y (k) (p) For a received signal y including (0) (p) Received signal from y (N-1) (p) The discrete Fourier transform process is performed on the M signal sequences including the received signal y after the Fourier transform process (i.e., the M×N received signals y after the Fourier transform process). (k) (p) The received signal y including the received signal y is output to the signal estimation unit 212. In the following description, unless otherwise specified, the received signal y (received signal y (k) (p) and the received signal y (k) (including ) means a received signal that has been subjected to Fourier transform processing.

[0031] The signal estimation unit 212 estimates the M×N received signals y (k) (p) Specifically, the signal estimation unit 212 estimates the transmitted signal x based on the received signal y including M×N transmitted signals x (k) (p) The M × N estimated signals x_estimate(k) (p) The signal estimation unit 212 estimates an estimated signal x_estimate including N transmitted signals x included in the transmitted signal x based on the received signal y. (k) N estimated signals x_estimate (k) In the following, for the sake of simplicity, the "estimated signal x_estimate" will be written as the "estimated signal xe."

[0032] Here, the relationship between the transmission signal x and the reception signal y is as shown in Fig. 4. In Fig. 4, "H" indicates a transmission path matrix (in other words, a channel matrix) indicating the state (typically, the transmission state) of the transmission path 3 between the transmission antenna 10 and the reception antenna 20. The transmission path matrix H is an M row x M row matrix H (i,j) As an (i, j) component (where i and j are integers greater than or equal to 0 and less than or equal to N-1), the block matrix has MN rows and MN columns. (0) , n (1) , , n (N-1) " indicates a vector whose components are noise (for example, white noise) occurring in the transmission path 3.

[0033] One example of a signal estimation method for estimating a transmitted signal x based on a received signal y is a signal estimation method employing an exhaustive search method. The signal estimation method employing an exhaustive search method calculates all possible signal patterns of the received signal y by performing the calculation shown in FIG. 4 for each of all possible signal patterns (i.e., signal sequences) of the transmitted signal x, and selects, as the signal pattern of the estimated signal xe, the signal pattern of the transmitted signal x corresponding to the received signal y having a signal pattern closest to the signal pattern of the actually received received signal y. However, the signal estimation method employing the exhaustive search method requires an enormous amount of calculation to estimate the transmitted signal x.

[0034] Another example of a signal estimation method for estimating the transmitted signal x based on the received signal y is a signal estimation method using the least squares method. The signal estimation method using the least squares method estimates the transmitted signal x using Equation 1 (i.e., M×N estimated signals xe (k) (p) In addition, "H†" in the formula 1 indicates the conjugate transpose matrix of the transmission channel matrix H. (k) ” is a function of M parameters “σ (k) (0) , , σ (k) (M-1) " in Equation 1. (0) , , σ (N-1) ) is the parameter σ, which represents the M × N signal-to-noise power ratio. (0) , , σ (N-1) This shows a diagonal matrix with MN rows and MN columns, with " " as diagonal components.

[0035]

number

[0036] The amount of calculation required to estimate the transmission signal x using the least squares method is smaller than the amount of calculation required to estimate the transmission signal x using the exhaustive search method. However, since the transmission channel matrix H has a size of MN rows x MN columns, in order to estimate the transmission signal x using Equation 1, the calculation of the inverse matrix having a size of MN rows x MN columns, which has a relatively large contribution to the amount of calculation, is required. 3 Therefore, there is still room for reduction in the amount of calculation required to estimate the transmitted signal x using the least squares method. Furthermore, the accuracy of estimating the transmitted signal x using the least squares method is inferior to that of estimating the transmitted signal x using the exhaustive search method.

[0037] On the other hand, in an ideal environment in which the transmitting antenna 10 and the receiving antenna 20 are arranged axially symmetrically (i.e., coaxially) and there is no interference due to fading or the like in the transmission path 3, the matrix H (i,j) becomes a zero matrix under the condition that i ≠ j. As a result, the transmission matrix H becomes a block diagonal matrix in which components other than the diagonal block components become zero, as shown in Fig. 5. In this case, the signal estimation method using the least squares method described above becomes a method of estimating the transmission signal x using Equation 2.

[0038]

number

[0039] Here, the matrix H (k、k) Since the size of the matrix has M rows and M columns, the calculation of the inverse matrix having a size of M rows and M columns, which has a relatively large contribution to the amount of calculation, is performed to estimate the transmitted signal x using Equation 2. 3 A calculation amount proportional to is required. Therefore, the calculation amount required to estimate the transmission signal x using the least squares method based on the formula 2 is smaller than the calculation amount required to estimate the transmission signal x using the least squares method based on the formula 1. On the other hand, the transmission signal x can be estimated using the least squares method based on the formula 2 only in an ideal scene in which the transmission antenna 10 and the reception antenna 20 are arranged axially symmetrically and there is no interference due to fading or the like in the transmission path 3. However, in reality, the transmission antenna 10 and the reception antenna 20 are not always arranged axially symmetrically. For example, there is a possibility that the transmission antenna 10 and the reception antenna 20 are not always axially symmetrical due to at least a part of the arrangement positions of the transmission antenna 10 and the reception antenna 20 being shifted due to wind and rain. In addition, it is not easy to realize an environment in which there is always no interference due to fading or the like in the transmission path 3. For this reason, the possibility that the transmission path matrix H will not become a block diagonal matrix is ​​not low at all.

[0040] Therefore, in this embodiment, the signal estimation unit 212 employs a new signal estimation method proposed below to estimate the transmission signal x. As a result, even when the transmission channel matrix H is not a block diagonal matrix, the signal estimation unit 212 can appropriately estimate the transmission signal x with a relatively small amount of calculation. For example, when the transmission channel matrix H is not a block diagonal matrix, the signal estimation unit 212 can appropriately estimate the transmission signal x with a smaller amount of calculation than the amount of calculation required to estimate the transmission signal x using the least squares method based on Equation 1. Note that the details of the signal estimation unit 212 will be described later with reference to FIG. 6 and the like, and therefore will not be described in detail here.

[0041] 1 again, the storage device 22 can store desired data. For example, the storage device 22 may temporarily store a computer program executed by the signal processing device 21. The storage device 22 may temporarily store data that is temporarily used by the signal processing device 21 when the signal processing device 21 is executing a computer program. The storage device 22 may store data that the receiving device 2 stores for a long period of time. The storage device 22 may include at least one of a RAM, a ROM, a hard disk device, a magneto-optical disk device, an SSD, and a disk array device. <2> Signal Estimation Unit 212

[0042] Next, the signal estimation unit 212 will be described. In this embodiment, the receiving device 2 may use a first signal estimation unit 212a as the signal estimation unit 212. Alternatively, the receiving device 2 may use a second signal estimation unit 212b, which has a different configuration and operation compared to the first signal estimation unit 212a, as the signal estimation unit 212, instead of the first signal estimation unit 212a. Therefore, hereinafter, the first signal estimation unit 212a and the second signal estimation unit 212b will be described in order. <2-1> First signal estimation unit 212a First, the first signal estimation unit 212a will be described. <2-1-1> Configuration of the first signal estimation unit 212a

[0043] First, the configuration of the first signal estimation unit 212a will be described with reference to Fig. 6. Fig. 6 is a block diagram showing the configuration of the first signal estimation unit 212a.

[0044] 6, the signal estimation unit 212a includes N signal estimation units 2121 (specifically, the signal estimation units 2121#0 to 2121#N-1), N interference signal estimation units 2122 (specifically, the interference signal generation units 2122#0 to 2122#N-1), N adders 2123 (specifically, the adders 2123#0 to 2123#N-1), and a signal output unit 2124. Note that the operations of the signal estimation units 2121#0 to 2121#N-1, the interference signal generation units 2122#0 to 2122#N-1, the adders 2123#0 to 2123#N-1, and the signal output unit 2124 will be described in detail later with reference to FIG. 7, but an overview thereof will be given below.

[0045] The signal estimation unit 2121#k estimates the received signal y and an interference signal y_interference (k) Based on and, the estimated signal xe (k) As a result, the estimated signals xe (0) Estimated signal xe from (N-1) In the following, for the sake of simplicity, the "interference signal y_interference" will be written as the "interference signal yi."

[0046] The interference signal generator 2122#k receives the estimated signals xe (0) Estimated signal xe from (N-1) Based on the estimated signal xe including (k) Generate.

[0047] The adder 2123#k adds the interference signal yi generated by the interference signal generator 2122#k from the received signal y.(k) The output of the adder 2123#k (i.e., the received signal y and the interference signal yi (k) The signal estimation unit 2121#k outputs the output of the adder 2123#k (i.e., the difference between the received signal y and the interference signal yi (k) Based on the difference between x and x, the estimated signal xe (k) Estimate.

[0048] The signal output unit 2124 outputs the estimated signals xe (0) Estimated signal xe from (N-1) Based on the estimated signal xe including the above, the signal estimation units 2121#0 to 2121#N-1 output a final estimated signal xe_final (hereinafter referred to as a "final estimated signal xef") corresponding to the final estimated value of the transmitted signal x. (0) Estimated signal xe from (N-1) The estimated signal xe including may be considered to be a tentative estimated signal. <2-1-2> Operation of the first signal estimation unit 212a to estimate the transmitted signal x

[0049] Next, an operation of the first signal estimation unit 212a to estimate the transmitted signal x will be described with reference to Fig. 7. Fig. 7 is a flowchart showing a flow of the first signal estimation unit 212a estimating the transmitted signal x.

[0050] 7 (except for step S18 described later) are performed in parallel by functional blocks to which different variables k are assigned. That is, a functional block including a signal estimation unit 2121#0, an interference signal generation unit 2122#0, and an adder 2123#0, a functional block including a signal estimation unit 2121#1, an interference signal generation unit 2122#1, and an adder 2123#1, and a functional block including a signal estimation unit 2121#N-1, an interference signal generation unit 2122#N-1, and an adder 2123#N-1 perform the operations shown in FIG. 8 in parallel.

[0051] As shown in FIG. 7, the signal estimation unit 2121#k receives, as initial information, a transmission channel matrix H and M parameters ρ(k) (0) , ρ (k) (2) , , and ρ (k) (M-1) A parameter set ρ (k) (Step S11). (k) is the estimated signal xe (k) More specifically, the parameter set ρ (k) The parameter ρ included in (k) (0) , ρ (k) (2) , , and ρ (k) (M-1) are the estimated signals xe (k) (0) , xe (k) (1) , , and xe (k) (M-1) This is a parameter that can be adjusted arbitrarily to set the estimation accuracy of

[0052] After that, the signal estimation unit 2121#k performs an initialization operation (step S12). For example, the signal estimation unit 2121#k sets a variable r to 0. The variable r is set by the signal estimation unit 2121#k when the estimated signal xe (k) This is because, as will be described later, the signal estimation unit 2121#k estimates the estimated signal xe (k) This is because the operation of estimating xe is repeated as necessary. Therefore, in the following, the estimated signal xe estimated by the signal estimation unit 2121#k for the (r+1)th time is (k) "Estimated signal xe r+1 (k) For example, the signal estimation unit 2121#k estimates the interference signal yi (k) For convenience of explanation, the initial value of the estimated signal xe is set to zero. r+1 (k) The interference signal yi used to estimate (k) "interference signal yi r (k) In this case, the interference signal yi (k)The initial value of the interference signal yi0 (k) For example, the signal estimation unit 2121#k estimates the estimated signal xe (k) The internal data v used by the signal estimation unit 2121#k to estimate (k) and z (k) For convenience of explanation, the initial value of the estimated signal xe is set to zero. r+1 (k) The internal data v used to estimate (k) and z (k) "Internal Data v r (k) and z r (k) In this case, the internal data v (k) and z (k) The initial value of "Internal data v0 (k) and z0 (k) For example, the signal estimation unit 2121#k estimates the estimated signal xe (k) The internal matrix A used by the signal estimation unit 2121#k to estimate (k) is set based on the formula 3. Note that "H (k) " is a matrix of MN rows and M columns consisting of the k-th column block of the transmission channel matrix. Also, "D(ρ (k) )” is a function of M parameters ρ (k) (0) , ρ (k) (2) , , and ρ (k) (M-1) This shows a diagonal matrix of M rows and M columns with diagonal elements

[0053]

number

[0054] Thereafter, the signal estimation unit 2121#k estimates the parameter set ρ (k) The transmission path matrix H obtained in step S11, the received signal y, and the interference signal yi r (k) and internal data v r (k)and internal data z r (k) and the internal matrix A set in step S12 (k) Based on and, the estimated signal xe r+1 (k) Specifically, the signal estimation unit 2121#k estimates the estimated signal xe using Equation 4 (step S13). r+1 (k) (Step S13). Note that "y-yi r (k) " corresponds to the output of the adder 2123#k. When step S13 is performed for the first time, the variable r is initialized to zero, so that the signal estimation unit 2121#k estimates the interference signal yi0 (k) and the internal data v0 set in step S12 (k) and the internal data z0 set in step S12 (k) Based on and, the estimated signal xe1 (k) The second term on the right side of Equation 4 is a term based on the Lagrange multiplier method that can be used to solve a constrained optimization problem. This second term does not necessarily have to be used. In this case, the internal data v r (k) and z r (k) also no longer needs to be used.

[0055]

number

[0056] After that, the signal estimation unit 2121#k judges whether or not the number obtained by adding 1 to the variable r is smaller than the predetermined threshold value R (step S14). As described above, the variable r is calculated by the signal estimation unit 2121#k based on the estimated signal xe r+1 (k) Specifically, the number of times that the signal estimation unit 2121#k has performed the operation of estimating the estimated signal xe r+1 (k)The predetermined threshold R indicates the number of times the signal estimation unit 2121#k has performed the operation of estimating the estimated signal xe r+1 (k) This is a preset value as the number of times that the operation of estimating the number of times should be performed.

[0057] As a result of the determination in step S14, when it is determined that the number obtained by adding 1 to the variable r is smaller than the predetermined threshold value R (step S14: Yes), the signal estimation unit 2121#k calculates the estimated signal xe r+1 (k) That is, the signal estimation unit 2121#k re-estimates the estimated signal xe r+2 (k) is newly estimated.

[0058] Estimated signal xe r+1 (k) In order to re-estimate, the signal estimation unit 2121#k estimates the latest estimated signal xe r+1 (k) Based on the internal data v r (k) and z r (k) (step S15). That is, the signal estimation unit 2121#k updates the internal data v r+1 (k) and z r+1 (k) Specifically, the signal estimation unit 2121#k generates the internal data z r+1 (k) In addition, the symbol "Π s “(w)” is a symbol for indicating a signal pattern of a transmission signal x that has the closest distance (Euclidean distance) to the signal pattern of the signal w among all signal patterns that the transmission signal x can have. Then, the signal estimation unit 2121#k calculates the internal data v r+1 (k) Generate.

[0059]

number

[0060]

number

[0061] In parallel with or before or after the operation of step S15, the interference signal generator 2122#k generates the latest estimated signal xe estimated by each of the N signal estimators 2121#0 to 2121#N-1 in step S13. r+1 (0) From xe r+1 (N-1) Based on this, the interference signal yi r (k) (Step S16). That is, the interference signal generator 2122#k updates the interference signal yi r+1 (k) Specifically, the interference signal generator 2122#k generates the interference signal yi r+1 (k) That is, the interference signal generator 2122#k generates N-1 column blocks excluding the k-th column block corresponding to the k-th transmission signal group from the N column blocks constituting the transmission channel matrix H, and the estimated signal xe r+1 (k) N-1 estimated signals xe excluding r+1 (s) (where s is a variable indicating an integer greater than or equal to 0 and less than or equal to N-1, excluding k), r+1 (k) For this purpose, the intermediate matrix Ht (k) Then, the estimated signal xe r+1 (k) N-1 estimated signals xe excluding r+1 (s) The intermediate signal xt r+1 (k) Then, Equation 7 can be expressed as Equation 8. Note that the matrix Ht (k) is a matrix with MN rows and (MN-M) columns. Also, the intermediate signal xt r+1 (k)is a (MN-M)-dimensional vector.

[0062]

number

[0063]

number

[0064] After that, the signal estimation unit 2121#k increments the variable r by 1 (step S17), and then calculates the estimated signal xe r+1 (k) That is, the signal estimation unit 2121#k re-estimates (i.e., updates) the parameter set ρ (k) The transmission path matrix H obtained in step S11, the received signal y, and the interference signal yi generated in step S16 r (k) and the internal data v updated in step S15 r (k) and the internal data z updated in step S15 r (k) Based on and, the estimated signal xe r+1 (k) Here again, the signal estimation unit 2121#k re-estimates the estimated signal xe using the above-mentioned Equation 4 (step S13). r+1 (k) Re-estimate.

[0065] The above operations from step S13 to step S17 are repeated until it is determined that the number obtained by adding 1 to the variable r is not smaller than the predetermined threshold value R. That is, the operations from step S13 to step S17 are repeated R-1 times.

[0066] As a result of the determination in step S14, when it is determined that the number obtained by adding 1 to the variable r is not smaller than the predetermined threshold value R (step S14: No), the signal estimation unit 2121#k calculates the estimated signal xe r+1 (k)In this case, the signal estimation unit 2121#k does not need to re-estimate the last estimated signal xe r+1 (k) (=xe R (k) ) to the signal output unit 2124. The signal output unit 2124 outputs the estimated signals xe R (0) Estimated signal xe from R (N-1) Specifically, the signal output unit 2124 uses Equation 9 to output the definite estimated signal xef based on the estimated signal xe including the transmitted signal x (k) The final confirmed estimate signal xef (k) (Step S18). That is, the signal output unit 2124 outputs the transmission signal x (k) Among all possible signal patterns, the estimated signal xe R (k) A transmission signal x having a signal pattern that is closest to the signal pattern of (k) , the definite estimated signal xef (k) As a result, the signal output unit 2124 outputs the definite estimated signal xef (0) From the confirmed estimated signal xef (N-1) In other words, the signal output unit 2124 outputs, as the definite estimated signal xef, the transmitted signal x having one signal pattern that has the shortest distance (Euclidean distance) from the signal pattern of the estimated signal xe among all signal patterns that the transmitted signal x can have.

[0067]

number

[0068] As shown in the above-mentioned formulas 3 and 4, the signal estimation unit 212a uses not only the diagonal block components of the transmission channel matrix H but also the non-diagonal block components of the transmission channel matrix H to estimate the transmission signal x (i.e., to estimate the estimated signal xe). Therefore, the signal estimation unit 212a can estimate the transmission signal x even when the transmission channel matrix H is not a block diagonal matrix.

[0069] Furthermore, even if the transmission channel matrix H is not a block diagonal matrix, the received signal y (k) and interference signal yi r (k) Based on the difference between the transmitted signal x (k) Since is estimated, the transmitted signal x (k) The estimation accuracy of the interference signal yi remains relatively high. r (k) is the intermediate matrix Ht obtained by removing the k-th column block from the transmission channel matrix H. (k) and the estimated signal xe r+1 (k) N-1 estimated signals xe excluding r+1 (s) Therefore, the interference signal yi r (k) is the transmitted signal x (k) This shows information about the transmission signal components contained in the received signal y other than the (k) and interference signal yi r (k) The difference between the received signal y and the transmitted signal x is essentially (k) Therefore, the signal estimation unit 212a estimates the transmitted signal x (k) Based on the received signal y, which excludes information about the transmitted signal components other than (k) As a result, the signal estimation unit 212a estimates the transmitted signal x (k) The received signal y is based on the transmitted signal x without removing any information about the transmitted signal components other than (k) Compared to when the transmitted signal x is estimated, (k)can be estimated with high accuracy. Therefore, the estimation accuracy of the transmitted signal x by the signal estimation unit 212a is higher than the estimation accuracy of the transmitted signal x using Equation 1. In some cases, the estimation accuracy of the transmitted signal x by the signal estimation unit 212a is high enough to approach the estimation accuracy of the transmitted signal x using the exhaustive search method.

[0070] Furthermore, as shown in Equation 3, the inner matrix A (k) Since H is a matrix of M rows by M columns, the size of the inverse matrix calculated by the signal estimation unit 212a is the same as the size of the inverse matrix calculated to estimate the transmission signal x using the above-mentioned Equation 2 (i.e., to estimate the transmission signal x using the diagonal block components of the transmission channel matrix H). Therefore, the amount of calculation required for the signal estimation unit 212a to estimate the transmission signal x is less than the amount of calculation required to estimate the transmission signal x using the above-mentioned Equation 1. Specifically, in order to perform the matrix multiplication and inverse matrix calculation shown in Equation 3, the signal estimation unit 212a calculates (M 3 +M 2 N) × N, and in order to perform the matrix multiplication shown in Equation 4, the amount of calculations required is proportional to (M 2 +M 2 On the other hand, in order to estimate the transmitted signal x using the above-mentioned formula 1, the amount of calculations required is proportional to (MN) 3 +2(MN) 2 In the situation where M=4, N=16 and R=4, the amount of computation required by the signal estimation unit 212a is reduced to less than 10% of the amount of computation required to estimate the transmitted signal x using Equation 1.

[0071] In an ideal environment in which the transmitting antenna 10 and the receiving antenna 20 are arranged axially symmetrically, the above-mentioned parameter set ρ (k) is the signal-to-noise power ratio σ (k) If the signal estimation unit 2121#k estimates the estimated signal xe (k) is the estimated signal xe estimated using Equation 2 (k) Therefore, the estimated signal xe(k) The accuracy of the estimated signal xe estimated using Eq. (k) Alternatively, the signal estimation unit 2121#k may estimate the estimated signal xe (k) If the predetermined threshold R indicating the number of times to estimate is set to 1, the amount of calculations required for the signal estimation unit 212a to estimate the transmitted signal x is reduced to the amount of calculations required to estimate the transmitted signal x using Equation 2. <2-2> Second signal estimation unit 212b Next, the second signal estimation unit 212b will be described. <2-2-1> Configuration of the second signal estimation unit 212b

[0072] First, the configuration of the second signal estimation unit 212b will be described with reference to Fig. 8. Fig. 8 is a block diagram showing the configuration of the second signal estimation unit 212b.

[0073] As shown in FIG. 8, the signal estimation unit 212a includes N×R basic arithmetic units 2125, R−1 selection output units 2126, and N signal output units 2127. The N×R basic arithmetic units 2125 are arranged in a matrix of N rows and R columns. In the example shown in FIG. 8, the N×R basic arithmetic units 2125 are arranged in a row direction such that N arithmetic blocks 2128 are arranged in a row direction, with R basic arithmetic units 2125 each capable of estimating an estimated signal xe arranged in a column direction. Hereinafter, the basic arithmetic unit 2125 arranged in the k+1th row and r+1th column is referred to as a “basic arithmetic unit 2125(k, r)”. Note that in the above-mentioned first signal estimation unit 212a, the variable r is a value obtained by the signal estimation unit 2121#k estimating the estimated signal xe. (k) In the second signal estimation unit 212b, the variable r is used as a variable indicating the arrangement position of the basic arithmetic section 2125. Therefore, the variable r is a variable indicating an integer not less than 0 and not more than R-1. Note that the operations of the basic arithmetic section 2125, the selection output section 2126, and the signal output section 2127 will be described in detail later with reference to Fig. 9, but an overview thereof will be given below.

[0074] The R basic arithmetic units 2125(k,0) to 2125(k,R−1) arranged in the k+1th row each generate an estimated signal xe1 (k) Estimated signal xe from R (k) That is, the basic arithmetic unit 2125(k,r) arranged in the (k+1)th row and the (r+1)th column estimates the estimated signal xe r+1 (k) Specifically, the basic arithmetic unit 2125(k,r) estimates the estimated signal xe r (k) N-1 estimated signals xe excluding r (s) The intermediate signal xt r (k) and internal data v r (k) and z r (k) and common information D used in common by R basic arithmetic units 2125(k,0) to 2125(k,R−1) arranged in the k+1th row. (k) Based on and, the estimated signal xe r+1 (k) Furthermore, the basic arithmetic unit 2125(k, r) estimates the internal data v r+1 (k) and z r+1 (k) Generate.

[0075] The R-1 selection output units 2126 include selection output units 2126(1) to 2126(R-1). The selection output unit 2126(r) outputs N estimated signals xe estimated by the N basic arithmetic units 2125(k, r-1) arranged in the r-th column. r (0) From xe r (N-1) The selection output unit 2126(r) receives the estimated signal xe r (k) N-1 estimated signals xe excluding r (s) The intermediate signal xt r (k) to the basic arithmetic unit 2125(k, r).

[0076] The N signal output units 2127 include signal output units 2127(0) to 2127(N-1). The signal output unit 2127(k) outputs the estimated signal xe R (k) The signal output unit 2127(k) receives the estimated signal xe R (k) Based on the transmitted signal x (k) The final confirmed estimate signal xef (k) Output. <2-2-2> Operation of the second signal estimation unit 212b to estimate the transmitted signal x

[0077] Next, an operation of the second signal estimation unit 212b estimating the transmitted signal x will be described with reference to Fig. 9. Fig. 9 is a flowchart showing a flow of the second signal estimation unit 212b estimating the transmitted signal x.

[0078] As shown in FIG. 9, the signal estimation unit 212b acquires a transmission channel matrix H as initial information (step S21). The acquired information on the transmission channel matrix H is included in the common information D (k) to the basic arithmetic unit 2125(k, r).

[0079] Furthermore, the signal estimation unit 212b estimates M parameters ρ r+1 (k) (0) , ρ r+1 (k) (2) , , and ρ r+1 (k) (M-1) A parameter set ρ r+1 (k) (Step S21). r+1 (k) is the estimated signal xe r+1 (k) More specifically, the parameter set ρ r+1 (k) The parameter ρ included in r+1 (k) (0) , ρ r+1(k) (2) , , and ρ r+1 (k) (M-1) are the estimated signals xe r+1 k) (0) , xe r+1 (k) (1) , , and xe r+1 (k) (M-1) These are parameters that can be adjusted arbitrarily to set the estimation accuracy of ρ. r+1 (k) is used by the basic arithmetic unit 2125(k, r). The signal estimation unit 212b uses such a parameter set ρ r+1 (k) In other words, the signal estimation unit 212b obtains R×N parameter sets ρ1 (0) From the parameter set ρ R (N-1) The obtained parameter set ρ r+1 (k) is stored in the basic arithmetic part 2125(k, r). Furthermore, the signal estimation unit 212b stores the parameter set ρ (k) From ρ R (k) The initial value of the parameter set ρ0 (k) According to the possible values ​​of the variable k, N parameter sets ρ are obtained. Therefore, the signal estimation unit 212b obtains (R+1)×N parameter sets ρ.

[0080] Furthermore, the signal estimation unit 212b uses a predetermined nonlinear function Ψ as initial information. r (k) The nonlinear function Ψ is obtained in R×N units according to the possible values ​​of the variable r and the variable k (step S21). r (k) The basic arithmetic unit 2125(k, r) calculates the internal data v r+1 (k) and z r+1 (k) The obtained nonlinear function Ψ r (k)is stored in the basic arithmetic unit 2125(k, r). Furthermore, the signal estimation unit 212b stores the nonlinear function Ψ R (k) The nonlinear function Ψ is obtained in N numbers according to the possible values ​​of the variable k (step S21). R (k) The signal output unit 2127(k) outputs the definite estimated signal xef (k) The obtained nonlinear function Ψ r (k) is stored in signal output unit 2127(k).

[0081] After that, the signal estimation unit 212b performs an initialization operation (step S22). For example, the signal estimation unit 212b sets a variable r to 0. Also, for example, the signal estimation unit 212b calculates the estimated signal xe (k) The initial value of xe0 (k) may be set to zero. That is, the signal estimation unit 212b may set the estimated signal xe (0) From xe (N-1) The initial value of xe0 (0) From xe (N-1) Also, for example, the signal estimation unit 212b sets the internal data v r (k) The initial value of v0 (k) and internal data z r (k) The initial value z0 (k) The initial value of xe0 (k) That is, the signal estimation unit 212b sets the internal data v r (0) From v r (N-1) The initial value of v0 (0) From v0 (N-1) and internal data z r (0) From z r (N-1) The initial value z0 (0) From z0 (N-1) and are set to zero. Furthermore, the signal estimation unit 212b sets the estimated signal xe r+1 (k) The internal matrix A used by the basic arithmetic unit 2125(k, r) to estimate (k)That is, the signal estimation unit 212b sets the inner matrix A (0) From A (N-1) Set the internal matrix. (k) For information on this, see Common Information D. (k) to the basic arithmetic unit 2125(k, r).

[0082]

number

[0083] Thereafter, the basic calculation unit 2125(k, r) calculates the parameter set ρ r+1 (k) The transmission channel matrix H obtained in step S11, the received signal y, and the estimated signal xe r (k) The intermediate signal xt generated from r (k) , internal data v r (k) and internal data z r (k) and the internal matrix A set in step S22 (k) Based on and, the estimated signal xe r+1 (k) Specifically, the basic arithmetic unit 2125(k,r) estimates the estimated signal xe using Equation 11. r+1 (k) (Step S23). When step S23 is performed for the first time, the variable r is initialized to zero, so the basic arithmetic unit 2125(k,0) estimates the estimated signal xe0 set in step S22. (k) and the internal data v0 set in step S22 (k) and the internal data z0 set in step S22 (k) Based on and, the estimated signal xe1 (k) The information about the received signal y is the common information D (k)may be output to the basic arithmetic unit 2125(k,r) as: Note that the second term on the right side of Equation 11 is a term based on the Lagrange multiplier method that can be used to solve a constrained optimization problem. This second term does not necessarily have to be used. In this case, the internal data v r (k) and z r (k) also no longer needs to be used.

[0084]

number

[0085] Based on Equation 11, the estimated signal xe r+1 (k) An example of the configuration of the basic arithmetic unit 2125(k,r) that estimates the estimated signal xe is shown in FIG. r+1 (k) As a processing block for estimating ρ, the basic calculation unit 2125(k, r) includes a memory device 2125S, a register 2125R1, a register 2125R2, a register 2125R3, a register 2125R4, a register 2125R5, a register 2125R6, a multiplier 2125M1, a multiplier 2125M2, a multiplier 2125M3, an adder 2125A1, and an adder 2125A2. r+1 (k) The register 2125R1 stores the intermediate signal xt r (k) The register 2125R1 receives the intermediate signal xt r (k) The register 2125R2 can temporarily hold the common information D (k) The information about the transmission channel matrix H included in (k) †H (k) " matrix is ​​input. The register 2125R2 stores the input "H (k) †H (k) The register 2125R3 can temporarily hold a matrix of common information D (k) The information about the transmission channel matrix H included in(k) †y" matrix is ​​input. Register 2125R3 stores the input "H (k) The register 2125R4 can temporarily hold a matrix called "†y". (k) The information contained in the internal matrix A (k) The register 2125R4 stores the input inner matrix A (k) The register 2125R5 can temporarily hold the internal data z r (k) The register 2125R5 stores the input internal data z r (k) The register 2125R6 can temporarily hold the internal data v r (k) The register 2125R6 stores the input internal data v r (k) The multiplier 2125M1 can temporarily hold the intermediate signal xt r (k) and "H (k) †H (k) The adder 2125A1 multiplies the internal data z r (k) and the internal data v input to register 2125R6 r (k) The multiplier 2125M2 performs an addition process of adding together the parameter set ρ r+1 (k) The adder 2125A2 multiplies the "H (k) The multiplier 2125M3 performs an addition process of subtracting the output of the multiplier 2125M1 from the result of adding the matrix "y" and the output of the multiplier 2125M2. (k) The output of the multiplier 2125M3 is multiplied by the output of the adder 2125A2. r+1 (k) is equivalent to.

[0086] The basic arithmetic unit 2125(k,r) further includes an adder 2125A3, an adder 2125A4, an adder 2125A5, and a calculator 2125C. These processing blocks mainly calculate the internal data v r+1 (k) and z r+1 (k) This will be described in detail later.

[0087] Thereafter, the signal estimation unit 212b judges whether the number obtained by adding 1 to the variable r is smaller than a predetermined threshold value R (step S24). The variable r is calculated by multiplying the estimated signal xe r+1 (k) Therefore, the operation of determining whether the number obtained by adding 1 to the variable r is smaller than the predetermined threshold R is essentially performed by the basic operation unit 2125(k,R−1) in the last column of each operation block 2128 estimating the estimated signal xe R (k) It can be said that this is equivalent to an operation of determining whether or not the above has been estimated.

[0088] As a result of the determination in step S24, if it is determined that the number obtained by adding 1 to the variable r is smaller than the predetermined threshold value R (step S14: Yes), the estimated signal xe r+1 (k) The basic calculation unit 2125(k,r+1) in the next column after the basic calculation unit 2125(k,r) that estimated r+2 (k) Estimate.

[0089] In this case, the basic calculation unit 2125(k, r) calculates the latest estimated signal xe r+1 (k) Based on the internal data v r+1 (k) and z r+1 (k) Specifically, the basic arithmetic unit 2125(k, r) generates the internal data z r+1 (k)Then, the basic arithmetic unit 2125(k, r) generates the internal data v r+1 (k) Generate.

[0090]

number

[0091]

number

[0092] In Equation 12, "Ψ(w)" means performing a nonlinear transformation process on a signal (=vector) w that contains M signal components. r (k) An example of the nonlinear function Ψ shown in Equation 14 is given below. r (k) is the M signal components (w0, w1, . . . , w M-1 ), parameters (a0, a1, . . . , a M-1 ) and (b0, b1, . . . , b M-1 11(a) to 11(c) are respectively performed using the nonlinear function Ψ r (k) An example of the nonlinear function Ψ shown in FIG. r (k) and the nonlinear function Ψ shown in Fig. 11(b) r (k) and the nonlinear function Ψ shown in Fig. 11(c) r (k) is the parameter (a0, a1, . . . , a M-1 ) and (b0, b1, . . . , b M-1 ) are at least partially different.

[0093]

number

[0094] Based on formulas 12 and 13, the internal data z r+1 (k) and v r+1 (k) An example of the configuration of the basic arithmetic unit 2125(k, r) that generates the internal data z r+1 (k) and v r+1 (k) The basic arithmetic unit 2125(k,r) includes an adder 2125A3, an adder 2125A4, an adder 2125A5, and a calculator 2125C as a processing block for generating the internal data v r (k) The calculator 2125C performs subtraction processing to subtract the nonlinear function Ψ r (k) The output of the adder 2125A3 is subjected to a nonlinear conversion process using the internal data z r+1 (k) The adder 2125A4 performs a subtraction process to subtract the output of the calculator 2125C from the output of the multiplier 2125M3. The adder 2125A5 subtracts the internal data v r (k) The output of the adder 2125A5 is the internal data v r+1 (k) is equivalent to.

[0095] After that, the variable r is incremented by 1 (step S27), and then the basic arithmetic unit 2125(k, r) in the next column calculates the estimated signal xe r+1 (k) That is, the basic calculation unit 2125(k, r) newly estimates the parameter set ρ r (k) The transmission channel matrix H obtained in step S21, the received signal y, and the internal data v generated in step S25. r (k) and the internal data z generated in step S25 r(k) and the intermediate signal xt r (k) Based on and, the estimated signal xe r+1 (k) Here, the signal estimation unit 2121#k also estimates the estimated signal xe using the above-mentioned Equation 11 (step S23). r+1 (k) Re-estimate.

[0096] The above operations from step S23 to step S27 are repeated until it is determined that the number obtained by adding 1 to the variable r is not smaller than the predetermined threshold value R. In other words, the operations from step S23 to step S27 are repeated R−1 times. However, as can be seen from the configuration of the actual signal estimation unit 212b shown in FIG. 8, in reality, the estimated signal xe is calculated by R basic arithmetic units 2125(k,0) to 2125(k,R−1) included in each arithmetic block 2128. r+1 (k) That is, the second signal estimation unit 212b estimates the estimated signal xe r+1 (k) The estimation signal xe is a pipeline process realized by the basic arithmetic units 2125(k,0) to 2125(k,R−1). r+1 (k) It can be said that the second signal estimation unit 212b is different from the first signal estimation unit 212a in that the process of estimating the estimated signal xe is a loop process. r+1 (k) Although the process of estimating the estimated signal xe is described in the form of a loop process, in reality, the signal estimation unit 212b r+1 (k) In other words, the signal estimation unit 212b outputs the estimated signal xe to the basic arithmetic units 2125(k, 0) to 2125(k, R−1) without making the decision in step S24 based on the variable r. r+1 (k) Alternatively, the process of estimating the vectors may be performed sequentially.

[0097] On the other hand, if it is determined in step S24 that the number obtained by adding 1 to the variable r is not smaller than the predetermined threshold value R (step S24: No), the basic arithmetic unit 2125(k, R−1) in the last column of each arithmetic block 2128 calculates the estimated signal xe R (k) In this case, the signal output unit 2127(k) outputs the estimated signal xe R (k) Based on this, the definite estimated signal xef (k) Specifically, the signal output unit 2127(k) uses Equation 15 to output the transmission signal x (k) The final confirmed estimate signal xef (k) As a result, the definite estimated signals xef are output from the N signal output units 2127(0) to 2127(N-1) respectively. (0) From xef (N-1) A definite estimate signal xef comprising:

[0098]

number

[0099] The signal estimation unit 212b can achieve the same effect as the signal estimation unit 212a. For example, the signal estimation unit 212a can estimate the transmission signal x even when the channel matrix H is not a block diagonal matrix. Furthermore, the intermediate signal xt r (k) and the intermediate matrix Ht (k) The multiplication result (= interference signal yi r (k) ) and the received signal y (k) Based on the difference between the transmitted signal x (k) Since is estimated, the transmitted signal x by the signal estimation unit 212b (k)The estimation accuracy of x is maintained relatively high, similar to that of the signal estimation unit 212a. Furthermore, the amount of calculation required for the signal estimation unit 212b to estimate the transmitted signal x is less than the amount of calculation required for estimating the transmitted signal x using Equation 1 above. <4> Variations

[0100] If the signal estimation unit 212 is the second signal estimation unit 212b, the communication system SYS selects the parameter set ρ r+1 (k) and the nonlinear function Ψ r (k) (For example, the nonlinear function Ψ r (k) The above parameters (a0, a1, . . . , a M-1 ) and (b0, b1, . . . , b M-1 For example, as shown in FIG. 12 showing a modified example of the communication system SYS (hereinafter, referred to as a “communication system SYSmod”), the communication system SYSmod includes a parameter set ρ r+1 (k) and the nonlinear function Ψ r (k) The receiving device 2 may include a learning device 4mod capable of learning at least a part of the above. The learning device 4mod may be disposed outside the receiving device 2, or may be disposed inside the receiving device 2. The learning device 4mod may be a processing block realized in the signal processing device 21 of the receiving device 2.

[0101] The learning device 4mod estimates the parameter set ρ using a loss function Loss based on an error (for example, a square error) between the deterministic estimated signal xef output by the signal estimation unit 212 and the transmission signal x actually transmitted by the transmission device 1. r+1 (k) and the nonlinear function Ψ r (k) In this case, the learning device 4mod may learn the parameter set ρ by using the backpropagation method used for learning the parameters of the neural network. r+1 (k)and the nonlinear function Ψ r (k) Equation 16 can be used to learn the parameter set ρ r+1 (k) and the nonlinear function Ψ R (k) 16 shows an example of a loss function Loss based on the square error between the deterministic estimation signal xef and the transmitted signal x for learning. Note that "B" in Equation 16 represents the parameter set ρ r+1 (k) and the nonlinear function Ψ R (k) , which indicates a set of transmitted signals x used to learn

[0102]

number

[0103] The loss function Loss calculated by Equation 16 is used to determine the learning target (for example, the parameter set ρ r+1 (k) and the nonlinear function Ψ R (k) The influence of the learning object on the learning process (at least one of the parameters) can be expressed by a partial differential that can be calculated by the backpropagation method. Therefore, the learning device 4mod may learn the learning object by using the formula 17. The formula 17 is used when the learning object is a parameter set ρ r+1 (k) In the formula 17, "ε" represents a hyperparameter that can be set arbitrarily.

[0104]

number

[0105] The present invention can be modified as appropriate within the scope that does not contradict the gist or concept of the invention that can be read from the claims and the entire specification, and the signal estimation device, signal estimation method, and computer program involving such modifications are also included in the technical concept of the present invention. [Explanation of symbols]

[0106] 1. Transmitting device 11 Signal Processing Device 2. Receiving device 21 Signal Processing Device 211 Conversion Unit 212 Signal Estimation Unit SYS Communication System x Transmission signal y Received signal

Claims

1. a transmitting device which uses a transmitting antenna in which M (M is an integer equal to or greater than 1) transmitting array antennas are arranged concentrically, the transmitting array antennas including N (N is an integer equal to or greater than 1) transmitting antenna elements arranged at equal intervals on a circle, divides M×N transmitting signals contained in a transmitting signal x including N transmitting signal groups each composed of M transmitting signal components transmitted by the M transmitting array antennas different from each other, into M signal series each including N transmitting signals, and transmits a transmitting signal x′ obtained by performing an inverse discrete Fourier transform process on each of the M signal series; a receiving device that receives the transmission signal x' transmitted by the transmitting device as a received signal y using a receiving antenna in which M receiving array antennas, each of which includes N receiving antenna elements arranged at equal intervals on a circle, are arranged concentrically; In a communication system comprising: a signal estimation device for estimating the transmitted signal x from the received signal y, The signal estimation device comprises: a transform means for performing a discrete Fourier transform process on M×N received signal components included in the received signal y and received by the M×N receiving antenna elements, respectively, in units of N received signal components received by each of the M receiving array antennas; an estimation means for estimating an estimated signal xe including M×N estimated signal components which are estimates of the M×N transmitted signal components, based on the received signal y which has been subjected to the discrete Fourier transform processing; Equipped with When the estimated signal xe is newly estimated, the estimation means derives, from the newly estimated estimated signal xe, estimates xe of M pieces of the transmitted signal components constituting the k-th (where k is a variable indicating an integer not less than 0 and not more than N-1)-th transmitted signal group. （ｋ） and performing an exclusion operation to exclude intermediate signal xt （ｋ） and the estimated value xe based on the received signal y. （ｋ） The estimated signal xe is re-estimated by updating Signal estimator.

2. When the estimated signal xe is newly estimated, the estimation means estimates a component H corresponding to the k-th transmission signal group in a transmission channel matrix H indicating a state of a transmission channel between the receiving antenna and the transmitting antenna. （ｋ） The intermediate matrix Ht （ｋ） and the intermediate signal xt （ｋ） By multiplying it with （ｋ） and the received signal y and the interference signal yi （ｋ） The estimated value xe （ｋ） The estimated signal xe is re-estimated by updating 2. A signal estimation device according to claim 1.

3. The estimation means estimates the intermediate matrix Ht （ｋ） and the intermediate signal xt （ｋ） By multiplying this, the interference signal yi （ｋ） The interference signal generating means includes N interference signal generating means that generate the interference signal, the N interference signal generating means being in accordance with the variable k. The estimation means estimates the interference signal yi generated by a corresponding one of the N interference signal generation means. （ｋ） and the estimated value xe （ｋ） The number of update means for updating is N, in accordance with the variable k.

3. A signal estimation device according to claim 2.

4. The estimation means includes: A parameter set ρ including M parameters corresponding to the k-th transmission signal group. （ｋ） and the transmission channel matrix H, the estimated value xe （ｋ） The inner matrix A used to generate （ｋ） and the estimated value xe （ｋ） The internal data v used to estimate （ｋ） and z （ｋ） and the interference signal yi （ｋ） performing a first operation for initializing After performing the first operation, the parameter set ρ （ｋ） the received signal y, the transmission channel matrix H, and the internal matrix A （ｋ） and the initialized interference signal yi （ｋ） and the initialized internal data v （ｋ） and z （ｋ） Based on the above, the estimated value xe （ｋ） performing a second operation of estimating the estimated signal xe by generating After performing the second operation, each time the estimated signal xe is newly estimated, (i) the internal data v is calculated based on the newly generated estimated signal xe. （ｋ） and z （ｋ） (ii) a first process of updating the intermediate matrix Ht （ｋ） and the intermediate signal xt obtained from the newly generated estimated signal xe. （ｋ） Based on the above, the interference signal yi （ｋ） (iii) a second process of generating a new parameter set ρ （ｋ） the received signal y, the transmission channel matrix H, and the internal matrix A （ｋ） and the updated internal data v （ｋ） and z （ｋ） and the newly generated interference signal yi （ｋ） Based on the above, the estimated value xe （ｋ） and performing a third operation including a third process of re-estimating the estimated signal xe by updating After repeating the third operation a predetermined number of times, the estimated value xe is selected from among a plurality of signal sequence candidates that can be taken by the M transmission signal components constituting the k-th transmission signal group. （ｋ） Output the signal sequence candidate that is closest to 4. A signal estimation device according to claim 2 or 3.

5. The estimation means each estimates the estimated value xe （ｋ） The estimated value xe １ （ｋ） From xe Ｒ （ｋ） The number of calculation blocks capable of estimating N is equal to the number of variables k, The kth transmission signal group is included in one calculation block, and the estimated value xe ｒ＋２ （ｋ） The r+1th (r is a variable indicating each of R integers not less than 0 and not more than R−1) arithmetic means estimating N−1 estimated values ​​xe estimated by N−1 r-th arithmetic means included in each of the N−1 arithmetic blocks excluding one arithmetic block corresponding to the k-th transmission signal group among the N arithmetic blocks. ｒ＋１ （ｓ） (where s is a variable indicating an integer greater than or equal to 0 and less than or equal to N-1, excluding k), ｒ＋２ （ｋ） Estimate 2. A signal estimation device according to claim 1.

6. The estimation means estimates a parameter set ρ corresponding to the k-th transmission signal group and including M parameters used by the r-th calculation means. ｒ＋１ （ｋ） The initial value of ρ ０ （ｋ） and the estimated value xe based on the received signal y and a transmission channel matrix H indicating the state of the transmission channel between the receiving antenna and the transmitting antenna. （ｋ） The inner matrix A used to generate （ｋ） and the estimated value xe ｒ （ｋ） The internal data v used by the r-th calculation means to estimate ｒ （ｋ） and z ｒ （ｋ） The initial value of v ０ （ｋ） and z ０ （ｋ） and the estimated value xe ｒ （ｋ） The initial value xe ０ （ｋ） Initialize and The r-th calculation means included in one calculation block corresponding to the k-th transmission signal group is The parameter set ρ ｒ＋１ （ｋ） the received signal y, the transmission channel matrix H, and the internal matrix A （ｋ） and the internal data v ｒ （ｋ） and z ｒ （ｋ） and the estimated value xe ｒ （ｓ） Based on the above, the estimated value xe ｒ＋１ （ｋ） Estimate The estimated value xe ｒ＋１ （ｋ） and the internal data v ｒ （ｋ） and z ｒ （ｋ） and a given nonlinear function Ψ ｒ （ｋ） Based on the internal data v ｒ＋１ （ｋ） and z ｒ＋１ （ｋ） Generate 6. A signal estimation device according to claim 5.

7. The parameter set ρ ｒ （ｋ） is learned by a learning operation using a loss function based on the error between the transmission signal x actually transmitted by the transmission device and the estimated signal xe actually estimated by the estimation means.

7. A signal estimation device according to claim 6.

8. a transmitting device which uses a transmitting antenna in which M (M is an integer equal to or greater than 1) transmitting array antennas are arranged concentrically, the transmitting array antennas including N (N is an integer equal to or greater than 1) transmitting antenna elements arranged at equal intervals on a circle, divides M×N transmitting signals contained in a transmitting signal x including N transmitting signal groups each composed of M transmitting signal components transmitted by the M transmitting array antennas different from each other, into M signal series each including N transmitting signals, and transmits a transmitting signal x′ obtained by performing an inverse discrete Fourier transform process on each of the M signal series; a receiving device that receives the transmission signal x' transmitted by the transmitting device as a received signal y using a receiving antenna in which M receiving array antennas, each of which includes N receiving antenna elements equally spaced on a circle, are arranged concentrically; A signal estimation method for estimating the transmitted signal x from the received signal y in a communication system comprising: The signal estimation method includes: a transform step of performing a discrete Fourier transform process on M×N received signal components included in the received signal y and received by the M×N receiving antenna elements, respectively, in units of N received signal components received by each of the M receiving array antennas; an estimation step of estimating an estimated signal xe including M×N estimated signal components that are estimates of the M×N transmitted signal components, based on the received signal y that has been subjected to the discrete Fourier transform processing; Including, When the estimated signal xe is newly estimated, the estimation step includes deriving, from the newly estimated estimated signal xe, estimates xe of M pieces of the transmitted signal components constituting the k-th (where k is a variable indicating an integer not less than 0 and not more than N-1)-th transmitted signal group. （ｋ） A first step of excluding the intermediate signal xt （ｋ） and the estimated value xe based on the received signal y. （ｋ） A second step of re-estimating the estimated signal xe by updating Signal estimation method.

9. A computer program for causing a computer to execute a signal estimation method, comprising: The signal estimation method includes: a transmitting device which uses a transmitting antenna in which M (M is an integer equal to or greater than 1) transmitting array antennas are arranged concentrically, the transmitting array antennas including N (N is an integer equal to or greater than 1) transmitting antenna elements arranged at equal intervals on a circle, divides M×N transmitting signals contained in a transmitting signal x including N transmitting signal groups each composed of M transmitting signal components transmitted by the M transmitting array antennas different from each other, into M signal series each including N transmitting signals, and transmits a transmitting signal x′ obtained by performing an inverse discrete Fourier transform process on each of the M signal series; a receiving device that receives the transmission signal x' transmitted by the transmitting device as a received signal y using a receiving antenna in which M receiving array antennas, each of which includes N receiving antenna elements equally spaced on a circle, are arranged concentrically; A signal estimation method for estimating the transmitted signal x from the received signal y in a communication system comprising: a transform step of performing a discrete Fourier transform process on M×N received signal components included in the received signal y and received by the M×N receiving antenna elements, respectively, in units of N received signal components received by each of the M receiving array antennas; an estimation step of estimating an estimated signal xe including M×N estimated signal components that are estimates of the M×N transmitted signal components, based on the received signal y that has been subjected to the discrete Fourier transform processing; Including, When the estimated signal xe is newly estimated, the estimation step includes deriving, from the newly estimated estimated signal xe, estimates xe of M pieces of the transmitted signal components constituting the k-th (where k is a variable indicating an integer not less than 0 and not more than N-1)-th transmitted signal group. （ｋ） A first step of excluding the intermediate signal xt （ｋ） and the estimated value xe based on the received signal y. （ｋ） A second step of re-estimating the estimated signal xe by updating Computer program.

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