JP4805042B2 - Wireless signal separation method, wireless receiver, program, and recording medium - Google Patents

Description

  The present invention wirelessly transmits a plurality of signal sequences on the same frequency using a MIMO (Multiple Input Multiple Output) channel and performs signal detection (or signal separation) on a spatially multiplexed signal in a wireless receiver. In particular, a radio signal separation method, a radio reception apparatus, and a program using a MIMO-OFDN communication system, which is a combination of an OFDM (Orthogonal frequency division multiplex) modulation system that is a multicarrier modulation system and a MIMO communication system, and a communication system The present invention relates to a recording medium.

  In wireless communication systems, it is essential to improve frequency utilization efficiency in order to increase the amount of communication transmission using limited frequency resources. As a technique for improving the frequency utilization efficiency, a plurality of transmission antennas are provided on the wireless transmission device side of the wireless communication system, a plurality of reception antennas are provided on the wireless reception device side, and spatial multiplexing channels are provided on the same frequency band at the same time There has been proposed a MIMO system configured to improve the information transmission rate.

  In addition, there is an OFDM multicarrier modulation scheme (hereinafter referred to as an OFDM scheme) in which an information signal is transmitted on a plurality of subcarriers orthogonal to each other. The OFDM scheme is a modulation scheme capable of flattening frequency selective fading by narrowing the band of each subcarrier, and further by multipath fading by adding a guard interval. The influence of intersymbol interference can be reduced. Accordingly, the OFDM system is widely used in wireless communication and broadcasting systems such as wireless LAN (Local Area Network) and digital television broadcasting.

A combination of the above MIMO system and the OFDM scheme is called a MIMO-OFDM system. In contrast, when a single carrier modulation scheme is simply used, it is called a MIMO-Single system. Both are unified and called a MIMO system.
A comparison of detection algorithms including BLAST for wireless communication using multiple antennas ”, Hassell, CZW; Thompson, JS; Mulgrew, B .; Grant, PM;, Personal, Indoor and Mobile Radio Communications, 2000. PIMRC 2000. The 11th IEEE International Symposium on Volume 1, 18-21 Sept. 2000 Page (s): 698-703 vol.1

By the way, in the signal detector (Signal Detector) with which the conventional radio | wireless receiver was equipped, as a signal detection method, ZF (Zero-Forcing) system, MMSE (Minimum Mean Square Error) system, SIC (Successive Interference Cancellation) system, MLD A combination of the (Maximum Likelihood Detection) method and those basic methods is used. Among these, the SIC method is excellent from the viewpoint of achieving both the reception error rate characteristics and the amount of computation required for signal detection processing. Therefore, the SIC method is considered to be a very practical approach for realizing MIMO transmission. The SIC scheme is compared with other signal detection process, rather than simultaneously, it is a process characterized to sequentially detect the T transmitted signals s _t. Here, there are two types of SIC methods: ZF standards and MMSE standards. A representative example of the ZF-SIC (ZF-based SIC method) method is a V-BLAST (Vertical Bell Laboratories Layered Space-Time) method. An MMSE-SIC (MMSE standard SIC method) has also been proposed. This method has the same required calculation amount as the ZF-SIC method, but has better error rate characteristics (that is, reception quality). It is a feature. Hereinafter, a conventional MMSE-SIC method will be described.

If the input to the signal detection device is the propagation path matrix H, the coefficient α, and the received signal vector x, and the signal output through the signal detection processing by the MMSE-SIC method is the detection signal ^ s, the signal detection device is ,
<a> For the T elements s = [s ₁ , s ₂ ,..., S _T ] in the transmission signal vector s, it has the maximum post-detection SINR (Signal to Interference plus noise ratio). Next, a transmission signal in the transmission system is determined as a signal detection target.
An extraction vector based on MMSE (minimum mean square error) for detecting the detection signal determined in <b> is calculated.
Element signals in the order determined in <a> are detected in s = [s ₁ , s ₂ ,..., S _T ] using the extraction vector generated in <c> b.
<D> Update the reception vector x and the propagation path matrix H.
Then, the signal detection apparatus repeatedly executes T times for all processes a to d.

Here, when the MMSE-SIC method, which is a conventional SIC method, is applied to process a spatially multiplexed signal in a MIMO system in a signal detection device of a wireless reception device, the following problems exist.
<Problem 1> The processing computation amount is enormous and the required computation circuit scale becomes large (T pseudo-inverse matrix computation is required, and the computation requirement amount becomes large as O (T ⁴ ). (In a MIMO system, the required amount of computation is enormous.)
<Problem 2> Increased required storage device capacity (Pseudo inverse matrix calculation requires a large storage capacity. Also, a storage device is required for updating the propagation path matrix H and storing the extracted vector)
<Problem 3> It is difficult to reduce the size and weight (in a wireless transmission device, particularly a wireless portable terminal, it is desirable to reduce the size and weight, but in the conventional MMSE-SIC method, the required arithmetic circuit scale and memory are required. (Since the device is large, it becomes difficult to reduce the size and weight of the wireless transmitter)
<Problem 4> Processing delay increases (the processing delay is large because T times of pseudo inverse matrix operations cannot be parallelized. In particular, when the number of transmission antennas is large, the number of pseudo inverse matrix operations is large. In order to solve this problem, there is a way to increase the operating clock frequency in the arithmetic circuit, which leads to a dramatic increase in power consumption)
<Problem 5> Large required power consumption (Since the required power is proportional to the required arithmetic circuit scale and its operation clock frequency, it is considered that the conventional MMSE-SIC system consumes a large amount of power. It is difficult to secure sufficient operating time for the MIMO system)
<Problem 6> Not suitable for mass production of products (Based on the above-mentioned problems 1 to 5, it is extremely difficult to mount the conventional MMSE-SIC method on a wireless receiver. That is, the conventional MMSE-SIC method is mounted. The manufacturing cost of the wireless device equipped with the MIMO system is high and is not suitable for mass production)

  Accordingly, the present invention reduces the amount of processing computation and the required computation circuit scale, thereby reducing the size and weight of a wireless communication device that performs wireless communication using a MIMO system, and reducing the processing delay and power consumption of the wireless communication device. It is an object of the present invention to provide a radio signal separation method, a radio reception device, a program, and a recording medium that can provide a radio communication device suitable for mass production.

  In order to achieve the above object, the present invention provides a wireless reception apparatus for detecting a received signal using a propagation path matrix H, a predetermined coefficient α, and a received signal vector x in a MIMO (Multiple Input Multiple Output) system. In this signal separation method, the order of signal detection is determined for T elements in the transmission signal vector s of the signal transmitted by the wireless transmission device, recorded in an order list, and transmitted. The expanded propagation path matrix H ′ calculated based on the path matrix H, the coefficient α, and the unit matrix I is rearranged according to the order list S to calculate the matrix H ″, and the matrix H ″ of R rows and T columns is calculated. QR decomposition is performed to calculate a unitary matrix Q and a triangular matrix R, filter a received vector x using a complex conjugate transpose of R rows of the matrix Q, and use the triangular matrix R to transmit the T transmission signals. Sequentially A radio signal separation method comprising: detecting, rearranging and outputting the detected T transmission signals in the original transmitted spatial order according to the order list.

The present invention also provides a radio signal separation method in a radio reception apparatus that performs signal detection of a received signal using a propagation path matrix H, a predetermined coefficient α, and a received signal vector x in a MIMO (Multiple Input Multiple Output) system, An order list in which the order of signal detection is determined for T elements in the transmission signal vector s of the signal transmitted by the wireless transmission device, calculated by G = H ′ ^H H ′ Decompose the matrix G to derive an upper triangular matrix, calculate the _l- th norm in the p-th row of the inverse matrix U of the upper triangular matrix to the power of d _l , calculate β _p, and calculate the inverse matrix U of the upper triangular matrix The β _p values are rearranged in ascending order, and numerical values obtained by the rearrangement are generated in an order list. Based on the propagation path matrix H, the coefficient α, and the unit matrix I Calculated extended channel matrix 'Is rearranged according to the order list S to calculate a matrix H ″, and the matrix H ″ of R rows and T columns is subjected to QR decomposition to calculate a unitary matrix Q and an upper triangular matrix R. Decomposition processing, filtering processing for filtering the received vector x using the complex conjugate transpose of R rows of the matrix Q, and the T transmission signals by backward substitution using the upper triangular structure of the upper triangular matrix R And a rearrangement process for sequentially detecting the T transmission signals, and a rearrangement process for rearranging and outputting the detected T transmission signals in the order of the original transmitted space according to the order list. This is a signal separation method.

Further, the present invention is the above-described radio signal separation method, wherein the rearrangement process outputs the calculated matrix H ″, the QR decomposition process outputs the matrix Q and the matrix R, and the filtering process Calculates a vector y by multiplying the complex conjugate transpose of R rows of the matrix Q and the received signal vector x, and the backward substitution process uses the column vector y and the upper triangular matrix R. , Calculating the detected transmission signal vector by backward substitution calculation processing, detecting the T elements of the detected transmission signal vector in order, calculating the interference component according to the interference component calculation formula, and calculating the k th of the column vector y A soft decision detection signal is calculated by subtracting the interference component from the element y _k, and a hard decision is performed on the soft decision detection signal based on the constellation applied at the time of modulation on the transmission side. The hard decision detection signal is calculated, and the order rearrangement process reads the detected transmission signal vector and the order list, rearranges the detected transmission signal vector according to the list, and outputs the rearrangement result. It is characterized by that.

The present invention also provides a radio signal separation method in a radio reception apparatus that performs signal detection of a received signal using a propagation path matrix H, a predetermined coefficient α, and a received signal vector x in a MIMO (Multiple Input Multiple Output) system, An order list in which the order of signal detection is determined for T elements in the transmission signal vector s of the signal transmitted by the wireless transmission device, calculated by G = H ′ ^H H ′ The matrix G is decomposed to derive a lower triangular matrix, the _l- th norm in the p-th row of the inverse matrix U of the lower triangular matrix is raised to the d ₁ power to calculate β _p, and the inverse matrix U of the lower triangular matrix is calculated The β _p values are rearranged in ascending order, and numerical values obtained by the rearrangement are generated in an order list. Based on the propagation path matrix H, the coefficient α, and the unit matrix I Calculated extended channel matrix 'Is rearranged according to the order list S to calculate a matrix H ″, and the matrix H ″ of R rows and T columns is subjected to QR decomposition to calculate a unitary matrix Q and a lower triangular matrix R. Decomposition processing, filtering processing for filtering the received vector x using complex conjugate transpose of R rows of the matrix Q, and T transmission signals by forward substitution using the lower triangular structure of the lower triangular matrix R And a rearrangement process for rearranging and outputting the detected T transmission signals in the original transmitted spatial order according to the order list. This is a signal separation method.

Further, the present invention is the above-described radio signal separation method, wherein the rearrangement process outputs the calculated matrix H ″, the QR decomposition process outputs the matrix Q and the matrix R, and the filtering process Calculates the vector y by multiplying the complex conjugate transpose of R rows of the matrix Q and the received signal vector x, and the forward substitution process uses the column vector y and the lower triangular matrix R. Then, the forward substitution calculation process calculates a detected transmission signal vector, detects T elements of the detected transmission signal vector in order, calculates an interference component according to an interference component calculation formula, and calculates the k th of the column vector y A soft decision detection signal is calculated by subtracting the interference component from the element y _k, and a hard decision is performed on the soft decision detection signal based on the constellation applied at the time of modulation on the transmission side. The hard decision detection signal is calculated, and the order rearrangement process reads the detected transmission signal vector and the order list, rearranges the detected transmission signal vector according to the list, and outputs the rearrangement result. It is characterized by that.

  The present invention also relates to a radio reception apparatus that performs signal detection of a received signal using a propagation path matrix H, a predetermined coefficient α, and a received signal vector x in a MIMO (Multiple Input Multiple Output) system, and the transmission of the radio transmission apparatus Means for determining each signal detection order for the T elements in the transmission signal vector s of the transmitted signal and recording it in the order list, the channel matrix H, the coefficient α, and the unit matrix The extended propagation path matrix H ′ calculated based on I is rearranged according to the order list S to calculate a matrix H ″, and the matrix H ″ of R rows and T columns is subjected to QR decomposition to obtain a unitary matrix Q And means for calculating the triangular matrix R, means for filtering the received vector x using the complex conjugate transpose of the R rows of the matrix Q, and detecting the T transmission signals sequentially using the triangular matrix R Means and And a means for rearranging the detected T transmission signals in the original transmitted spatial order in accordance with the order list and outputting them.

The present invention also relates to a radio reception apparatus that performs signal detection of a received signal using a propagation path matrix H, a predetermined coefficient α, and a received signal vector x in a MIMO (Multiple Input Multiple Output) system, and the transmission of the radio transmission apparatus An order list in which the order of signal detection is determined for T elements in the transmission signal vector s of the transmitted signal, and the matrix G calculated by G = H ′ ^H H ′ is decomposed. Te leads to an upper triangular matrix, the order l norm in p-th row of the inverse matrix U of the upper triangular matrix to calculate a d _l th power to beta _p, of the beta _p calculated for an inverse matrix U of the upper triangular matrix The order of values is sorted in ascending order, and the numerical value obtained by the rearrangement is generated as an order list. The expanded propagation path calculated based on the propagation path matrix H, the coefficient α, and the unit matrix I The matrix H ′ is added to the ordered list S. Accordingly, rearrangement means for calculating the matrix H ″ by rearrangement, QR decomposition means for calculating the unitary matrix Q and the upper triangular matrix R by QR decomposition of the matrix H ″ of R rows and T columns, and the matrix Q Filtering means for filtering the received vector x using the complex conjugate transpose of R rows, and backward substitution means for sequentially detecting the T transmission signals by backward substitution using the upper triangular structure of the upper triangular matrix R And an order rearranging means for rearranging and outputting the detected T transmission signals in the order of the original transmitted space according to the order list.

According to the present invention, in the above-described wireless reception device, the rearranging unit outputs the calculated matrix H ″, the QR decomposition unit outputs the matrix Q and the matrix R, and the filtering unit The vector y is calculated by multiplying the complex conjugate transpose of R rows of the matrix Q and the received signal vector x, and the backward substitution means uses the column vector y and the upper triangular matrix R, The detected transmission signal vector is calculated by the backward substitution calculation process, T elements of the detected transmission signal vector are sequentially detected, the interference component is calculated according to the interference component calculation formula, and the kth element of the column vector y A soft decision detection signal is calculated by subtracting the interference component from y _k, and a hard decision is performed on the soft decision detection signal based on the constellation applied at the time of modulation on the transmission side. A hard decision detection signal is calculated, and the order rearranging means reads the detected transmission signal vector and the order list, outputs the rearrangement result after rearranging the detected transmission signal vector according to the list. It is characterized by.

The present invention also relates to a radio reception apparatus that performs signal detection of a received signal using a propagation path matrix H, a predetermined coefficient α, and a received signal vector x in a MIMO (Multiple Input Multiple Output) system, and the transmission of the radio transmission apparatus An order list in which the order of signal detection is determined for T elements in the transmission signal vector s of the transmitted signal, and the matrix G calculated by G = H ′ ^H H ′ is decomposed. Te leads to a lower triangular matrix, the order l norm in p-th row of the inverse matrix U of the lower triangular matrix by multiplication d _l calculates beta _p, of the beta _p calculated for an inverse matrix U of the lower triangular matrix The order of values is sorted in ascending order, and the numerical value obtained by the rearrangement is generated as an order list. The expanded propagation path calculated based on the propagation path matrix H, the coefficient α, and the unit matrix I The matrix H ′ is added to the ordered list S. Accordingly, rearrangement means for calculating the matrix H ″ by rearrangement, QR decomposition means for calculating the unitary matrix Q and the lower triangular matrix R by QR decomposition of the matrix H ″ of R rows and T columns, and the matrix Q Filtering means for filtering the received vector x using the complex conjugate transpose of R rows, and forward substitution means for sequentially detecting the T transmission signals by forward substitution using the lower triangular structure of the lower triangular matrix R And an order rearranging means for rearranging and outputting the detected T transmission signals in the order of the original transmitted space according to the order list.

According to the present invention, in the above-described wireless reception device, the rearranging unit outputs the calculated matrix H ″, the QR decomposition unit outputs the matrix Q and the matrix R, and the filtering unit The vector y is calculated by multiplying the complex conjugate transpose of R rows of the matrix Q and the received signal vector x, and the forward substitution means uses the column vector y and the lower triangular matrix R, A forward transmission calculation process calculates a detected transmission signal vector, sequentially detects T elements of the detected transmission signal vector, calculates an interference component according to an interference component calculation formula, and calculates the k th element of the column vector y. A soft decision detection signal is calculated by subtracting the interference component from y _k, and a hard decision is performed on the soft decision detection signal based on the constellation applied at the time of modulation on the transmission side. A hard decision detection signal is calculated, and the order rearranging means reads the detected transmission signal vector and the order list, outputs the rearrangement result after rearranging the detected transmission signal vector according to the list. It is characterized by.

  Further, the present invention is a program executed by a computer of a radio reception apparatus that performs signal detection of a received signal using a propagation path matrix H, a predetermined coefficient α, and a received signal vector x in a MIMO (Multiple Input Multiple Output) system. , A process of determining the order of signal detection for each of T elements in the transmission signal vector s of the signal transmitted by the wireless transmission device, and recording it in the order list; A process of rearranging the extended channel matrix H ′ calculated based on the coefficient α and the unit matrix I according to the order list S to calculate a matrix H ″, and QR decomposition of the matrix H ″ of R rows and T columns Then, a unitary matrix Q and a triangular matrix R are calculated, the received vector x is filtered using a complex conjugate transpose of R rows of the matrix Q, and the T number of matrixes are calculated using the triangular matrix R. A program for causing a computer to execute a process of sequentially detecting transmission signals and a process of outputting the detected T transmission signals in the order of the original transmitted space according to the order list.

Further, the present invention is a program executed by a computer of a radio reception apparatus that performs signal detection of a received signal using a propagation path matrix H, a predetermined coefficient α, and a received signal vector x in a MIMO (Multiple Input Multiple Output) system. , An order list in which the order of signal detection is determined for T elements in the transmission signal vector s of the signal transmitted by the wireless transmission device, calculated by G = H ′ ^H H ′ The matrix G is decomposed to derive an upper triangular matrix, and β _p is calculated by raising the _l- th norm in the p-th row of the inverse matrix U of the upper triangular matrix to the d ₁ power, and the inverse matrix U of the upper triangular matrix is calculated. Based on the detection order determination process for rearranging the calculated β _p values in ascending order and generating an order list for each numerical value obtained by the rearrangement, the propagation path matrix H, the coefficient α, and the unit matrix I Calculated expansion The channel matrix H ′ is rearranged according to the order list S to calculate a matrix H ″, and the matrix H ″ of R rows and T columns is subjected to QR decomposition to obtain a unitary matrix Q and an upper triangular matrix R. QR decomposition processing for calculating R, filtering processing for filtering the received vector x using the complex conjugate transpose of the R rows of the matrix Q, and the upper triangular structure R using the upper triangular structure, and the T The computer performs reverse substitution processing for sequentially detecting transmission signals and order rearrangement processing for rearranging the detected T transmission signals in the original transmitted spatial order according to the order list and outputting them. It is a program to let you.

Further, the present invention outputs the calculated matrix H ″ in the rearrangement process, outputs the matrix Q and the matrix R in the QR decomposition process, and outputs the matrix Q in the filtering process. A vector y is calculated by multiplying the complex conjugate transpose of R rows and the received signal vector x, and in the backward substitution process, a backward substitution operation is performed using the column vector y and the upper triangular matrix R. By processing, a detected transmission signal vector is calculated, T elements of the detected transmission signal vector are sequentially detected, an interference component is calculated according to an interference component calculation formula, and the k-th element y _{k of the} column vector y is calculated. A soft decision detection signal is calculated by subtracting the interference component, and a hard decision is made on the soft decision detection signal based on the constellation applied at the time of modulation on the transmission side. In the order rearrangement process, the detected transmission signal vector and the order list are read, the detection transmission signal vector is rearranged according to the list, and the rearrangement result is output. This is a program that causes a computer to execute each process.

Further, the present invention is a program executed by a computer of a radio reception apparatus that performs signal detection of a received signal using a propagation path matrix H, a predetermined coefficient α, and a received signal vector x in a MIMO (Multiple Input Multiple Output) system. , An order list in which the order of signal detection is determined for T elements in the transmission signal vector s of the signal transmitted by the wireless transmission device, calculated by G = H ′ ^H H ′ By decomposing the matrix G, a lower triangular matrix is derived, the _l- th norm in the p-th row of the inverse matrix U of the lower triangular matrix is raised to the power of d _l , β _p is calculated, and the inverse matrix U of the lower triangular matrix is calculated Based on the detection order determination process for rearranging the calculated β _p values in ascending order and generating an order list for each numerical value obtained by the rearrangement, the propagation path matrix H, the coefficient α, and the unit matrix I Calculated expansion A rearrangement process for rearranging the propagation path matrix H ′ in accordance with the order list S to calculate a matrix H ″, QR decomposition of the matrix H ″ of R rows and T columns, and a unitary matrix Q and a lower triangular matrix R QR decomposition processing for calculating, filtering processing for filtering the received vector x using the complex conjugate transpose of the R rows of the matrix Q, and the lower triangular structure of the lower triangular matrix R, and forward substitution using the T Forward substitution processing for sequentially detecting transmission signals and order rearrangement processing for rearranging the detected T transmission signals in the original transmitted spatial order according to the order list and outputting them to the computer It is a program to let you.

Further, the present invention outputs the calculated matrix H ″ in the rearrangement process, outputs the matrix Q and the matrix R in the QR decomposition process, and outputs the matrix Q in the filtering process. The vector y is calculated by multiplying the complex conjugate transpose of R rows and the received signal vector x, and in the forward substitution process, the forward substitution calculation is performed using the column vector y and the lower triangular matrix R. By processing, a detected transmission signal vector is calculated, T elements of the detected transmission signal vector are sequentially detected, an interference component is calculated according to an interference component calculation formula, and the k-th element y _{k of the} column vector y is calculated. A soft decision detection signal is calculated by subtracting the interference component, and a hard decision is made on the soft decision detection signal based on the constellation applied at the time of modulation on the transmission side. In the order rearrangement process, the detected transmission signal vector and the order list are read, the detection transmission signal vector is rearranged according to the list, and the rearrangement result is output. This is a program that causes a computer to execute each process.

  Further, the present invention is a computer-readable recording medium that records any one of the above programs.

In the prior art, signal detection order determination and signal extraction vector generation for T transmission signals are performed by T pseudo inverse matrix operations, and transmission signals are detected in order using the extraction vectors. However, in the present invention, without first calculating the pseudo inverse matrix, the detection order is first determined by a novel method, and then the extended propagation path matrix H ′ in which the column vectors are rearranged by the QR decomposition operation is triangulated. Finally, using the triangular structure of the transfer coefficient matrix, T transmission signals are detected by backward substitution or forward substitution, rearranged in the original transmitted spatial order, and output.
Thus, according to the above-described embodiment, it is not necessary to perform the pseudo inverse matrix calculation, and main calculation amounts are the detection order determination calculation, the QR decomposition calculation, and the backward or forward substitution calculation. Accordingly, the required calculation amount is extremely small as compared with the conventional SIC method. Therefore, it is possible to provide a signal detection device for a wireless reception device that has a smaller amount of processing computation and a smaller required computation circuit size than conventional ones.

  Further, according to the present invention, since there is no calculation of the pseudo inverse matrix, the required storage capacity is small. Thereby, the required storage device capacity of the signal detection device of the wireless reception device can be reduced.

  Further, according to the present invention, since the required arithmetic circuit scale and the storage device are small, it is possible to easily reduce the size and weight of the signal detection device of the wireless reception device.

  Further, according to the present invention, instead of T times of pseudo inverse matrix calculation, the detection order is determined by a novel method, and then the triangle of the extended channel matrix H ′ in which column vectors are rearranged by QR decomposition calculation. Finally, using the triangular structure of the transfer coefficient matrix, T transmission signals are detected by backward substitution or forward substitution. For this reason, the processing delay is greatly reduced. As a result, even when the number of transmission antennas is large, real-time processing is possible without increasing the clock frequency in the arithmetic circuit. That is, the processing delay of the signal detection device of the wireless reception device can be reduced.

  Further, according to the present invention, since the required power consumption is proportional to the required arithmetic circuit scale, the operation clock frequency, etc., the power consumption in the signal detection device of the wireless receiver of the present invention is higher than the power consumption by the conventional SIC method. Less. Therefore, it is possible to realize a long operating time of the MIMO system operated by the battery.

  In addition, according to the present invention, in the economical implementation of hardware and software of the signal detection device of the wireless reception device, the above-described effects can reduce the manufacturing cost and make it suitable for mass production.

Hereinafter, a wireless communication system according to an embodiment of the present invention will be described with reference to the drawings.
FIG. 1 is a first diagram showing a configuration of a MIMO-OFDM system.
FIG. 2 is a second diagram showing the configuration of the MIMO-OFDM system.
FIG. 3 is a first diagram illustrating a configuration of the MIMO-Single system.
FIG. 4 is a second diagram showing the configuration of the MIMO-Single system.
In these MIMO systems, the system configuration shown in FIGS. 1 and 3 processes channel coding and symbol mapping in one series. Further, the system shown in FIGS. 2 and 4 is newly provided with a configuration for processing T signal sequences in parallel according to the number T of transmission antennas.

In the radio transmission apparatus (Transmitter) of the MIMO system, T transmission signals s _t (t = 1, 2,..., T) are subjected to baseband modulation and passband processing, and then transmitted from T transmission antennas. Sent to space. In addition, in the MIMO system radio receiver (Receiver), T transmission signals multiplexed in space are received using R reception antennas, and after R band processing and baseband demodulation, R R signals are received. The received signal x _r (r = 1, 2,..., R) is input to the signal detection device. The signal detection apparatus (Signal Detector) has a function of detecting a signal spatially multiplexed, and outputs the T number of detection signals ^ s _t detected by this processing. Here, the signal detection may be referred to as signal separation or interference canceller, but the essence is to detect a signal for each transmission system transmitted by the wireless transmission device from a spatially multiplexed signal.

In MIMO-OFDM system and MIMO-Single system can be expressed with its T transmit signal _{s t,} the relationship between the R received signals _{x r} in equation (1).

In this equation (1), “s” represents a transmission signal vector of T × 1 (T rows and 1 column). “X” represents a received signal vector of R × 1 (R rows and 1 column). “W” represents an R × 1 noise component vector. “H” represents a system transfer coefficient matrix (propagation path matrix) of R × T (R rows and T columns). All subscript numbers represent spatial indexes. For example, s ₄ is a transmission signal transmitted by the fourth transmission antenna in the wireless transmission device, x ₂ is a reception signal received by the second reception antenna in the wireless reception device, and w ₁ is the _first reception in the wireless reception device. Noise components added by the antenna, h _{3 and 2} , represent transmission coefficients in the radio link connecting the second transmission antenna in the radio transmission apparatus and the third reception antenna in the radio reception apparatus. Furthermore, in the MIMO-OFDM system, the above equation (1) can be expressed as the following equation (2).

In this equation (2), n represents a time index. K represents a frequency index. Further, Expression (2) limits Expression (1) to a mathematical relationship between T transmission signals and R reception signals in the kth subcarrier of the nth OFDM signal at the time. Further, in the MIMO-Single system, Expression (1) can be expressed as Expression (3).

In this formula (3), n represents a time index. Further, Expression (3) limits Expression (1) to a mathematical relationship between T transmission signals and R reception signals in the n-th single carrier modulation signal. However, since the signal detection method of the present invention can be implemented in the same manner for all time indexes and frequency indexes in the MIMO system, n and k are omitted in the following description. If it is necessary to reestimate the value of the propagation path matrix H as time and frequency change, the estimation process is performed. Furthermore, it is assumed that the frequency and time are normally synchronized between the transmitting and receiving apparatuses in the MIMO system. Hereinafter, a signal detection method of the radio reception apparatus in the MIMO system shown in FIGS. 1 to 4 will be described.

<Example 1>
Assume that the input to the signal detection device in the wireless reception device is the propagation path matrix H, the coefficient α, and the reception signal vector x, and the signal output through the signal detection processing according to the present embodiment is the detection signal ^ s (symbol ^ Indicates a hat), the signal detection device
(Step S1a) With respect to T elements s = [s ₁ , s ₂ ,..., S _T ] in the transmission signal vector s, the order of signal detection is simultaneously determined and the list S is obtained. Record.
(Step S1b) The column vector of the extended propagation path matrix H ′ is rearranged according to the order list S determined in Step S1a, and the matrix H ″ is calculated.
(Step S1c) The matrix H ″ calculated by the rearrangement in step S1b is subjected to QR decomposition to calculate a matrix Q and an upper triangular matrix R.
(Step S1d) The received vector x is filtered using the complex conjugate transpose of the first R rows of the matrix Q.
(Step S1e) Using the upper triangular structure of the matrix R, T transmission signals are sequentially detected by backward substitution.
(Step S1f) According to the list S, the detected T transmission signals are rearranged in the original transmitted spatial order (antenna order) and output.
Here, in the signal detection apparatus, only the process of step S1e includes iterative calculation, but the processes of other steps S1a to 1d and 1f need only be executed once.

  Here, the QR decomposition of the matrix is to decompose a matrix A of R rows and T columns into a column unitary matrix Q of R rows and T columns and an upper triangular matrix R of T rows and T columns, or R rows T This means that the matrix A of columns is decomposed into a unitary matrix Q of R rows and R columns and a matrix U of R rows and T columns including an upper triangular matrix R. In other words, the QR decomposition can be expressed by the following QR decomposition formula (4) or (5).

  Here, in equation (5),

It becomes. That is, 0 _n is a zero matrix of n rows and T columns, and 0 _m is a zero matrix of m rows and T columns. Furthermore, the condition (n, m = 0, 1, 2,..., RT and n + m = RT) is satisfied. R is an upper triangular matrix as shown in Equation (8).

Next, the details of the above-described processes (step S1a) to (step S1f) will be described.
<About Step S1a>
For the T elements s = [s ₁ , s ₂ ,..., S _T ] in the transmission signal vector s, the respective signal detection orders are simultaneously determined and recorded in the list S. Then, the matrix G is calculated by Expression (9) using the extended propagation path matrix H ′ defined as Expression (9).

Here, H ′ represents a matrix of R + T rows and T columns. Further, α = σ _w / σ _s, and σ _w and σ _s represent the variance of the noise component and the variance of the transmission signal, respectively. If the values of σ _w and σ _s are not known, it is possible to estimate them and obtain the coefficient α using the estimated values. Also, the coefficient α can be set to other values according to the requirements of the MIMO system. For example, α = 0 is set. In this case, since the R + 1th row to the R + Tth row of the extended channel matrix H ′ are zero, the Rth from the first row of the extended channel matrix H ′ is set. Only the part up to the line (that is, the propagation path matrix H) needs to be considered. At that time, G = H ^H H. The following processing is regarded as an extended channel matrix H ′ = channel matrix H when α = 0.

  Next, the matrix G calculated by the equation (9) is decomposed as the equation (4) and expressed using the upper triangular matrix R. Expression (10) is an expression obtained by decomposing the matrix G and using the upper triangular matrix R.

  There are several possible methods for decomposing the matrix G using the upper triangular matrix R as shown in Equation (10), for example, Gaxpy Cholesky decomposition method, Outer Product Cholesky decomposition method and the like. The specific decomposition method to be used should be determined based on implementation considerations.

  Next, the signal detection device calculates an inverse matrix U of the upper triangular matrix R using Equation (11).

Then, the signal detection device calculates the _l- th norm of the _l- th norm at the p-th row of the matrix U using Equation (12), and calculates it as β _p . Here, l and d _l should be determined according to the system requirements in the MIMO system in which the signal detection device is mounted on the wireless reception device. As an example, when 1 = 2 and d ₁ = 2 are set, β _p is the square of the second-order norm in the p-th row of the matrix U. “U _p ” represents the P th column vector in the U matrix, and “U _{p ,:} ” represents the P th row vector in the U matrix.

Next, the signal detection device sorts the calculated T β _p in ascending order by comparing the magnitudes as shown in Equation (13).

When T = 3 in Equation (13), it is assumed that β ₁ = 0.3, β ₂ = 5.7, and β ₃ = 1.8 for a certain channel matrix H. Then, according to the equation (13), β ₁ ≦ β ₃ ≦ β ₂ → β _p1 ≦ β _p2 ≦ β _p3 , p ₁ = 1, p ₂ = 3, p ₃ = 2.

Next, the numerical values from p ₁ to p _T obtained by the magnitude comparison and rearrangement in Expression (13) are recorded as a detection order list S of T transmission signals as in Expression (14). Expressions (12) to (14) are taken as an order list generation expression.

As described above, assuming T = 3, β ₁ = 0.3, β ₂ = 5.7, and β ₃ = 1.8 for a certain extended channel matrix H ′, S = {p ₃ , p ₂ , P ₁ } = {2, 3, ₁ }. In other words, the transmission signal s ₁ is detected first, s ₃ is detected second, and s ₂ is detected third. Note that p _k (k = 1,..., T) means that the transmission signal s _pk is detected k-th.

<About Step S1b>
Next, the column vector of the extended propagation path matrix H ′ is rearranged according to the order list S determined in step S1a. Expression (15) is an expression used for performing the rearrangement.

In this equation (15), P corresponds to a rearrangement matrix, and its column vector is composed of e _pT ,..., E _p2 , e _p1 . E _k is a column vector of T rows and 1 column, the k th element is 1 and the others are 0. A matrix after rearrangement as shown in Expression (15) or after processing corresponding to the rearrangement is expressed as H ″. For example, S = {p ₃ , p ₂ , p ₁ } = { ₂ , ₃ , ₁ }, P = [e _p3 , e _p2 , e _p1 ] = [e ₂ , e ₃ , e ₁ ] Therefore, as shown in the equation (16), the extended channel matrix The column vector of H ′ is sorted by P.

Here, the multiplication of the matrices H ′ and P does not actually require a mathematical operation, and the matrix P may be rearranged according to the order list S and the column vectors of H ′. That is, even when step S1b is actually implemented, the column vectors of the extended propagation path matrix H ′ may be rearranged according to the list S.

<Regarding Step S1c>
Next, the matrix H ″ rearranged in step S1b is subjected to QR decomposition to calculate a matrix Q and an upper triangular matrix R. A process for deriving the matrix Q and the upper triangular matrix R is expressed by Expression (17).

Here, Q represents a matrix of R + T rows and T columns, and R represents a matrix of T rows and T columns. Q ₁ represents a partial matrix of the matrix Q having R rows, and Q ₂ represents a partial matrix of the matrix Q having T rows. Several QR decomposition methods such as the equation (17) are conceivable. For example, Classical Gram-Schmidt QR decomposition method, Modified Gram-Schmidt QR decomposition method, Householder QR decomposition method, Given QR decomposition method and the like. If necessary, the matrix G calculated in step S1a may be used as an input for the QR decomposition calculation. What QR decomposition method is used is determined in consideration of implementation considerations.

<About Step S1d>
Next, a column vector y is calculated using the complex conjugate transpose of the first R rows of the matrix Q calculated in step S1c, and the received vector x is filtered as shown in Expression (18). In Equation (18), the first R row of the matrix Q is Q ₁ , and the remaining T rows are Q ₂ .

Here, when α = 0, the extended propagation path matrix H ′ = propagation path matrix H, and Q = Q ₁ (that is, both H ′ and the matrix Q have only R rows). S ′ represents a matrix in which the order of elements of the transmission signal vector s is rearranged by the matrix ^PT . V represents the synthesis of the noise component vector and the interference component vector after the linear filtering process. The column vector y includes a column vector v obtained by multiplying the matrix R and the column vector s ′ and synthesizing the noise component and the interference component.

<About Step S1e>
Next, using the upper triangular structure of the matrix R, T transmission signals are sequentially detected by backward substitution. The calculated column vector y can be written for each element as shown in equation (19).

In Equation (19), r _{k, k} , r _{k, i} , v _k (k = T,..., 1) represent elements in the matrix R and the vector v, respectively. In the backward substitution process, the following three equations (20), (21), and (22) are calculated from k = T to k = 1 (that is, k = T, T-1,..., 1). Repeat. Expression (20) is an operation (interference component calculation expression) for calculating an interference component for the transmission signal s _k ^′ . In this calculation, when K = T, the interference component is 0, that is, ^ m _T = 0. The subtracting the interference component ^ m _k from the k-th element y _k of the column vector Equation (21), the soft decision result ^~ s _k 'of the transmission signal ^(~ symbol indicates the tilde) is a calculation for obtaining a. The equation (22) is a process of performing a hard decision based on the cons sauce Deployment applied during modulation at the transmission side with respect to formula (21) soft decision result ^{~ s} k obtained in _'.

Then, the processing according to the above equations (20) to (22) is executed T times from k = T to k = 1, and the transmission signal vector ^ s' = [^ s ₁ ', ^ s ₂ ', ..., ^ s _T '] Is obtained.

<Regarding Step S1f>
Next, the T transmission signals detected are rearranged in the original transmitted spatial order (antenna order) according to the order list S and output. Using the transpose of the matrix P as shown in Expression (23), the rearrangement processing of the order of the transmission signal ^ s ′ detected in Step S1e is performed. The matrix P is the same as the matrix P obtained according to the detection order list S in the process of step S1b.

For example, similarly to step S1b, in the case of S = {p ₃ , p ₂ , p ₁ } = { ₁ , ₃ , ₂ }, P = [e ₁ , e ₃ , e ₂ ] = [e ₁ , e ₃ , E ₂ ] ^T. Therefore, each element of ^ s ^' is rearranged by P as shown in Expression (24).

  Here, the multiplication of the matrix P and ^ s' shown in the equation (24) does not actually require a mathematical operation, and the signal detection apparatus inside the wireless reception apparatus has the matrix P according to the order list S. It only needs to have a function to sort the elements of '. After the rearrangement processing is completed, the detected transmission signal vector ^ s is output from the signal detection device, and the next processing unit of the wireless reception device performs the processing.

Next, the configuration of the signal detection device will be described.
FIG. 5 is a first diagram illustrating a function processing unit of the signal detection device.
FIG. 6 is a second diagram illustrating the function processing unit of the signal detection device.
FIG. 7 is a third diagram illustrating the function processing unit of the signal detection device.
First, in FIG. 5, function processing units denoted by reference numerals 11 to 16 correspond to function processing units that perform processes corresponding to the above-described steps S1a to S1f. Here, the function processing unit means a circuit group in the signal detection device or a program group executed by the device. Reference numeral 17 represents a readable / writable storage device or an information pipeline (wiring).

Reference numeral 11 denotes a detection order determination processing unit (Ordering). The detection order determination processing unit 11 reads or receives the propagation path matrix H and the coefficient α from the storage device (or pipeline) 17, and performs an order list S, a matrix G, an inverse matrix U of the upper triangular matrix R, and an inverse matrix by arithmetic processing. The value of β _{k obtained} by raising the _l- th norm in the k-th row of U to the power of d ₁ is written to the storage device 37 (or output to the pipeline). As shown in FIG. 6, the configuration of the detection order determination processing unit 11 is further divided into 11a and 11b. Reference numeral 11a denotes a matrix G calculation processing unit (G Computation). The matrix G calculation processing unit 11a reads or receives the propagation path matrix H and the coefficient α from the storage device (or pipeline) 17, calculates the matrix G according to the equation (9), and records it in the storage device 17 (or Output to the pipeline). Reference numeral 11b denotes an order list determination processing unit (S Determination). The order list determination processing unit 11b reads or receives the matrix G from the storage device (or pipeline) 17, generates the signal detection order list S according to the equations (10) to (14), and generates the signal detection order list S. And the inverse matrix U of the upper triangular matrix R and the value of β _{k obtained} by raising the _l- th norm in the k-th row of the inverse matrix U to the d ₁ power are written in the storage device 37 (or output to the pipeline).

  Reference numeral 12 denotes an extended channel matrix vector rearrangement processing unit (Column Exchange). The extended propagation path matrix vector rearrangement processing unit 12 reads or receives the signal detection order list S and the extended propagation path matrix H ′ from the storage device (or pipeline) 17, and the extended propagation path matrix H according to the signal detection order list S. After rearranging ', the resulting matrix H ″ is written to the storage device 17 (or output to the pipeline).

  Reference numeral 13 denotes a QR decomposition processing unit (QR Decomposition). The QR decomposition processing unit 13 reads or receives the matrix H ″ or both the matrix H ″ and the matrix G from the storage device (or pipeline) 17, and performs the matrix by the QR decomposition processing according to the equation (4) or the equation (5). Q and matrix R are calculated and written to the storage device 17 (or output to the pipeline).

Reference numeral 14 denotes a filtering processing unit (Q ^H Filtering). The filtering processing unit 14 reads or receives the matrix Q ₁ and the received signal vector x from the storage device (or pipeline) 17, calculates the vector y by multiplying the complex conjugate transpose of Q ₁ and x, and calculates it. Write to the storage device 17 (or output to the pipeline).

Reference numeral 15 denotes a backward substitution processing unit (Back Substitution). The backward substitution processing unit 15 reads or receives the column vector y and the matrix R from the storage device (or pipeline) 17, calculates the detected transmission signal vector ^ s' by the backward substitution calculation process, and detects the detected transmission signal vector ^ Write s ^′ to the storage device 17 (or output to the pipeline). As shown in FIG. 7, the backward substitution processing unit 15 further includes functional processing units of an interference component calculation processing unit (Interference Computation) 15a, a subtraction processing unit (subtractor) 15b, and a quantization processing unit (Quantiztion) 15c. Yes. Until From k = T a k = 1, is detected in the order of 'the elements of ^ s _T' detect signal vector ^ s each functional processing unit with T times in FIG. 7 to ^ s 1 _'. Then, the interference component calculation processing unit 15a sends r _{k, i} (k = T, T-1,..., 1) and ^ s _i ′ (i = k + 1, k + 2,...) From the storage device (or pipeline) 17. , T) is read or received, the interference component ^ m _k is calculated according to the equation (20), and is sent to the subtraction processing unit 15b. The subtraction processing unit 15b or receive reading k-th element y _k column vectors y from a storage device (or pipeline) 17, soft decision detection signal by subtracting the interference component ^ m _k from the element y _k calculating a ^~ s _k ', and sends it to the quantization processing unit 15c. Then, the quantization processing unit 15c makes a hard decision based on the constellation applied at the time of modulation ^to the soft decision detection signal ˜s _k ′ that has received the input, and the hard decision detection signal ｓ _k ′. Is written into the storage device 17 (or output to the pipeline).

  Reference numeral 16 denotes an order rearrangement processing unit (Row Exchange). The order rearrangement processing unit 16 reads or receives ^ s 'and the order list S from the storage device (or pipeline) 17 and rearranges ^ s' according to the order list S. As a result, the transmission signal vector ^ s is output from the signal detection device.

<Example 2>
Next, Example 2 will be described.
As in the first embodiment, it is assumed that the input to the signal detection device in the wireless reception device is the propagation path matrix H, the coefficient α, and the reception signal vector x, and the signal output through the signal detection processing according to the present embodiment is the detection signal. When ^ s, the signal detection device is
(Step S2a) For the T elements s = [s ₁ , s ₂ ,..., S _T ] in the transmission signal vector s, the order of signal detection is simultaneously determined and Record.
(Step S2b) The column vector of the extended propagation path matrix H ′ is rearranged according to the order list S determined in Step S2a to calculate the matrix H ″.
(Step S2c) The matrix H ″ calculated by the rearrangement in step S2b is subjected to QR decomposition to calculate a matrix Q and a lower triangular matrix R.
(Step S2d) The received vector x is filtered using the complex conjugate transpose of the first R rows of the matrix Q.
(Step S2e) Using the lower triangular structure of the matrix R, T transmission signals are sequentially detected by forward substitution.
(Step S2f) According to the list S, the detected T transmission signals are rearranged in the original transmitted spatial order (antenna order) and output.
Here, in the signal detection apparatus, only the process of step S2e includes iterative calculation, but the other processes of steps S2a to 2d and 2f need only be executed once.

  Here, the QR decomposition of the matrix is to decompose a matrix A of R rows and T columns into a column unitary matrix Q of R rows and T columns and a lower triangular matrix R of T rows and T columns, or R rows T This means that the matrix A of columns is decomposed into a unitary matrix Q of R rows and R columns and a matrix L of R rows and T columns including a lower triangular matrix R. That is, the QR decomposition can be expressed by the following QR decomposition formula (25) or (26).

  Here, in equation (26),

It becomes. That is, 0 _n is a zero matrix of n rows and T columns, and 0 _m is a zero matrix of m rows and T columns. Furthermore, the condition (n, m = 0, 1, 2,..., RT and n + m = RT) is satisfied. R is a lower triangular matrix as shown in equation (29).

Next, details of the above-described processes of (Step S2a) to (Step S2f) will be described.
<About Step S2a>
For the T elements s = [s ₁ , s ₂ ,..., S _T ] in the transmission signal vector s, the respective signal detection orders are simultaneously determined and recorded in the list S. Then, the matrix G is calculated by Equation (30) using the extended propagation path matrix H ′ defined as Equation (9).

Here, H ′ represents a matrix of R + T rows and T columns. Further, α = σ _w / σ _s, and σ _w and σ _s represent the variance of the noise component and the variance of the transmission signal, respectively. If the values of σ _w and σ _s are not known, it is possible to estimate them and obtain the coefficient α using the estimated values. Also, the coefficient α can be set to other values according to the requirements of the MIMO system. For example, α = 0 is set. In this case, since the R + 1th row to the R + Tth row of the extended channel matrix H ′ are zero, the Rth from the first row of the extended channel matrix H ′ is set. Only the part up to the line (that is, the propagation path matrix H) needs to be considered. At that time, G = H ^H H. The following processing is regarded as an extended channel matrix H ′ = channel matrix H when α = 0.

  Next, the matrix G calculated by the equation (9) is decomposed as the equation (25) and represented by using the lower triangular matrix R. Expression (31) is an expression obtained by decomposing the matrix G and using the lower triangular matrix R.

  There are several possible methods for decomposing the matrix G using the lower triangular matrix R as shown in Equation (31), for example, Gaxpy Cholesky decomposition method, Outer Product Cholesky decomposition method and the like. The specific decomposition method to be used should be determined based on implementation considerations.

  Next, the signal detection device calculates an inverse matrix U of the lower triangular matrix R using Expression (32).

Then, the signal detection device calculates the d ₁ power of the l-order norm in the p-th row of the matrix U using Equation (33), and calculates it as β _p . Here, l and d _l should be determined according to the system requirements in the MIMO system in which the signal detection device is mounted on the wireless reception device. As an example, when 1 = 2 and d ₁ = 2 are set, β _p is the square of the second-order norm in the p-th row of the matrix U. “U _p ” represents the P th column vector in the U matrix, and “U _{p ,:} ” represents the P th row vector in the U matrix.

Next, the signal detection device sorts the calculated T β _p in ascending order by comparing the magnitudes as shown in Expression (34).

When T = 3 in Equation (34), it is assumed that β ₁ = 0.3, β ₂ = 5.7, and β ₃ = 1.8 for a certain channel matrix H. Then, according to the equation (34), β ₁ ≦ β ₃ ≦ β ₂ → β _p1 ≦ β _p2 ≦ β _p3 , p ₁ = 1, p ₂ = 3, p ₃ = 2.

Next, the numerical values from p ₁ to p _T obtained by the magnitude comparison and rearrangement in Expression (34) are recorded as a detection order list S of T transmission signals as in Expression (35). Expressions (33) to (35) are taken as an order list generation expression.

As described above, assuming T = 3, β ₁ = 0.3, β ₂ = 5.7, and β ₃ = 1.8 for a certain extended channel matrix H ′, S = {p ₁ , p ₂ , P ₃ } = {1, _{3, 2} }. In other words, the transmission signal s ₁ is detected first, s ₃ is detected second, and s ₂ is detected third. Note that p _k (k = 1,..., T) means that the transmission signal s _pk is detected k-th.

<About Step S2b>
Next, the column vector of the extended propagation path matrix H ′ is rearranged according to the order list S determined in step S2a. Expression (36) is an expression used for performing the rearrangement.

In this equation (36), P corresponds to a rearrangement matrix, and its column vector is composed of e ₁ , e ₂ ,..., _EpT . E _k is a column vector of T rows and 1 column, the k th element is 1 and the others are 0. A channel matrix after rearrangement as shown in Expression (36) or after processing corresponding to the rearrangement is expressed as H ″. For example, S = {p ₁ , p ₂ , p _In the case of ₃ } = { ₁ , ₃ , ₂ }, P = [e _p1 , e _p2 , e _p3 ] = [e ₁ , e ₃ , e ₂ ], so that the extended propagation as shown in the equation (37). The column vector of the path matrix H ′ is rearranged by P.

Here, the multiplication of the matrices H ′ and P does not actually require a mathematical operation, and the matrix P may be rearranged according to the order list S and the column vectors of H ′. That is, even when step S2b is actually implemented, the column vectors of the extended propagation path matrix H ′ may be rearranged according to the list S.

<About Step S2c>
Next, the matrix H ″ rearranged in step S2b is subjected to QR decomposition to calculate a matrix Q and a lower triangular matrix R. A process for deriving the matrix Q and the lower triangular matrix R is expressed by Expression (38).

Here, Q represents a matrix of R + T rows and T columns, and R represents a matrix of T rows and T columns. Q ₁ represents a partial matrix of the matrix Q having R rows, and Q ₂ represents a partial matrix of the matrix Q having T rows. Several QR decomposition methods such as the equation (38) are conceivable. For example, Classical Gram-Schmidt QR decomposition method, Modified Gram-Schmidt QR decomposition method, Householder QR decomposition method, Given QR decomposition method and the like. If necessary, the matrix G calculated in step S2a may be used as an input for the QR decomposition calculation. What kind of decomposition method to use is determined based on implementation considerations.

<About Step S2d>
Next, a column vector y is calculated using the complex conjugate transpose of the first R row (Q ₁ ) of the matrix Q calculated in step S2c, and the received vector x is linearly filtered (that is, multiplied) as shown in Expression (39). Process). In Equation (39), the first R row of the matrix Q is Q ₁ and the remaining T rows are Q ₂ .

Here, when α = 0, the extended propagation path matrix H ′ = propagation path matrix H, and Q = Q ₁ (that is, both H ′ and Q have only R rows). S ′ represents a matrix in which the order of elements of the transmission signal vector s is rearranged by the matrix ^PT . V represents the synthesis of the noise component vector and the interference component vector after the linear filtering process. The column vector y includes a column vector v obtained by multiplying the matrix R and the column vector s ′ and synthesizing the noise component and the interference component.

<About Step S2e>
Next, using the lower triangular structure of the matrix R, T transmission signals are sequentially detected by forward substitution. The calculated column vector y can be written for each element as shown in Equation (40).

In Equation (40), r _{k, k} , r _{k, i} , v _k (k = T,..., 1) represent elements in the matrix R and the vector v, respectively. In the forward substitution process, the following three expressions (41), (42), and (43) are repeated from k = 1 to k = T (that is, k = 1, 2,..., T). Do. Expression (41) is an operation (interference component calculation expression) for calculating an interference component for the transmission signal s _k ^′ . In this calculation, when K = 1, the interference component is 0, that is, ^ m ₁ = 0. The subtracting the interference component ^ m _k from the k-th element y _k of the column vector Equation (42), the soft decision result ^~ s _k 'of the transmission signal ^(~ symbol indicates the tilde) is a calculation for obtaining a. The equation (43) is a process of performing a hard decision based on the cons sauce Deployment applied during modulation at the transmission side with respect to formula (42) soft decision result ^{~ s} k obtained in _'.

Then, the processing according to the above equations (41) to (42) is executed T times from k = 1 to k = T, and the transmission signal vector ^ s' = [^ s ₁ ', ^ s ₂ ', ..., ^ s _T '] Is obtained.

<About Step S2f>
Next, the T transmission signals detected are rearranged in the original transmitted spatial order (antenna order) according to the order list S and output. Using the transpose of the matrix P as shown in Expression (44), the rearrangement processing of the order of the transmission signal ^ s ′ detected in Step S2e is performed. The matrix P is the same as the matrix P obtained according to the detection order list S in the process of step S2b.

For example, as in step S2b, in the case of S = {p ₁ , p ₂ , p ₃ } = { ₁ , ₃ , ₂ }, P = [e ₁ , e ₃ , e ₂ ] = [e ₁ , e ₃ , E ₂ ] ^T. Therefore, each element of ^ s ^' is rearranged by P as shown in Expression (45).

  Here, the multiplication of the matrix P and ^ s' shown in the equation (45) does not actually require a mathematical operation, and the signal detection apparatus inside the wireless reception apparatus has the matrix P according to the order list S. It only needs to have a function to sort the elements of '. After the rearrangement processing is completed, the detected transmission signal vector ^ s is output from the signal detection device, and the next processing unit of the wireless reception device performs the processing.

Next, the configuration of the signal detection device will be described.
FIG. 8 is a fourth diagram illustrating the function processing unit of the signal detection device.
FIG. 9 is a fifth diagram illustrating the function processing unit of the signal detection device.
FIG. 10 is a sixth diagram illustrating the function processing unit of the signal detection device.
First, in FIG. 8, function processing units denoted by reference numerals 21 to 26 correspond to function processing units that perform processes corresponding to the above-described steps S2a to S2f, respectively. Here, the function processing unit means a circuit group in the signal detection device or a program group executed by the device. Reference numeral 27 denotes a readable / writable storage device or an information pipeline (wiring).

Reference numeral 21 denotes a detection order determination processing unit (Ordering). The detection order determination processing unit 21 reads or receives the propagation path matrix H and the coefficient α from the storage device (or pipeline) 27, and performs an arithmetic process to the order list S, the matrix G, the inverse matrix U of the lower triangular matrix R, and the inverse matrix. The value of β _{k obtained} by raising the _l- th norm in the k-th row of U to the power of d ₁ is written to the storage device 37 (or output to the pipeline). As shown in FIG. 9, the configuration of the detection order determination processing unit 21 is further divided into 21a and 21b. Reference numeral 21a denotes a matrix G calculation processing unit (G Computation). The matrix G calculation processing unit 21a reads or receives the propagation path matrix H and the coefficient α from the storage device (or pipeline) 27, calculates the matrix G according to the equation (30), and records it in the storage device 27 (or Output to the pipeline). Reference numeral 21b denotes an order list determination processing unit (S Determination). The order list determination processing unit 21b reads or receives the matrix G from the storage device (or pipeline) 27, generates the signal detection order list S according to the expressions (31) to (35), and generates the signal detection order list S. And the inverse matrix U of the upper triangular matrix R and the value of β _{k obtained} by raising the _l- th norm in the k-th row of the inverse matrix U to the d ₁ power are written in the storage device 37 (or output to the pipeline).

  Reference numeral 22 denotes an extended channel matrix vector rearrangement processing unit (Column Exchange). The extended propagation path matrix vector rearrangement processing unit 22 reads or receives the signal detection order list S and the extended propagation path matrix H ′ from the storage device (or pipeline) 27, and the extended propagation path matrix H according to the signal detection order list S. After rearranging ', the resulting matrix H ″ is written into the storage device 27 (or output to the pipeline).

  Reference numeral 23 denotes a QR decomposition processing unit (QR Decomposition). The QR decomposition processing unit 23 reads or receives the matrix H ″ or both the matrix H ″ and the matrix G from the storage device (or pipeline) 27, and performs the matrix by the QR decomposition processing according to the equation (25) or the equation (26). Q and matrix R are calculated and written to the storage device 27 (or output to the pipeline).

Reference numeral 24 denotes a filtering processing unit (Q ^H Filtering). The filtering processing unit 24 reads or receives the matrix Q ₁ and the received signal vector x from the storage device (or pipeline) 27, calculates the vector y by multiplying the complex conjugate transpose of Q ₁ and x, and calculates it. Write to the storage device 27 (or output to the pipeline).

Reference numeral 25 denotes a forward substitution processing unit (Back Substitution). The forward substitution processing unit 25 reads or receives the column vector y and the matrix R from the storage device (or pipeline) 17, calculates the detected transmission signal vector ^ s' by the forward substitution calculation process, and detects the detected transmission signal vector ^ s ^′ is written to the storage device 27 (or output to the pipeline). As shown in FIG. 10, the forward substitution processing unit 25 further includes functional processing units of an interference component calculation processing unit (Interference Computation) 25a, a subtraction processing unit (subtractor) 25b, and a quantization processing unit (Quantiztion) 25c. Yes. Until From k = 1 for k = T, is detected in the order of 'the elements of ^ s _1' detection signal vector ^ s each functional processing unit with T times in FIG. 10 to ^ s T _'. Then, the interference component calculation processing unit 25a sends r _{k, i} (k = 1, 2,..., T) and ^ s _i ′ (i = 1, 2,...) From the storage device (or pipeline) 27. , K−1) is read or received, the interference component ^ m _k is calculated according to the equation (41), and is sent to the subtraction processing unit 25b. The subtraction processing unit 25b or receive reading k-th element y _k column vectors y from a storage device (or pipeline) 27, soft decision detection signal by subtracting the interference component ^ m _k from the element y _k calculating a ^~ s _k ', and sends it to the quantization processing unit 25c. Then, the quantization processing unit 25c performs a hard decision based on the constellation applied at the time of modulation on the transmission side with respect ^to the soft decision detection signal ˜s _k ′ that has received the input, and the hard decision detection signal ^ s _k ′. Is written into the storage device 27 (or output to the pipeline).

  Reference numeral 26 denotes an order rearrangement processing unit (Row Exchange). The order rearrangement processing unit 26 reads or receives ^ s 'and the order list S from the storage device (or pipeline) 27 and rearranges ^ s' according to the order list S. As a result, the transmission signal vector ^ s is output from the signal detection device.

As described above, the embodiments of the present invention have been described. In the prior art, the signal detection order determination and signal extraction vector generation in T transmission signals are performed by T pseudo inverse matrix operations, and further, the order is determined using the extraction vectors. The transmission signal was detected. However, in the present invention, without first calculating the pseudo inverse matrix, the detection order is first determined by a novel method, and then the extended propagation path matrix H ′ in which the column vectors are rearranged by the QR decomposition operation is triangulated. Finally, using the triangular structure of the transfer coefficient matrix, T transmission signals are detected by backward substitution or forward substitution, rearranged in the original transmitted spatial order, and output.
Thus, according to the above-described embodiment, it is not necessary to perform the pseudo inverse matrix calculation, and main calculation amounts are the detection order determination calculation, the QR decomposition calculation, and the backward or forward substitution calculation. Accordingly, the required calculation amount is extremely small as compared with the conventional SIC method. Therefore, it is possible to provide a signal detection device for a wireless reception device that has a smaller amount of processing computation and a smaller required computation circuit size than conventional ones.

  Further, according to the present invention, since there is no calculation of the pseudo inverse matrix, the required storage capacity is small. Thereby, the required storage device capacity of the signal detection device of the wireless reception device can be reduced.

  Further, according to the present invention, since the required arithmetic circuit scale and the storage device are small, it is possible to easily reduce the size and weight of the signal detection device of the wireless reception device.

  Further, according to the present invention, instead of T times of pseudo inverse matrix calculation, the detection order is determined by a novel method, and then the triangle of the extended channel matrix H ′ in which column vectors are rearranged by QR decomposition calculation. Finally, using the triangular structure of the transfer coefficient matrix, T transmission signals are detected by backward substitution or forward substitution. For this reason, the processing delay is greatly reduced. As a result, even when the number of transmission antennas is large, real-time processing is possible without increasing the clock frequency in the arithmetic circuit. That is, the processing delay of the signal detection device of the wireless reception device can be reduced.

  Further, according to the present invention, since the required power consumption is proportional to the required arithmetic circuit scale, the operation clock frequency, etc., the power consumption in the signal detection device of the wireless receiver of the present invention is higher than the power consumption by the conventional SIC method. Less. Therefore, it is possible to realize a long operating time of the MIMO system operated by the battery.

  In addition, according to the present invention, in the economical implementation of hardware and software of the signal detection device of the wireless reception device, the above-described effects can reduce the manufacturing cost and make it suitable for mass production.

  The most important features in the embodiment of the present invention are: 1. A new signal detection order determination method has been devised. 2. devised a method of triangulating the extended channel matrix H 'by QR decomposition; 3. Invented a method of signal detection by backward or forward substitution using the triangular structure of the extended channel matrix H '. That is, a method of combining (1.), (2.) and (3.) was devised.

  Note that the signal detection device of the above-described wireless reception device has a computer system therein. The process described above is stored in a computer-readable recording medium in the form of a program, and the above process is performed by the computer reading and executing this program. Here, the computer-readable recording medium means a magnetic disk, a magneto-optical disk, a CD-ROM, a DVD-ROM, a semiconductor memory, or the like. Alternatively, the computer program may be distributed to the computer via a communication line, and the computer that has received the distribution may execute the program.

  The program may be for realizing a part of the functions described above. Furthermore, what can implement | achieve the function mentioned above in combination with the program already recorded on the computer system, and what is called a difference file (difference program) may be sufficient.

It is a 1st figure which shows the structure of a MIMO-OFDM system. It is a 2nd figure which shows the structure of a MIMO-OFDM system. It is a 1st figure which shows the structure of a MIMO-Single system. It is a 2nd figure which shows the structure of a MIMO-Single system. It is a 1st figure which shows the function process part of a signal detection apparatus. It is a 2nd figure which shows the function process part of a signal detection apparatus. It is a 3rd figure which shows the function process part of a signal detection apparatus. It is a 4th figure which shows the function process part of a signal detection apparatus. It is a 5th figure which shows the function process part of a signal detection apparatus. It is a 6th figure which shows the function process part of a signal detection apparatus.

Explanation of symbols

11, 21... Detection order determination processing unit 12, 22 ... Channel matrix vector rearrangement processing unit 13, 23 ... QR decomposition processing unit 14, 24 ... Filtering processing unit 15 ... Backward substitution Processing unit 25: Forward substitution processing unit 16, 26 ... Order rearrangement processing unit 17, 27 ... Storage device

Claims (13)

A radio signal separation method in a radio reception apparatus that performs signal detection of a received signal using a propagation path matrix H, a predetermined coefficient α, and a received signal vector x in a MIMO (Multiple Input Multiple Output) system,
An order list in which the order of signal detection is determined for T elements in the transmission signal vector s of the signal transmitted by the wireless transmission device, calculated by G = H ′ ^H H ′ Decompose the matrix G to derive an upper triangular matrix, calculate the _l- th norm in the p-th row of the inverse matrix U of the upper triangular matrix to the power of d _l , calculate β _p, and calculate the inverse matrix U of the upper triangular matrix A detection order determination process for rearranging the β _p values in ascending order and generating an order list for each numerical value obtained by the rearrangement;
A rearrangement process for rearranging the extended channel matrix H ′ calculated based on the channel matrix H, the coefficient α, and the unit matrix I according to the order list S to calculate a matrix H ″;
QR decomposition of the matrix H ″ of R rows and T columns to calculate a unitary matrix Q and an upper triangular matrix R by QR decomposition;
A filtering process for filtering the received vector x using a complex conjugate transpose of R rows of the matrix Q;
Using the upper triangular structure of the upper triangular matrix R, backward substitution processing for sequentially detecting the T transmission signals by backward substitution;
An order rearrangement process for rearranging the detected T transmission signals according to the order list and outputting them in the original transmitted spatial order;
A radio signal separation method comprising: The rearrangement process outputs the calculated matrix H ″,
The QR decomposition process outputs the matrix Q and the matrix R;
The filtering process calculates a vector y by multiplying the complex conjugate transpose of R rows of the matrix Q and the received signal vector x,
The backward substitution process uses the column vector y and the upper triangular matrix R to calculate a detected transmission signal vector by a backward substitution calculation process, and sequentially detects T elements of the detected transmission signal vector. Then, an interference component is calculated according to an interference component calculation formula, a soft decision detection signal is calculated by subtracting the interference component from the _kth element y _{k of the} column vector y, and transmitted to the soft decision detection signal. The hard decision is made based on the constellation applied during modulation on the side, and the hard decision detection signal is calculated,
The order rearrangement processing reads and said ordered list and the detected transmission signal vector, after rearranging the detection transmitted signal vector in accordance with the list, to claim 1, characterized in that outputs the rearrangement result The radio signal separation method as described. A radio signal separation method in a radio reception apparatus that performs signal detection of a received signal using a propagation path matrix H, a predetermined coefficient α, and a received signal vector x in a MIMO (Multiple Input Multiple Output) system,
An order list in which the order of signal detection is determined for T elements in the transmission signal vector s of the signal transmitted by the wireless transmission device, calculated by G = H ′ ^H H ′ The matrix G is decomposed to derive a lower triangular matrix, the _l- th norm in the p-th row of the inverse matrix U of the lower triangular matrix is raised to the d ₁ power to calculate β _p, and the inverse matrix U of the lower triangular matrix is calculated A detection order determination process for rearranging the β _p values in ascending order and generating an order list for each numerical value obtained by the rearrangement;
A rearrangement process for rearranging the extended channel matrix H ′ calculated based on the channel matrix H, the coefficient α, and the unit matrix I according to the order list S to calculate a matrix H ″;
QR decomposition processing for calculating the unitary matrix Q and the lower triangular matrix R by QR decomposition of the matrix H ″ of R rows and T columns;
A filtering process for filtering the received vector x using a complex conjugate transpose of R rows of the matrix Q;
Using the lower triangular structure of the lower triangular matrix R, forward substitution processing for sequentially detecting the T transmission signals by forward substitution;
An order rearrangement process for rearranging the detected T transmission signals according to the order list and outputting them in the original transmitted spatial order;
A radio signal separation method comprising: The rearrangement process outputs the calculated matrix H ″,
The QR decomposition process outputs the matrix Q and the matrix R;
The filtering process calculates a vector y by multiplying the complex conjugate transpose of R rows of the matrix Q and the received signal vector x,
The forward substitution process uses the column vector y and the lower triangular matrix R to calculate a detected transmission signal vector by a forward substitution calculation process, and sequentially detects T elements of the detected transmission signal vector. Then, an interference component is calculated according to an interference component calculation formula, a soft decision detection signal is calculated by subtracting the interference component from the _kth element y _{k of the} column vector y, and transmitted to the soft decision detection signal. The hard decision is made based on the constellation applied during modulation on the side, and the hard decision detection signal is calculated,
The order rearrangement processing reads and said ordered list and the detected transmission signal vector, after rearranging the detection transmitted signal vector in accordance with the list, to claim 3, characterized in that outputs the rearrangement result The radio signal separation method as described. A radio receiving apparatus that performs signal detection of a received signal using a propagation path matrix H, a predetermined coefficient α, and a received signal vector x in a MIMO (Multiple Input Multiple Output) system,
An order list in which the order of signal detection is determined for T elements in the transmission signal vector s of the signal transmitted by the wireless transmission device, calculated by G = H ′ ^H H ′ Decompose the matrix G to derive an upper triangular matrix, calculate the _l- th norm in the p-th row of the inverse matrix U of the upper triangular matrix to the power of d _l , calculate β _p, and calculate the inverse matrix U of the upper triangular matrix A detection order determining means for rearranging the β _p values in ascending order and generating an order list for each numerical value obtained by the rearrangement;
Rearrangement means for rearranging the extended propagation path matrix H ′ calculated based on the propagation path matrix H, the coefficient α, and the unit matrix I according to the order list S to calculate the matrix H ″;
QR decomposition means for QR decomposition of the matrix H ″ of R rows and T columns to calculate a unitary matrix Q and an upper triangular matrix R;
Filtering means for filtering the received vector x using a complex conjugate transpose of R rows of the matrix Q;
Using the upper triangular structure of the upper triangular matrix R, backward substitution means for sequentially detecting the T transmission signals by backward substitution;
Order rearrangement means for rearranging the detected T transmission signals in the order of the original transmitted spatial order according to the order list;
A radio receiving apparatus comprising: The sorting means outputs the calculated matrix H ″,
The QR decomposition means outputs the matrix Q and the matrix R;
The filtering means calculates a vector y by multiplying the complex conjugate transpose of R rows of the matrix Q and the received signal vector x,
The backward substitution means calculates a detected transmission signal vector by backward substitution arithmetic processing using the column vector y and the upper triangular matrix R, and sequentially detects T elements of the detected transmission signal vector. Then, an interference component is calculated according to an interference component calculation formula, a soft decision detection signal is calculated by subtracting the interference component from the _kth element y _{k of the} column vector y, and transmitted to the soft decision detection signal. The hard decision is made based on the constellation applied during modulation on the side, and the hard decision detection signal is calculated,
The order sorting unit reads said ordered list and the detected transmission signal vector, after rearranging the detection transmitted signal vector in accordance with the list, to claim 5, characterized in that outputs the rearrangement result The wireless receiving device described. A radio receiving apparatus that performs signal detection of a received signal using a propagation path matrix H, a predetermined coefficient α, and a received signal vector x in a MIMO (Multiple Input Multiple Output) system,
An order list in which the order of signal detection is determined for T elements in the transmission signal vector s of the signal transmitted by the wireless transmission device, calculated by G = H ′ ^H H ′ The matrix G is decomposed to derive a lower triangular matrix, the _l- th norm in the p-th row of the inverse matrix U of the lower triangular matrix is raised to the d ₁ power to calculate β _p, and the inverse matrix U of the lower triangular matrix is calculated A detection order determining means for rearranging the β _p values in ascending order and generating an order list for each numerical value obtained by the rearrangement;
Rearrangement means for rearranging the extended propagation path matrix H ′ calculated based on the propagation path matrix H, the coefficient α, and the unit matrix I according to the order list S to calculate the matrix H ″;
QR decomposition means for QR decomposition of the matrix H ″ of R rows and T columns to calculate a unitary matrix Q and a lower triangular matrix R;
Filtering means for filtering the received vector x using a complex conjugate transpose of R rows of the matrix Q;
Forward substitution means for sequentially detecting the T transmission signals by forward substitution using the lower triangular structure of the lower triangular matrix R;
Order rearrangement means for rearranging the detected T transmission signals in the order of the original transmitted spatial order according to the order list;
A radio receiving apparatus comprising: The sorting means outputs the calculated matrix H ″,
The QR decomposition means outputs the matrix Q and the matrix R;
The filtering means calculates a vector y by multiplying the complex conjugate transpose of R rows of the matrix Q and the received signal vector x,
The forward substitution means calculates a detection transmission signal vector by forward substitution calculation processing using the column vector y and the lower triangular matrix R, and sequentially detects T elements of the detection transmission signal vector. Then, an interference component is calculated according to an interference component calculation formula, a soft decision detection signal is calculated by subtracting the interference component from the _kth element y _{k of the} column vector y, and transmitted to the soft decision detection signal. The hard decision is made based on the constellation applied during modulation on the side, and the hard decision detection signal is calculated,
The order sorting unit reads said ordered list and the detected transmission signal vector, after rearranging the detection transmitted signal vector in accordance with the list, to claim 7, characterized in that outputs the rearrangement result The wireless receiving device described. A program that is executed by a computer of a wireless reception device that performs signal detection of a received signal using a propagation path matrix H, a predetermined coefficient α, and a received signal vector x in a MIMO (Multiple Input Multiple Output) system,
An order list in which the order of signal detection is determined for T elements in the transmission signal vector s of the signal transmitted by the wireless transmission device, calculated by G = H ′ ^H H ′ Decompose the matrix G to derive an upper triangular matrix, calculate the _l- th norm in the p-th row of the inverse matrix U of the upper triangular matrix to the power of d _l , calculate β _p, and calculate the inverse matrix U of the upper triangular matrix A detection order determination process for rearranging the β _p values in ascending order and generating an order list for each numerical value obtained by the rearrangement;
A rearrangement process for rearranging the extended channel matrix H ′ calculated based on the channel matrix H, the coefficient α, and the unit matrix I according to the order list S to calculate a matrix H ″;
QR decomposition of the matrix H ″ of R rows and T columns to calculate a unitary matrix Q and an upper triangular matrix R by QR decomposition;
A filtering process for filtering the received vector x using a complex conjugate transpose of R rows of the matrix Q;
Using the upper triangular structure of the upper triangular matrix R, backward substitution processing for sequentially detecting the T transmission signals by backward substitution;
An order rearrangement process for rearranging the detected T transmission signals according to the order list and outputting them in the original transmitted spatial order;
A program that causes a computer to execute. In the rearrangement process, the calculated matrix H ″ is output,
In the QR decomposition process, the matrix Q and the matrix R are output,
In the filtering process, a vector y is calculated by multiplying the complex conjugate transpose of the R rows of the matrix Q and the received signal vector x,
In the backward substitution process, a detected transmission signal vector is calculated by a backward substitution calculation process using the column vector y and the upper triangular matrix R, and T elements of the detected transmission signal vector are sequentially detected. Calculating an interference component according to an interference component calculation formula, subtracting the interference component from the k-th element y _{k of the} column vector y, calculating a soft decision detection signal, and for the soft decision detection signal, Based on the constellation applied at the time of modulation on the transmission side, hard decision is performed and a hard decision detection signal is calculated,
In the order rearrangement process, the detection transmission signal vector and the order list are read, and after the detection transmission signal vector is rearranged according to the list, each process of outputting the rearrangement result is executed by the computer. Item 10. The program according to Item 9 . A program that is executed by a computer of a wireless reception device that performs signal detection of a received signal using a propagation path matrix H, a predetermined coefficient α, and a received signal vector x in a MIMO (Multiple Input Multiple Output) system,
An order list in which the order of signal detection is determined for T elements in the transmission signal vector s of the signal transmitted by the wireless transmission device, calculated by G = H ′ ^H H ′ The matrix G is decomposed to derive a lower triangular matrix, the _l- th norm in the p-th row of the inverse matrix U of the lower triangular matrix is raised to the d ₁ power to calculate β _p, and the inverse matrix U of the lower triangular matrix is calculated A detection order determination process for rearranging the β _p values in ascending order and generating an order list for each numerical value obtained by the rearrangement;
A rearrangement process for rearranging the extended channel matrix H ′ calculated based on the channel matrix H, the coefficient α, and the unit matrix I according to the order list S to calculate a matrix H ″;
QR decomposition processing for calculating the unitary matrix Q and the lower triangular matrix R by QR decomposition of the matrix H ″ of R rows and T columns;
A filtering process for filtering the received vector x using a complex conjugate transpose of R rows of the matrix Q;
Using the lower triangular structure of the lower triangular matrix R, forward substitution processing for sequentially detecting the T transmission signals by forward substitution;
An order rearrangement process for rearranging the detected T transmission signals according to the order list and outputting them in the original transmitted spatial order;
A program that causes a computer to execute. In the rearrangement process, the calculated matrix H ″ is output,
In the QR decomposition process, the matrix Q and the matrix R are output,
In the filtering process, a vector y is calculated by multiplying the complex conjugate transpose of the R rows of the matrix Q and the received signal vector x,
In the forward substitution process, a detected transmission signal vector is calculated by a forward substitution calculation process using the column vector y and the lower triangular matrix R, and T elements of the detected transmission signal vector are sequentially detected. Calculating an interference component according to an interference component calculation formula, subtracting the interference component from the k-th element y _{k of the} column vector y, calculating a soft decision detection signal, and for the soft decision detection signal, Based on the constellation applied at the time of modulation on the transmission side, hard decision is performed and a hard decision detection signal is calculated,
In the order rearrangement process, the detection transmission signal vector and the order list are read, and after the detection transmission signal vector is rearranged according to the list, each process of outputting the rearrangement result is executed by the computer. the program according to claim 1 1. Computer readable recording medium having recorded the claims 1 2 or programs of Claims 9.

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