JP2006222743A - Space multiplex signal detection circuit - Google Patents

Abstract

<P>PROBLEM TO BE SOLVED: To obtain an excellent error rate characteristic by suppressing an increase in circuit scale even if a modulation multivalued number is particularly increased in the case of receiving a signal subjected to space multiplexing to detect the signal. <P>SOLUTION: A metric arithmetic circuit 112 for a plurality of transmission signal candidates generates a replica signal by multiplying components S108 corresponding to N-row vectors of an upper triangle matrix outputted from a QR separation circuit 103 by a plurality of transmission signal candidates S112, and subtracts the replica signal from elements S107 of N transmission systems stored in a multiplication result storage circuit 106 to calculate a metric S113 by each transmission system. A metric summation storage circuit 113 accumulates and sums up the metrics S113 of the N transmission systems in accordance with a transmission signal sequence S115 stored in a transmission signal sequence storage circuit 111 and stores the result as the metric of the N transmission systems. <P>COPYRIGHT: (C)2006,JPO&NCIPI

Description

  The present invention relates to a demodulator that detects a signal from a spatially multiplexed signal in a digital wireless communication system, and more particularly to spatial multiplexing that can be applied to an OFDM (Orthogonal frequency division multiplex) modulation scheme among the multicarrier modulation schemes. The present invention relates to a signal detection circuit.

  The multicarrier modulation scheme is a wireless transmission scheme that transmits information using a plurality of subcarriers. The input data signal is modulated by QPSK (Quadrature phase shift keying) or the like for each subcarrier. In this multicarrier modulation method, the orthogonal multicarrier modulation method in which the frequencies of the subcarriers are orthogonal is also called orthogonal frequency division multiplexing (OFDM), and wireless communication in which multipath propagation is a problem. Widely applied in the system.

  OFDM is a modulation scheme suitable for high-speed transmission with features that are not easily affected by multipath. However, in order to further improve the transmission rate, transmission is performed on the same frequency using multiple transmission antennas. It is conceivable to perform spatial multiplexing transmission using a spatially multiplexed signal. This spatial multiplexing transmission is called SDM (Space division multiplexing) transmission or MIMO (Multi input multi output) transmission because of the characteristics of the transmission path of the spatial multiplexing transmission system using a plurality of transmission antennas in the transceiver.

  FIG. 10 is a block diagram for explaining the spatial multiplexing transmission. In FIG. 10, four antennas are provided on each of the transmission side and the reception side. When performing spatial multiplexing transmission, there is no need to increase the frequency bandwidth. For example, when spatial multiplexing transmission is applied to OFDM, it is necessary to transmit the OFDM symbols in synchronization with the transmission timing. When performing the spatial multiplexing transmission, if it is desired to double the transmission rate, transmission is performed simultaneously from two antennas. When it is desired to triple the transmission, the transmission is performed simultaneously using three antennas. Of course, it is also possible to perform transmission from one transmission antenna without multiplexing.

Furthermore, the number of transmission systems for transmission and the number of antennas on the data reception side need not be the same as the number of antennas used on the transmission side, and these values are determined according to system requirements. Here, the transmission antenna is generalized as N and the reception antenna as M. The received signal Y can be expressed as Equation (1) using an M × N transfer function H of the propagation path using a matrix representation in the frequency domain. Here, a case where M ≧ N is shown as an example. Matrix elements such as h _MN in Equation (1) indicate transfer functions between the transmitting and receiving antennas. Here, W represents noise and is represented by an M-dimensional M × 1 column vector.

  In order to detect the transmission signal of each transmission system from the spatially multiplexed reception signal represented by Equation (1) in the demodulator, a ZF (Zero-forcing) method, an MMSE (Minimum mean square error) method, an OSD (Ordered successive) detection) method, maximum likelihood detection (MLD) method, and the like. Among them, the error rate characteristic of the MLD method is the best. From a different perspective, the fact that the error rate characteristics are excellent means that communication with a low CNR is possible, which contributes to the expansion of the communication area. Further, when MLD is used, demodulation is possible even if reception is performed with one receiving antenna. Further, when a plurality of antennas are used on the reception side, there is a feature that a reception diversity effect can be obtained.

  Here, a signal detection method for performing signal detection from a spatially multiplexed signal is sometimes called signal separation or interference canceller, but the essence is that a signal transmitted from a multiplexed signal for each transmission system is used. Is to detect. Signal detection when the MLD method is used is realized as follows. Here, FIG. 11 is a conceptual diagram for explaining a conventional MLD system. The MLD scheme is not a scheme that can be applied only to the multicarrier modulation scheme, but is a technique that can be generally applied to single carrier transmission. Here, the case where it applies to the subcarrier signal after multicarrier demodulation is shown as an example. In the MLD method, signal detection is performed on the subcarrier signal, which is the FFT circuit output signal, using the channel estimation result. The principle of MLD signal detection is shown in Equation (2).

  However,

Indicates the kth transmission signal sequence candidate,

Indicates the i-row vector of the M × N-MIMO matrix of the estimated channel matrix obtained after channel estimation. In Equation (2), maximum likelihood estimation is performed using a metric μ which is one scale. In the MLD method, the signal point distance between the replica signal and the reception signal is calculated for each reception system. Thereafter, the signal point distances obtained in the respective receiving systems are added, and maximum likelihood estimation is performed using the result. Of course, signal detection by the MLD method is possible even with one receiving system, and in this case, only the result of one receiving system is used. Among the added signal point distances, the one with the shortest signal point distance is selected as the most probable combination of transmission signals. And the transmission signal of the signal of this combination is output as a signal detection estimation result. As described above, since the MLD method performs a full search for all combinations of replicas of transmission signals, the error rate characteristics are improved and excellent communication can be realized.

  On the other hand, there are the following examination examples. FIG. 12 is a block diagram showing a configuration of a conventional spatial multiplexing signal detection circuit (see, for example, Non-Patent Document 1). The operation will be described below. FIG. 12 shows a case where the demodulation circuit demodulates transmission signals transmitted from N transmission systems using the M reception system.

  The received signal S1 is multicarrier demodulated by M FFT circuits 1 and 1, and outputs a subcarrier signal S2. The subcarrier signal S2 is input to the channel estimation circuit 2, the channel distortion of the propagation path is estimated from the subcarrier signal S2, and the channel estimation signal S3 is output. On the other hand, the transmission signal generation circuit 3 outputs an m-value transmission signal having a modulation multi-level number of m. The replica signal generation circuit 4 performs complex multiplication of the m-value transmission signal S4 and the channel estimation signal S3 to generate a replica signal S5 of the reception signal. The complex multiplier specifically required here is obtained as follows.

Considering transmission of m values-transmission signals for N transmission systems, there are m ^N possible transmission signal point candidates. Since it is necessary to perform complex multiplication for each transmission system to generate each replica, m ^N × N are required. Further, when processing is performed for a plurality of reception systems on the reception side, finally, M × m ^N × N complex multipliers are required. Next, the signal point distance calculation circuit 5 performs signal point distance calculation between the subcarrier signal S2 in each reception system and the replica signal S5 in each reception system. This signal point distance calculation circuit calculates the signal point distance in each reception system as shown in Equation (2) and adds the values of each reception system to calculate the final metric signal S6. Further, the number of times of the distance calculation can be specifically calculated as follows.

The total number of replica signals outputted from the replica signal generation circuit 4 is a m ^N pieces. Since the signal point distance in each receiving system is calculated for this replica signal, the total number of distance calculations is M × m ^N. This metric signal S6 is input to the full-search maximum likelihood estimation circuit 6 to perform maximum likelihood estimation. Signal detection is performed on the assumption that the replica signal having the smallest metric, that is, the distance between signal points among the input signals, is the most likely combination of transmission signals, and N transmission signals corresponding thereto are output.

As described above, the conventional spatial multiplexing signal detection circuit shown in FIG. 12 performs signal detection by maximum likelihood estimation of a spatially multiplexed signal. First, the signal point distance between the received signal and the replica signal is calculated for each reception system, and the replica signal indicating the distance between the signal points, which is the smallest metric for this result, is selected, and the signal constituting this replica signal Is detected.
A. A. van Zelst, R.C. R. van Nee, and G. A. GA Awater, “Space division multiplexing (SDM) for OFDM systems, Proc. Of VTC 2000-Spring, pp. 1070-1074.

  Currently, backward compatibility with the IEEE 802.11g standard in which the operating frequency band is changed to the 2.4 GHz band using signals in the same wireless section as the IEEE 802.11a standard or IEEE 802.11a standard of the wireless LAN transmission system. In order to realize high-quality and a high transmission rate, studies on a wireless LAN using spatial multiplexing transmission are in progress. For example, in the task group (TG) n in the IEEE 802 committee, studies aiming at application of spatial multiplexing transmission of 2 × 2 or more have been started.

  In a wireless LAN that realizes this wireless backward compatibility and uses spatial multiplexing transmission, the signal conforming to IEEE 802.11a is an OFDM signal before being multiplexed and corresponds to an existing system. FIG. 13 shows an example of a packet format that takes this backward compatibility into consideration. FIG. 14 shows a packet format in a two-dimensional representation using a frequency axis-time axis having a common part with the IEEE802.11a signal.

  In these packets, in order to realize backward compatibility, a preamble signal that can be demodulated by the existing system is transmitted at the beginning of the packet, and then an existing system signal indicating the packet information is transmitted as necessary. Is done. However, since the data portion is spatially multiplexed and transmitted, application of a high-performance spatial multiplexing signal detection method is very important for improving communication quality. Furthermore, even when all transmitted packets are transmitted as spatially multiplexed signals, it is naturally important to apply a high-performance signal detection method. As a technique for realizing high-performance signal detection in this spatial multiplexing transmission, it is conceivable to apply the MLD method having excellent error rate characteristics.

Also, in order to realize further increase in transmission speed, 64QAM having a large modulation multi-level number (m = 64) is often applied to subcarrier modulation of a signal before multiplexing. When such a modulation multi-level number is large, the conventional spatial multiplexing signal detection circuit increases the circuit scale because a full search of the replica signal and the received signal is performed as shown in Equation (2). If the number of transmission systems is N, the number of reception systems at the demodulator is M, and the number of signals to be transmitted is m, the number of complex multipliers required at the time of replica generation is only M × m ^N × N. Thus, the circuit scale increases. In particular, when a modulation scheme with a large number of modulation multi-values is applied to increase the speed, the circuit scale increases exponentially, so the effect is more serious.

  Further, specifically, the complex multiplier circuit includes four real number multipliers having a large circuit scale and two adders. Therefore, using many complex multiplication circuits means that the circuit scale increases. In particular, in a wireless LAN that frequently uses a PCMCIA card or the like, there is a limit to the circuit scale allowed for the PCMCIA card.

Further, the number of distance calculations required for signal point distance calculation in a circuit according to the prior art is M × m ^N under the same parameters as described above, which directly leads to an increase in circuit scale. At this time, two real number multipliers and three real number adders are required for one distance calculation, and since the total number of distance calculations is large, an increase in circuit scale is inevitable.

  Furthermore, power consumption increases in proportion to the increase in circuit scale. In particular, when considering use in a wireless LAN or the like where it is difficult to use an external power source, there is a problem that an increase in power consumption accelerates battery consumption.

  The present invention has been made in consideration of such circumstances, and the object thereof is to solve these problems, and in particular, when receiving a spatially multiplexed signal and performing signal detection, the modulation multi-value number It is an object of the present invention to provide a spatial multiplexing signal detection circuit that can suppress an increase in circuit scale and realize an excellent error rate characteristic even when the signal is increased.

In order to solve the above-described problems, the present invention provides a channel estimation unit that receives a plurality of received signals and estimates channel distortion of a channel between transmission and reception antennas, and a channel estimated by the channel estimation unit. Estimated channel matrix generating means for generating an estimated channel matrix having distortion as a component, and QR decomposition means for performing unitary and triangulation (QR) decomposition operations on the estimated channel matrix generated by the estimated channel matrix generating means; , a complex conjugate transpose operation means for performing a Q ^H is the complex conjugate transpose operation with respect to the unitary matrix Q obtained by the QR decomposition unit, by using the calculation result by the complex conjugate transpose operation unit, constituting the plurality of received signals a matrix multiplication means for performing a matrix multiplication of the Q ^H × r to the received column vector signal r whose elements, the matrix multiplication means A multiplication result storage means for storing a calculation result of the transmission system; an output signal of each transmission system obtained from the multiplication result storage means; a matrix element signal of an upper triangular matrix R which is another output signal of the QR decomposition means; And transmission signal estimation means for estimating a transmission signal of each desired transmission system using an interference signal that is a signal other than the desired transmission system, and transmission signal generation for generating a signal that may be transmitted from the transmitter Means, a signal point distance calculating means for calculating a signal point distance between the estimated transmission signal estimated by the transmission signal estimating means and the transmission signal generated by the transmission signal generating means, and calculated by the signal point distance calculating means A signal candidate narrowing means for selecting a plurality of estimated transmission signals of each transmission system as candidates in order from a signal point distance that is the smallest among the signal point distances, A signal sequence addition storage unit that stores a plurality of estimated transmission signals of each transmission system selected by the signal candidate narrowing unit and information of each transmission system together as an estimated transmission signal sequence; and the signal candidate narrowing unit Matrix elements of an upper triangular matrix R which is a plurality of estimated transmission signals of each transmission system selected by the above, an output signal of each transmission system stored in the multiplication result storage means, and another output signal of the QR decomposition means Signal candidate metric calculation means for calculating each metric in a plurality of estimated transmission signals of each transmission system using an interference signal which is a signal and a signal other than a desired transmission system, and is stored in the signal sequence storage means Metrics for adding and storing each metric calculated by the signal candidate metric calculation means according to a plurality of estimated transmission signals of each transmission system. Based on the addition storage means, the estimated transmission signal of each transmission system stored in the signal sequence addition storage means, and the matrix element signal of the upper triangular matrix R which is another output signal of the QR decomposition means, Interference signal generating means for generating an interference signal that is a signal other than a desired transmission system, each estimated transmission signal sequence stored in the signal sequence addition storage means, and the estimated transmission signal output from the metric addition storage means Maximum likelihood estimation means for outputting a signal sequence indicating the smallest metric among the already added metric signals corresponding to the sequence as a finally estimated transmission signal sequence is provided.

  According to the present invention, in the above invention, the channel estimation unit further generates a weighted information signal of an estimated channel matrix, and uses the weighted information signal output separately from the channel estimation unit, and the estimated channel matrix generation unit A sequence of transmission signal sequences output from the maximum likelihood estimation means using weighting means for performing weighting according to the transmission system of the estimated channel matrix generated by the above, and weighting information signals output separately from the channel estimation means And rearranging means for performing replacement.

  The present invention, in the above invention, comprises multicarrier demodulation means for performing multicarrier demodulation on the plurality of received signals and outputting a subcarrier signal, wherein the subcarrier signal is the channel estimation means and the matrix multiplication means. And an input signal.

In order to solve the above-described problems, the present invention provides a channel estimation unit that receives a plurality of received signals and estimates channel distortion of a channel between transmission and reception antennas, and a channel estimated by the channel estimation unit. Estimated channel matrix generating means for generating an estimated channel matrix having distortion as a component, and QR decomposition means for performing unitary and triangulation (QR) decomposition operations on the estimated channel matrix generated by the estimated channel matrix generating means; , a complex conjugate transpose operation means for performing a Q ^H is the complex conjugate transpose operation with respect to the unitary matrix Q obtained by the QR decomposition unit, by using the calculation result by the complex conjugate transpose operation unit, constituting the plurality of received signals a matrix multiplication means for performing a matrix multiplication of the Q ^H × r to the received column vector signal r whose elements, the matrix multiplication means A multiplication result storage means for storing a calculation result of the transmission system; an output signal of each transmission system obtained from the multiplication result storage means; a matrix element signal of an upper triangular matrix R which is another output signal of the QR decomposition means; And transmission signal estimation means for estimating a transmission signal of each desired transmission system using an interference signal that is a signal other than the desired transmission system, and transmission signal generation for generating a signal that may be transmitted from the transmitter Means, a signal point distance calculating means for calculating a signal point distance between the estimated transmission signal estimated by the transmission signal estimating means and the transmission signal generated by the transmission signal generating means, and calculated by the signal point distance calculating means A signal candidate narrowing means for selecting a plurality of estimated transmission signals of each transmission system as candidates in order from a signal point distance that is the smallest among the signal point distances, A signal sequence addition storage unit that stores a plurality of estimated transmission signals of each transmission system selected by the signal candidate narrowing unit and information of each transmission system together as an estimated transmission signal sequence; and the signal sequence addition storage A plurality of estimated transmission signal sequences stored in the means, an output signal of each transmission system stored in the multiplication result storage means, and a matrix element signal of the upper triangular matrix R which is another output signal of the QR decomposition means , And a plurality of signal sequence metric calculation means for calculating each metric in a plurality of estimated transmission signal sequences using an interference signal that is a signal other than a desired transmission system, and each of the signal sequence addition storage means Based on the estimated transmission signal of the transmission system and the matrix element signal of the upper triangular matrix R which is another output signal of the QR decomposition means, the desired transmission system Interference signal generating means for generating an interference signal that is a signal other than the above, each estimated transmission signal sequence stored in the signal sequence addition storage means, and the estimated transmission signal sequence output from the multiple signal sequence metric calculation means And a maximum likelihood estimating means for outputting a signal sequence indicating the smallest metric among the corresponding already added metric signals as a finally estimated transmission signal sequence.

  According to the present invention, in the above invention, the channel estimation unit further generates a weighted information signal of an estimated channel matrix, and uses the weighted information signal output separately from the channel estimation unit, and the estimated channel matrix generation unit A sequence of transmission signal sequences output from the maximum likelihood estimation means using weighting means for performing weighting according to the transmission system of the estimated channel matrix generated by the above, and weighting information signals output separately from the channel estimation means And rearranging means for performing replacement.

  The present invention, in the above invention, comprises multicarrier demodulation means for performing multicarrier demodulation on the plurality of received signals and outputting a subcarrier signal, wherein the subcarrier signal is the channel estimation means and the matrix multiplication means. And an input signal.

According to the present invention, the channel estimation means estimates the channel distortion of the channel between the transmitting and receiving antennas, and the estimated channel matrix generation means generates an estimated channel matrix having the estimated channel distortion as a component. by QR decomposition unit performs unitary triangulation (QR) decomposition operation for the estimated channel matrix, the complex conjugate transpose operation means performs Q ^H is the complex conjugate transpose operation with respect to the unitary matrix Q, matrix multiplication By means of the complex conjugate transpose operation result, a matrix multiplication operation of Q ^H × r is performed on the reception column vector signal r having a plurality of reception signals as components, and the operation result of each transmission system is stored as the multiplication result The transmission signal estimation means stores the output signal of each transmission system, the matrix element signal of the upper triangular matrix R, and the interference signal that is a signal other than the desired transmission system. Is used to estimate the transmission signal of each desired transmission system, the transmission signal generation means generates a signal that may be transmitted from the transmitter, and the signal point distance calculation means estimates the estimated transmission signal. The signal point distance between the transmission signal and the generated transmission signal is calculated, and a plurality of estimated transmission signals of each transmission system are sequentially obtained by a predetermined number from the smallest signal point distance among the signal point distances by the signal candidate narrowing means. Selecting as a candidate, storing a plurality of estimated transmission signals of each selected transmission system and the information of each transmission system in the signal sequence addition storage means as each estimated transmission signal series, by the signal candidate metric calculation means, Using a plurality of estimated transmission signals of each selected transmission system, stored output signals of each transmission system, matrix element signals of the upper triangular matrix R, and interference signals that are signals other than the desired transmission system Calculating each metric in the plurality of estimated transmission signals of each transmission system, adding and storing each calculated metric in the metric addition storage means according to the plurality of estimated transmission signals of each transmission system, and interference signal generating means Based on the estimated transmission signal of each transmission system and the matrix element signal of the upper triangular matrix R, an interference signal that is a signal other than the desired transmission system is generated, and each estimated transmission signal sequence is generated by the maximum likelihood estimation means. And the signal sequence indicating the smallest metric among the already added metric signals corresponding to the estimated transmission signal sequence is output as the finally estimated transmission signal sequence. Therefore, it is also characterized by calculating a metric for each transmission system, and there is an advantage that an excellent error rate characteristic can be realized while reducing the circuit scale while reducing the time required for the metric calculation.

  Further, according to the present invention, the channel estimation means further generates a weighted information signal of the estimated channel matrix, and the weighting means performs weighting according to the transmission system of the estimated channel matrix using the weighted information signal. The rearrangement means rearranges the transmission signal series output from the maximum likelihood estimation means using the weighted information signal. Therefore, it is possible to estimate a plurality of signals from a system having a high SNR in the transmission system by using a weighting method according to the SNR of the transmission system, and to perform highly accurate signal detection. The number of candidates can be reduced. Therefore, the number of search signal points can be reduced, and there is an advantage that excellent error rate characteristics can be realized while reducing the circuit scale.

  According to the present invention, the multicarrier demodulation means performs multicarrier demodulation on the plurality of received signals to generate a subcarrier signal, and the subcarrier signal is converted to the channel estimation means and the matrix multiplication means. Input signal. Therefore, the present invention can be applied to an OFDM modulation scheme that requires multi-carrier demodulation, and an advantage that an excellent error rate characteristic can be realized while reducing the circuit scale.

Further, according to the present invention, the channel estimation means estimates the channel distortion of the channel between the transmitting and receiving antennas, and the estimated channel matrix generation means calculates the estimated channel matrix having the estimated channel distortion as a component. produced by QR decomposition unit performs unitary triangulation (QR) decomposition operation for the estimated channel matrix, the complex conjugate transpose operation means performs Q ^H is the complex conjugate transpose operation with respect to the unitary matrix Q, The matrix multiplication means uses the complex conjugate transpose calculation result to perform a Q ^H × r matrix multiplication operation on the received string vector signal r having a plurality of received signals as components, and multiplies the calculation result of each transmission system. Stored in the result storage means, and by the transmission signal estimation means, the output signal of each transmission system, the matrix element signal of the upper triangular matrix R, and the signal other than the desired transmission system Using the interference signal, the transmission signal of each desired transmission system is estimated, a signal that may be transmitted from the transmitter is generated by the transmission signal generation means, and the estimation estimated by the signal point distance calculation means The signal point distance between the transmission signal and the generated transmission signal is calculated, and a plurality of estimated transmissions of each transmission system are sequentially performed by a predetermined number from the signal point distance having the smallest signal point distance by the signal candidate narrowing means. A signal is selected as a candidate, and a plurality of estimated transmission signals of each selected transmission system and information of each transmission system are combined and stored in the signal sequence addition storage means as each estimated transmission signal sequence, and a multiple signal sequence metric calculation is performed. Means, using a plurality of estimated transmission signal sequences, stored output signals of each transmission system, matrix element signals of the upper triangular matrix R, and interference signals that are signals other than the desired transmission system, Each metric in the estimated transmission signal sequence is calculated, and interference that is a signal other than the desired transmission system is calculated based on the estimated transmission signal of each transmission system and the matrix element signal of the upper triangular matrix R by the interference signal generation unit. A transmission signal generated by a signal, and finally estimated by the maximum likelihood estimation means, a signal sequence indicating the smallest metric among each estimated transmission signal sequence and the already added metric signal corresponding to the estimated transmission signal sequence Output as a series. Therefore, the metric is calculated for each transmission signal sequence at the final stage, and the control process associated with the metric calculation is simplified, and an excellent error rate characteristic can be realized while reducing the circuit scale. Is obtained.

  Further, according to the present invention, the channel estimation means further generates a weighted information signal of the estimated channel matrix, and the weighting means performs weighting according to the transmission system of the estimated channel matrix using the weighted information signal. The rearrangement means rearranges the transmission signal series output from the maximum likelihood estimation means using the weighted information signal. Therefore, it is possible to estimate a plurality of signals from a system having a high SNR in the transmission system by using a weighting method according to the SNR of the transmission system, and to perform highly accurate signal detection. The number of candidates can be reduced. Therefore, the number of search signal points can be reduced, and there is an advantage that excellent error rate characteristics can be realized while reducing the circuit scale.

  According to the present invention, the multicarrier demodulation means performs multicarrier demodulation on the plurality of received signals to generate a subcarrier signal, and the subcarrier signal is converted to the channel estimation means and the matrix multiplication means. Input signal. Therefore, the present invention can be applied to an OFDM modulation scheme that requires multi-carrier demodulation, and an advantage that an excellent error rate characteristic can be realized while reducing the circuit scale.

  Hereinafter, a spatial multiplexing signal detection circuit according to an embodiment of the present invention will be described with reference to the drawings.

A. First, the basic principle of the present invention will be described. The present invention realizes a spatial multiplexing signal detection circuit that realizes an excellent error rate characteristic equivalent to that of the MLD method while suppressing an increase in circuit scale, which is a problem in the prior art. The present invention can be applied to both a multicarrier modulation system and a single carrier modulation system. When applied to a multicarrier modulation scheme, it is applied to a subcarrier signal after multicarrier demodulation.

  In the present invention, first, the channel estimation of the transfer function between the transmitting and receiving antennas is performed using the MIMO preamble signal of the received packet signal (channel estimation means). And the estimation channel matrix H is produced | generated using the channel estimation result (estimation channel matrix production | generation means). Next, as shown in Equation (5), unitary and triangulation (QR) decomposition of this estimated channel matrix is performed (QR decomposition means). However, in Formula (5), the formula modification which applied QR decomposition | disassembly with respect to an estimation channel matrix is shown for simplification of description. The following is a case where M ≧ N. The unitary matrix Q shown in Equation (6) is an M × M orthonormal matrix, and the triangular matrix R shown in Equation (7) is M × M. N matrix, which is composed of an upper triangular matrix R and a zero matrix. Naturally, when M = N, the triangular matrix R is configured as an upper triangular matrix R having no 0 matrix portion.

  However,

  Alternatively, when expressing the unitary matrix Q as an M × N matrix as another expression of Equation (5), the triangulation matrix R is QR-decomposed as an N × N matrix.

  As a calculation method used for this QR decomposition, naturally, the application of the Gram-Schmidt orthogonalization method can be considered. In this case, among the elements of the upper triangular matrix R, an element (diagonal component) having the same row number and column number is a real number. In general, the diagonal component of the upper triangular matrix R in the QR decomposition is not necessarily a real number, but by performing the QR decomposition operation so that it becomes a real number, a division operation such as Equation (10) described later can be simplified. Of course, it can be realized.

  Furthermore, the essence of the QR decomposition is to divide the transfer function matrix H into a unitary matrix Q and an upper triangular matrix R, and rotate each matrix element. As a result, the upper triangular matrix is sequentially generated. Of course, it is possible to apply the Givens method and the Householder method in which “0” elements of the upper triangular matrix are added in units of rows and columns.

  Furthermore, in the present invention, a complex conjugate operation of each matrix element is performed on the unitary matrix Q, and then a transpose operation process of the matrix is performed (complex conjugate transpose operation means). This complex conjugate transposition may be called by various names such as Hermitian transpose and Hermitian conjugate, but the essence of the operation here is to perform complex conjugate operation on each element of unitary matrix and generate transpose matrix of that matrix That is.

Next, the multiplication from the left side of Q ^H is the complex conjugate transpose matrix of the resulting unitary matrix by the QR decomposition on the received signal Y (matrix multiplication means). By performing this processing, the received signal can be simply shown as a multiplication of the triangulation matrix and the transmission signal, as shown in Equation (8).

Further, as a feature in the case of this matrix multiplication, it is a feature of the present invention that noise enhancement is not generated in QR decomposition because each column vector is multiplied by a unitary matrix Q ^H that is orthonormal.

It is also a further feature of the present invention to noise enhancement due to the multiplication of the Q ^H since the eigenvalues of the unitary matrix used in the QR decomposition are all 1 does not occur. In this way, a column vector Z = [z ₁ , z ₂ ,..., Z _M ] ^T which is an operation result is obtained, and each value is stored (multiplication result storage means).

Furthermore, in the present invention, after this unitary matrix multiplication, transmission signals are estimated for each transmission system in sequence. First, to estimate the a transmission signal of the transmission system corresponding to the bottom line of the upper triangular matrix t _N. Next, the transmission signal of the transmission system corresponding to the N-1 row of the upper triangular matrix is estimated. In the present invention, a process of sequentially raising the layer of the transmission system to be repeatedly estimated while removing the interference component of the other transmission system is performed.

The specific procedure is as follows.
First, the interference signal of the other transmission system is subtracted from each element of the stored column vector Z, and the following division processing is performed using each matrix element of the desired transmission system of the upper triangular matrix R (transmission signal estimation means) ). However, in the case of the transmission system N which is the lowest layer, it is not necessary to consider the interference signal of the other transmission system (from the interference signal generating means). First, the case where calculation is performed for the N transmission systems will be described below.

The signal point t _N in the case of the transmission system N soft determines.

  Furthermore, naturally, not only the soft decision result but also the hard decision result can be used for transmission signal estimation.

  In the following, for the sake of simplicity, the flow of processing is first shown for the case of transmission signal estimation in the case of the transmission system N, and the case of the transmission systems of N-1, N-2,. go. Next, after the transmission signal is estimated, the m-valued multi-level signal generated by the (transmission signal generation means) as a signal that may be transmitted from the transmitter according to Equation (11). The signal point distance from the signal point s is calculated (signal point distance calculation means).

  However, the case where the square of the Euclidean distance is used is shown here as an example of the distance calculation. Using this calculation result, a predetermined number of signal points are selected as a plurality of transmission signal candidates in the transmission system N in the order indicating the small signal point distance (transmission candidate narrowing means). For example, when the upper 32 signal candidates are selected as an example, a plurality of transmission signal candidates of N transmission systems are selected based on Equation (11) as shown in Equation (12).

  The transmission signals of these transmission systems and the history of each transmission system are stored (transmission sequence addition storage means) and applied to the following metric calculation (interference signal generation means).

On the other hand, by using the element signal z _{N of} the stored column vector Z and r _NN which is the element signal of the upper triangular matrix subjected to QR decomposition, the following metric M is obtained for each of the 32 transmission signal candidates. Calculation is performed as in Equation (13) (signal candidate metric calculation means).

  Here, as the signal point distance calculation and metric used in the present invention, the case where the square of the Euclidean distance is used is shown in the above description, but the specific distance calculation includes the Euclidean distance, the Manhattan distance, and those Naturally, it can be realized by using various distance measures such as the square distance of the distance.

  Next, this metric is stored and held as a cumulative addition metric after being added to the previous metrics together with information on the transmission signal of each transmission system and information on the history of each transmission signal (metric addition storage means). However, the calculation of the cumulative addition metric is executed not in the case of the N transmission system that is the lowest layer but in the case of the N-1 transmission systems that are one layer above. The above is the signal processing flow in the transmission system N which is the lowest layer in the present invention.

Next, processing in the N-1 transmission system will be described. In order to estimate the transmission signal of the N-1 transmission system, an operation for generating an interference signal from the estimation signal of the N transmission system is required. For example, when calculating for the N-1 transmission system, the interference signal is expressed by Equation (14) for all combinations of the element signal r _{N-1 N} of the upper triangular matrix and the estimated transmission signal hat [t _N (l _N )]. As shown in (2) and is generated (interference signal generating means). The above hat corresponds to the symbol (^) in the mathematical formula, and hereinafter the same notation.

  The basic operation when detecting a signal of the N-1 transmission system can be considered as follows. The signal detection procedure of the N-1 transmission system is basically the same operation as the signal detection of the N transmission system. The difference is that the estimated signal of the other transmission system (output from the interference signal generation means) (transmission system N larger than N-1 in the case of N-1 transmission system) is subtracted (transmission signal estimation means). And signal candidate metric calculation means).

First, in practice, as shown in Expression (12), when a plurality of estimated signals of N transmission systems are represented simply as hat [t _N (l _N )], the following Expression (15) To perform a soft decision calculation (transmission signal estimation means). As with the N transmission system, naturally, a hard decision can be applied.

Next, as in the N transmission system, each of a plurality of output signals s (transmission signal generation means) generated as a signal that may be transmitted from the transmitter is represented as shown in Expression (16). For [hat [t _N (l _N )] (signal point distance calculation means).

  Furthermore, using the signal distance obtained by this calculation, a plurality of transmission signal candidates are estimated from the one showing the smaller value of the signal distance (signal candidate narrowing means). For example, when estimating the upper 16 transmission signal candidates, it is estimated as shown in Equation (17).

Moreover, 16 types of hat [t _N-1 (l _N-1 )] used for the 16 types of narrowing down are also obtained. Therefore, in the next metric calculation, the values shown in Equation (18) are obtained as a plurality of estimated signals of N transmission systems.

Here, a major feature of the present invention is that there is no deterioration in characteristics even when the number of signal points considered as candidates is reduced as the estimated transmission system increases. Since the metric is calculated using the transmission signals estimated sequentially, the diversity effect is improved. In the estimation of the upper transmission signal, the transmission signal is estimated after canceling a signal from another transmission system. For higher-order signal estimation, estimation is not performed using only information on the transmission system. For example, for the estimation of the N-1 transmission system, a replica signal of the signal of the N transmission system is subtracted from the matrix multiplication result zN _{-1 of the N-1} transmission system. In this way, the diversity effect is generated because the transmission signal is estimated using the information of the two transmission systems N-1 and N. Therefore, the diversity effect can be obtained even if the number of transmission signal candidates narrowed down as candidates at the upper level is reduced. Of course, the present invention can be applied without decreasing the number of candidates as it goes up.

  The reduction in the number of transmission signal candidates described above will be specifically described. In the present invention, for example, in the case of 64QAM having four transmission systems, the number of narrowing down can be reduced by limiting to “32, 16, 8, 2”, and the number depends on the transmission signal point. It is not necessary to generate all the number of replica signals, and realization with a simple circuit scale is possible.

  Next, a metric is calculated using a plurality of estimated transmission signals of the N-1 transmission system obtained in this way (signal candidate metric calculation means).

  Further, as described above, the metric in the N-1 transmission system and the metric in the previous N transmission system are calculated, and the cumulative addition metric (AM) is calculated as shown in Equation (20) (metric addition). Storage means).

  In addition at this time, a cumulative addition metric is calculated with reference to a signal sequence (signal sequence addition storage means) of each transmission system.

  Subsequently, all the signals up to one transmission system are sequentially estimated, and the process is repeated until the signal sequences of all the transmission systems and the cumulative addition metric are calculated. This is shown in FIG. In this case, the number of transmission signal candidates in the N transmission system is 32, the number of transmission signal candidates in the N-1 transmission system is 16, and finally, the number of candidates in the highest transmission system is 2. As described above, in the present invention, the metric is calculated after sequentially subtracting the number of transmission signal candidates. Further, this calculation need not be performed at the end, but can be performed by calculating each transmission system and accumulating metrics. Therefore, it is possible to reduce the delay time associated with the metric calculation, and it is possible to suppress a decrease in throughput that greatly affects the delay time.

  Furthermore, in the present invention, the final transmission signal sequence is estimated (maximum likelihood estimation means). Specifically, a signal sequence candidate (signal sequence addition storage unit) of each transmission system and a transmission signal sequence indicating the smallest value among the corresponding cumulative addition metrics (metric addition storage unit) are transmitted signals. Output as a series.

As described above, according to the present invention, it is possible to greatly reduce the generation of a huge amount of replica signals that are necessary in the prior art. In the present invention, the number of complex multiplications required by M × m ^N × N in the prior art can be greatly reduced to (64 + 64 ² +... +64 ^N ) in the present invention. Can be significantly reduced to (1 + 2 +... + N) × m when interference signals are stored instead of sequentially calculating. For example, normally, in the case of N = 4 transmission systems, when 64QAM with m = 64 is used, operation can be performed with the number of candidates of about 32 + 8 + 2 + 1. In this case, for example, the number of complex multiplications can be significantly reduced to about 32+ (32 + 16) + (32 + 16 + 8) + (32 + 16 + 8 + 1) = 78.

Furthermore, as described above, the calculation of the signal point distance necessary for the search for the transmission signal, which was necessary in the prior art, can be reduced from M × m ^N to m × N when the reduction is the smallest. The maximum number of signal point distance calculations of the present invention is m × N. For example, in the case of N = 4 transmission systems, when 64QAM with m = 64 is used, the number can be significantly reduced to about 32 × 8 × 2 × 1 = 512.

  Naturally, the number of signal searches is the total number, and the actual calculation is performed for the signal distance for each metric calculation of each transmission system. Therefore, it is naturally possible to share the complex multiplier used for the calculation of each transmission system.

  On the other hand, as a further configuration for improving the characteristics of the present invention, using each channel estimation result, a received SNR (signal to noise ratio), SNIR (signal to noise and interference ratio) of a received signal input from a receiving antenna, Alternatively, it is also possible to apply a weighting method or the like according to the transmission signal system according to the received power (weighting means). Specifically, an operation for replacing the column vectors of the estimated channel matrix according to the SNR and the like is performed. Assuming that the transformation matrix is A which is an M × M matrix as shown in Equation (21), it is possible to perform an operation to replace the column vectors of the estimated channel matrix below, and to estimate a transmission signal from a transmission system having a high reception SNR. become. Here, in the case of N = 4 and M = 4, when the reception SNR of each transmission system is in the order of “1, 2, 3, 4” in the descending order, the following is shown.

  When this weighting is used, Equation (5) can be transformed into Equation (22) using the transformation matrix A.

The meaning of this equation (22) is that the column vectors are replaced by HA, and are arranged from the right in the order of higher SNR. In addition, rearrangement is performed from the bottom in order of increasing SNR of the transmission signal vector by H ^A × T. As described above, when weighting based on SNR is performed, QR decomposition can be performed using HA as an HA as shown in Expression (23) instead of H as an estimated channel matrix.

  The subsequent calculation procedure is the same as that in the case where weighting is not used, and can be expressed by Equation (24).

  By using this weighting process, the estimation accuracy for narrowing down transmission signal candidates is improved. As a result, the entire estimated candidate transmission signal can be reduced, and the circuit scale can be reduced.

In this case, the transmission signal finally estimated by the maximum likelihood estimation is a signal after the SNR rearrangement in signal processing, and is not a transmission signal corresponding to the actual transmission system. After the final estimated transmission signal A ^H × T is detected, the transformation matrix A is multiplied as shown in Equation (25), the correct transmission signal is rearranged, and the estimated transmission signal T is output (signal rearrangement). means).

  As described above, the weighting method applied to the present invention is easily realized by a circuit that performs an operation of replacing the column vector of the transfer function matrix according to the SNR or SNIR of the received signal (weighting means). Furthermore, as a further configuration of the present invention, a configuration in which a metric is calculated in the final stage without performing a metric calculation of each transmission system such as Formula (13), Formula (19), and Formula (20) is naturally conceivable. .

  For example, normally, in the case of N = 4 transmission system, when 64QAM with m = 64 is used, the number of candidates is about 32+ (32 + 16) + (32 + 16 + 8) + (32 + 16 + 8 + 1) = 78. Operation is possible. In this case, 32 × 8 × 2 × 1 metric calculation is performed (multiple signal sequence metric calculation means) at the time when a signal candidate of one transmission system as the final stage is estimated, and the final stage is used using this result. The transmission signal sequence with the smallest metric is output as an estimation result (maximum likelihood estimation means). In this case, the control operation for maintaining the relationship between the transmission signal candidate and the metric accompanying the cumulative addition of the metric and the processing of the control signal and the like are unnecessary.

Furthermore, in the present invention, the transmission signal is estimated based on the past transmission signal for each transmission system, as represented by Equation (10), Equation (15), and the like. Then, using the transmission signal estimation results obtained by Equation (10), Equation (15), etc., the transmission signal candidates indicated by Equation (11) and Equation (16) are narrowed down. Therefore, the estimated signal of each transmission system of the present invention naturally depends not only on the information on the desired transmission system but also on the signals of the past transmission system. Specifically, in Equation (15), the transmission signal of the previous N systems indicated by hat [t _N (l _N )] is used for estimating t _N−1 of the N−1 transmission system. It is shown. That is, t _N−1 is obtained individually for each l _{N having} different hat [t _N (l _N )]].

B. First Embodiment Next, a first embodiment of the present invention will be described.
B-1. Configuration of First Embodiment FIG. 2 is a block diagram showing a configuration of a spatial multiplexing signal detection circuit according to the first embodiment of the present invention. The channel estimation circuit 101 performs channel estimation of the transfer function between the transmitting and receiving antennas using the MIMO preamble signal of the received packet signal S101. The estimated channel matrix generation circuit 102 generates an estimated channel matrix H using the channel estimation result. The QR decomposition circuit 103 performs unitary and triangulation (QR) decomposition of the estimated channel matrix as shown in Equation (5). The complex conjugate transpose operation circuit 104 performs a complex conjugate operation of each matrix element on the unitary matrix Q and performs a transpose operation process of the matrix.

Matrix multiplication circuit 105 performs multiplication from the left side of Q ^H is the complex conjugate transpose matrix of the resulting unitary matrix by QR decomposition on the received packet signal S101. The multiplication result storage circuit 106 stores a column vector Z = [z ₁ , z ₂ ,..., Z _M ] ^T that is an operation result of the matrix multiplication circuit 105. The transmission signal estimation circuit 107 subtracts the interference signal S116 of the other transmission system from each element S107 of the column vector Z stored in the multiplication result storage circuit 106, and corresponds to the N row vector output from the QR decomposition circuit 103. By performing a predetermined division process using each matrix element S108 of the desired transmission system of the upper triangular matrix R, the soft decision of the transmission signal is estimated. However, in the case of the transmission system N that is the lowest layer, it is not necessary to consider the interference signal of the other transmission system from the interference signal generation circuit 114.

  The transmission signal generation circuit 108 generates a transmission signal S109 that may be transmitted as a transmission signal. The transmission signal point distance calculation circuit 109 calculates the signal point distance between the soft decision estimation result S110 and the transmission signal S109. The plurality of transmission signal candidate narrowing circuits 110 select a plurality of transmission signal candidates S112 from the one with the smaller signal point distance. The transmission signal sequence storage circuit 111 stores the plurality of transmission signal candidates S112 and the history of each transmission system. The multiple transmission signal candidate metric calculation circuit 112 multiplies the component signal S108 corresponding to the N row vector of the upper triangular matrix output from the QR decomposition circuit 103 and the multiple transmission signal candidates S112 to generate a replica signal, The replica signal is subtracted from each element S107 of the N transmission system stored in the multiplication result storage circuit 106 to calculate the metric of the N transmission system. The metric addition storage circuit 113 cumulatively adds the metrics S113 of the N transmission systems according to the transmission signal sequence S115 stored in the transmission signal sequence storage circuit 111, and stores the result as a metric of the N transmission systems.

  The interference signal generation circuit 114 includes a transmission signal sequence candidate S115 stored in the transmission signal sequence storage circuit 111, a matrix element S108 corresponding to the N−1 row vector of the upper triangular matrix output from the QR decomposition circuit 103, and Thus, the replica S116 of the transmission system larger than the above-described N-1 is generated. The maximum likelihood estimation circuit 115 outputs an estimated transmission sequence S117 having the smallest metric. Among the transmission signal sequence candidates S115 stored in the transmission signal sequence storage circuit 111, and the metric S114 of the N transmission systems accumulated and stored in the transmission signal sequence metric addition storage circuit 113 corresponding thereto. The transmission signal sequence showing the smallest value is output as the final transmission signal sequence.

B-1. Operation of First Embodiment Next, the operation of the first embodiment described above will be described. Received signal S101 is input to channel estimation circuit 101. The channel estimation circuit 101 estimates the propagation path distortion between the transmitting and receiving antennas using the MIMO preamble signal or the preamble signal of the existing system in the received signal. The estimated distortion S102 is input to the estimated channel matrix generation circuit 102 and output as the estimated channel matrix S103. The QR decomposition circuit 103 performs a QR decomposition operation on the estimated channel matrix S103, and performs decomposition into a matrix R including a unitary matrix Q and an upper triangular matrix. The unitary matrix S104 is input to the complex conjugate transpose circuit 104.

  The complex conjugate transpose operation circuit 104 performs complex conjugate computation of each matrix element on the unitary matrix Q, performs transposition computation processing of the matrix, and outputs the result as a complex conjugate transpose matrix S105 of the unitary matrix. The matrix multiplication circuit 105 multiplies the input received signal S101 by the complex conjugate transpose matrix S105 from the left side with the received signal in column vector notation. The multiplication result S106 is stored in the multiplication result storage circuit 106 for one symbol time.

  Thereafter, the signal processing operation of the signal detection circuit shifts to signal detection. First, the transmission signal of the N transmission system which is the lowest layer is estimated. In the transmission signal estimation circuit 107, an upper triangular matrix corresponding to the N-row vector output from the QR decomposition circuit 103 with respect to the element S107 of the N transmission system indicated by the mathematical expression (8) stored in the multiplication result storage circuit 106. By performing the division operation using the component S108, the soft decision of the transmission signal is estimated and output as the estimated signal S110.

  On the other hand, a transmission signal S109 that may be transmitted as a transmission signal is output from the transmission signal generation circuit 108, and the transmission signal point distance calculation circuit 109 outputs a signal point between the estimated signal S110 and the transmission signal S109. The signal point distance calculation is performed. The signal point distance signal S111 is input to the multiple transmission signal candidate narrowing circuit 110. The multiple transmission signal candidate narrowing circuit 110 selects a plurality of transmission signal candidates S112 from the one with the smaller signal point distance. The plurality of transmission signal candidates S112 are stored in the transmission signal storage circuit 111 together with information on each transmission system.

  Furthermore, in the multiple transmission signal candidate metric calculation circuit 112, first, a replica signal is generated by multiplication of the component S108 corresponding to the N-row vector of the upper triangular matrix output from the QR decomposition circuit 103 and the multiple transmission signal candidates S112. Then, the replica signal is subtracted from the element S107 of the N transmission system indicated by the mathematical formula (8) stored in the multiplication result storage circuit 106, and the metric S113 of the N transmission system is calculated. The metric S113 of the N transmission system is stored as a metric of the N transmission system in the metric addition storage circuit 113 in accordance with the transmission signal sequence signal S115 stored in the transmission signal sequence storage circuit 111.

  Next, the signal detection processing operation shifts to the N-1 transmission system. For the estimation of the N-1 transmission system, it is necessary to remove interference signals larger than N-1, for example, the N transmission system. A plurality of transmission signals S115 of N transmission systems stored in the transmission signal sequence storage circuit 111 are input to the interference signal generation circuit 114 and correspond to the N−1 row vector of the upper triangular matrix output from the QR decomposition circuit 103 together. The component S108 is also input to the interference signal generation circuit 114. In the interference signal generation circuit 114, a replica signal of a transmission system larger than N-1 is generated. Thereafter, signal estimation is performed in the same manner as in the N transmission system. The main difference between the signal processing of the N transmission system and the signal processing of the N-1 transmission system is only a difference in whether or not the replica signal S116 output from the interference signal generation circuit is used.

  In the transmission signal estimation circuit 107, the replica S116 corresponding to the N transmission system, which is the output of the interference signal generation circuit 114, from the element S107 of the N-1 transmission system represented by the mathematical expression (8) stored in the multiplication result storage circuit 106. Is subtracted. Further, the component S108 of the upper triangular matrix corresponding to the N−1 row vector output from the QR decomposition circuit 103 is divided with respect to the subtraction result, the soft decision of the transmission signal is estimated, and N−1 transmission is performed. It is output as a system estimation signal S110.

  On the other hand, a transmission signal S109 that may be transmitted as a transmission signal is output from the transmission signal generation circuit 108, and the transmission signal point distance calculation circuit 109 outputs a signal point between the estimated signal S110 and the transmission signal S109. The signal point distance calculation is performed. The signal point distance signal S111 is input to the multiple transmission signal candidate narrowing circuit 110. In the multiple transmission signal candidate narrowing circuit 110, a plurality of transmission signal candidates S112 are selected from the one with the smaller signal point distance. At this time, it is naturally possible to reduce the number of transmission signal candidates as the number of transmission systems on which estimation processing is performed increases. This transmission signal candidate S111 is stored in the transmission signal storage circuit 111 together with information on each transmission system. Specifically, it is stored as a transmission signal candidate for the N-1 transmission system.

  Further, in the multiple transmission signal candidate metric calculation circuit 112, as shown in the equation (19), the replica S116 corresponding to the N transmission system, which is the output of the interference signal generation circuit 114, and the upper triangle output from the QR decomposition circuit 103 The component S108 corresponding to the N-1 row vector of the matrix is multiplied by a plurality of transmission signal candidates S112, and then stored in the multiplication result storage circuit 106 as N-1 shown by the equation (8). The metric S113 of the N-1 transmission system is calculated by subtracting each replica from the transmission system element S107.

  The metric addition storage circuit 113 stores the metric S113 of the N-1 transmission system as a metric of the N-1 transmission system according to the transmission signal sequence S115 stored in the transmission signal sequence storage circuit 111. When storing this metric, the metric of the N-1 transmission system is stored as the cumulative addition metric in consideration of the history in the metric of the N transmission system. In this way, this process is repeated sequentially until a transmission signal of one transmission system is estimated. Finally, transmission signal sequence S115 and cumulative metric S114 of the transmission signal sequence are input to maximum likelihood estimation circuit 115, and estimated transmission sequence S117 having the smallest metric is output.

C. Second Embodiment Next, a second embodiment of the present invention will be described. The second embodiment is characterized in that the estimation accuracy of signal detection is improved by performing weighting according to the transmission system before QR decomposition with respect to the first embodiment described above. Further, the estimated transmission signal sequence to be output is replaced.

C-1. Configuration of Second Embodiment FIG. 3 is a block diagram showing a configuration of a spatial multiplexing signal detection circuit according to a second embodiment of the present invention. It should be noted that parts corresponding to those in FIG. The estimation channel matrix weighting circuit 216 weights the estimation channel matrix S103 output from the estimation channel matrix generation circuit 102 according to the information signal S218 used for weighting the transmission sequence output from the channel estimation circuit 101, and the weighting is performed. The estimated channel matrix S 221 is supplied to the QR decomposition circuit 103. The output signal replacement circuit 217 performs rearrangement so that an appropriate transmission signal sequence is obtained in accordance with the information signal S218 used for the weighting.

C-2. Operation of Second Embodiment Next, a second embodiment of the present invention will be described. In the following, only differences from the first embodiment will be described. The estimated channel matrix S103 output from the estimated channel matrix generation circuit 102 is input to the estimated channel matrix weighting circuit 216. Further, an information signal S218 used for weighting the transmission sequence output from the channel estimation circuit 101 is also input. The estimated channel matrix weighting circuit 216 rearranges the column vectors of the estimated channel matrix based on the SNR and the like of the transmission system. The weighted estimated channel matrix S221 is supplied to the QR decomposition circuit 103. On the other hand, the estimated transmission sequence S217 obtained from the maximum likelihood estimation circuit 115 is rearranged in the order of the appropriate transmission signal sequence based on the information signal S218 used for weighting the transmission sequence in the rearrangement circuit 217. Other operations are the same as those in the first embodiment described above.

D. Third Embodiment Next, a third embodiment of the present invention will be described. Compared to the first embodiment described above, the third embodiment does not calculate the metrics in each transmission system, but calculates the metrics at the end when the estimated transmission signal sequence is obtained. It is a feature.

D-1. Configuration of Third Embodiment FIG. 4 is a block diagram showing a configuration of a spatial multiplexing signal detection circuit according to a third embodiment of the present invention. It should be noted that parts corresponding to those in FIG. In the third embodiment, the metric S313 is calculated by the multiple transmission signal series metric calculation circuit 316, and the metric S313 is directly input to the maximum likelihood estimation circuit 115. Therefore, in this case, the metric addition storage circuit 113 that cumulatively adds the metrics of each transmission system is not used.

D-2. Operation of Third Embodiment Next, in the third embodiment, the operation of the multiple transmission signal series metric calculation circuit 316 will be described with reference to Equation (19). In Equation (19), the metric of each transmission system is derived, but the metric is calculated from the estimated transmission sequence over all transmission systems by the same calculation method. For example, assuming that the calculation of Expression (19) is a case of two transmission systems with N = 2, the metric calculation in the third embodiment is performed. Configuration corresponding to the replica S116 corresponding to the N (= 2) transmission system, which is the output signal of the interference signal generation circuit 104, and the N-1 (= 1) row vector of the upper triangular matrix output from the QR decomposition circuit 103 The multiplication result of element S108 and transmission signal sequence candidate S115 is calculated as a replica signal of the N-1 transmission system. Next, the replica signal is subtracted from the element S107 of the N-1 (= 2) transmission system stored in the multiplication result storage circuit 106 to calculate the metric of the N-1 transmission system. This is input to the maximum likelihood estimation circuit 115 as a metric of the estimated transmission signal sequence, and the transmission signal sequence having the smallest metric is selected. Other operations are the same as those of the first embodiment described above.

E. Fourth Embodiment Next, a fourth embodiment of the present invention will be described. In the fourth embodiment, the third embodiment described above is applied to the second embodiment described above, weighting is performed according to the transmission system before QR decomposition, and the estimated transmission to be output is further output. When the signal series is replaced, the metric is calculated at the end of the estimated transmission signal series when the estimated transmission signal series is obtained, instead of calculating the metrics in each transmission system.

E-1. Configuration of Fourth Embodiment FIG. 5 is a block diagram showing a configuration of a spatial multiplexing signal detection circuit according to a fourth embodiment of the present invention. The parts corresponding to those in FIG. In the fourth embodiment, the metric S313 is calculated by the multiple transmission signal series metric calculation circuit 316, and the metric S313 is directly input to the maximum likelihood estimation circuit 115. Therefore, in this case, the metric addition storage circuit 113 that cumulatively adds the metrics of each transmission system is not used.

E-2. Operation of Fourth Embodiment Next, the operation of the third embodiment will be described. The estimated channel matrix S103 output from the estimated channel matrix generation circuit 102 is input to the estimated channel matrix weighting circuit 216. Further, an information signal S 218 used for weighting a transmission sequence output from the channel estimation circuit 101 is also input to the estimation channel matrix weighting circuit 216. The estimated channel matrix weighting circuit 216 rearranges the column vectors of the estimated channel matrix based on the SNR and the like of the transmission system. The weighted estimated channel matrix S221 is input to the QR decomposition circuit 103.

  On the other hand, it corresponds to the replica S116 corresponding to the N (= 2) transmission system, which is the output signal of the interference signal generation circuit 104, and the N-1 (= 1) row vector of the upper triangular matrix output from the QR decomposition circuit 103. The multiplication result of the constituent element S108 and the transmission signal sequence candidate S115 is calculated as a replica signal of the N-1 transmission system. Next, the replica signal is subtracted from the element S107 of the N-1 (= 2) transmission system stored in the multiplication result storage circuit 106 to calculate the metric of the N-1 transmission system. This is input to the maximum likelihood estimation circuit 115 as the metric of the estimated transmission signal sequence, and the transmission signal sequence having the smallest metric is selected and output as the estimated transmission sequence S117. Further, the estimated transmission sequence S217 obtained from the maximum likelihood estimation circuit 115 is rearranged in the order of the appropriate transmission signal sequence by the rearrangement circuit 417 based on the information signal S218 used for weighting the transmission sequence. Other operations are the same as those in the second embodiment.

F. Fifth Embodiment Next, a fifth embodiment of the present invention will be described. The fifth embodiment is characterized in that the received signal S101 is a subcarrier signal after multicarrier demodulation, compared to the first embodiment described above. Therefore, in the fifth embodiment, the received signal is a multicarrier modulation signal.

F-1. Configuration of Fifth Embodiment FIG. 6 is a block diagram showing a configuration of a spatial multiplexing signal detection circuit according to a fifth embodiment of the present invention. It should be noted that parts corresponding to those in FIG. The FFT circuits 518 and 518 perform multicarrier demodulation on the multicarrier modulation signal S520, which is a received signal, and supply it to the channel estimation circuit 101 and the matrix multiplier 105 as a subcarrier signal S501.

F-2. Operation of Fifth Embodiment Next, the operation of the fifth embodiment will be described. Multicarrier modulation signal S520 as a reception signal is input to FFT circuits 518 and 518, subjected to multicarrier demodulation, and output as subcarrier signal S501. The subcarrier signal S501 is input to the channel estimation circuit 101 and the matrix multiplication circuit 105. Other operations are the same as those in the first embodiment.

G. Sixth Embodiment Next, a sixth embodiment of the present invention will be described. The sixth embodiment is characterized in that the received signal S101 is a subcarrier signal after multicarrier demodulation, compared to the second embodiment described above. Therefore, in the sixth embodiment, the received signal is a multicarrier modulation signal.

G-1. Configuration of Sixth Embodiment FIG. 7 is a block diagram showing a configuration of a spatial multiplexing signal detection circuit according to a sixth embodiment of the present invention. The parts corresponding to those in FIG. The FFT circuits 518 and 518 perform multicarrier demodulation on the multicarrier modulation signal S520, which is a received signal, and supply it to the channel estimation circuit 101 and the matrix multiplier 105 as a subcarrier signal S501.

G-2. Operation of Sixth Embodiment Next, the operation of the sixth embodiment will be described. Multicarrier modulation signal S520 as a reception signal is input to FFT circuits 518 and 518, subjected to multicarrier demodulation, and output as subcarrier signal S501. The subcarrier signal S501 is input to the channel estimation circuit 101 and the matrix multiplication circuit 105. Other operations are the same as those in the second embodiment.

H. Seventh Embodiment Next, a seventh embodiment of the present invention will be described. The seventh embodiment is characterized in that the received signal S101 is a subcarrier signal after multicarrier demodulation, compared to the third embodiment described above. Therefore, in the seventh embodiment, the received signal is a multicarrier modulation signal.

H-1. Configuration of Seventh Embodiment FIG. 8 is a block diagram showing a configuration of a spatial multiplexing signal detection circuit according to a seventh embodiment of the present invention. Note that portions corresponding to those in FIG. 4 are denoted by the same reference numerals and description thereof is omitted. The FFT circuits 518 and 518 perform multicarrier demodulation on the multicarrier modulation signal S520, which is a received signal, and supply it to the channel estimation circuit 101 and the matrix multiplier 105 as a subcarrier signal S501.

H-2. Operation of Seventh Embodiment Next, the operation of the seventh embodiment will be described. Multicarrier modulation signal S520 as a reception signal is input to FFT circuits 518 and 518, subjected to multicarrier demodulation, and output as subcarrier signal S501. The subcarrier signal S501 is input to the channel estimation circuit 101 and the matrix multiplication circuit 105. Other operations are the same as those in the third embodiment.

I. Eighth Embodiment Next, an eighth embodiment of the present invention will be described. The eighth embodiment is characterized in that the received signal S101 is a subcarrier signal after multicarrier demodulation, compared to the fourth embodiment described above. Therefore, in the eighth embodiment, the received signal is a multicarrier modulation signal.

I-1. Configuration of Eighth Embodiment FIG. 9 is a block diagram showing a configuration of a spatial multiplexing signal detection circuit according to an eighth embodiment of the present invention. The parts corresponding to those in FIG. The FFT circuits 518 and 518 perform multicarrier demodulation on the multicarrier modulation signal S520, which is a received signal, and supply it to the channel estimation circuit 101 and the matrix multiplier 105 as a subcarrier signal S501.

I-2. Operation of Eighth Embodiment Next, the operation of the eighth embodiment will be described. Multicarrier modulation signal S520 as a reception signal is input to FFT circuits 518 and 518, subjected to multicarrier demodulation, and output as subcarrier signal S501. The subcarrier signal S501 is input to the channel estimation circuit 101 and the matrix multiplication circuit 105. Other operations are the same as those in the fourth embodiment.

  According to the first to eighth embodiments described above, when receiving a spatially multiplexed signal and performing signal detection, particularly when the number of modulation multilevels is increased, an increase in circuit scale is suppressed, and an excellent error is achieved. Rate characteristics can be realized.

  Further, according to the first to eighth embodiments described above, the calculation of QR decomposition is performed based on the channel estimation result, and the calculation is performed only at the head portion of the received packet. Therefore, it is not necessary to perform QR decomposition over the data portion, and power consumption can be reduced. In addition, in Equation (16), Equation (19), and the like, the product of the non-zero element of the upper triangular matrix R and the estimated transmission signal candidate is used as the interference signal. In this case, it is possible to store an interference signal as a multiplication result, and to refer to the stored value in a received packet over a plurality of symbols, and to greatly reduce the number of multiplications. It is.

  Furthermore, according to the first to eighth embodiments described above, it is possible to apply a signal detection method with excellent error rate characteristics even in a wireless LAN or the like in which the circuit scale or power consumption is severely limited. Also, in the past, the circuit scale and power consumption are small, but the signal detection method with excellent error rate characteristics can be applied even when a signal detection method with poor error rate characteristics has to be used. It becomes possible, and the effect that it becomes possible to provide a high-quality wireless system is also obtained.

  Furthermore, according to the above-described first to eighth embodiments, it is possible to use a feature with excellent error rate characteristics, which means that communication with a low CNR is possible while reducing the circuit scale. It can also contribute to the expansion of the area. Further, the memory circuit can be realized by a circuit that can be rewritten for each processing of each transmission system, for example, a circuit using a RAM or the like.

  In the first to eighth embodiments described above, it is specified that a signal is transmitted in a general expression with a multi-level signal (m). However, of course, an m-value QAM is included in this m-value signal. Signal, m-value PSK signal, m-value ASK, m-value FSK signal, m-value CCK (Complementary Code Keying) signal, SS (Spread Spectrum) signal multiplexed with m codes, etc. A general modulation scheme may be applied.

  Further, as described in the fifth to eighth embodiments, the multi-carrier demodulation is performed after the repetitive signal section called the guard interval is removed by the FFT circuit 518 (multi-carrier demodulating means). Thus, the subsequent processing is signal processing for each subcarrier. Therefore, it is possible to apply not only to the multicarrier modulation method but also to the case of using a single carrier modulation method.

  Further, the channel estimation circuit 101 may have a plurality of configurations depending on the signal format in which the channel estimation preamble signal for the spatially multiplexed signal on the transmission side is transmitted. A configuration corresponding to various situations such as a case where a synchronous detection is performed using a preamble signal provided in a receiver and a channel estimation result is obtained or an inverse matrix operation is performed may be adopted.

  Further, in the first to eighth embodiments described above, as shown in Equation (5), the expansion is possible even when the number of transmission systems is three or more, and the number of reception systems is also three or more. It can be extended in the case of Also, in a configuration of three or more multiplexes, it is not necessary to provide as many reception sequences as the number of transmission systems to be transmitted. Various combinations are possible accordingly.

  In addition, in the configuration according to the first to eighth embodiments described above, it is possible to reduce the power consumption by operating each unit and each circuit only when necessary, instead of always operating each unit and each circuit.

  In the first to eighth embodiments described above, each unit and each circuit are executed in a computer system. A series of processing steps by each unit and each circuit described above is stored in a computer-readable recording medium in the form of a program, and the above-described processing is performed by the computer reading and executing this program. That is, each unit and each circuit is realized by a central processing unit such as a CPU reading the above program into a main storage device such as a ROM or RAM and executing information processing / calculation processing. Also good.

  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.

It is a conceptual diagram for demonstrating the metric addition in this invention. It is a block diagram which shows the structure of the spatial multiplexing signal detection circuit by 1st Embodiment of this invention. It is a block diagram which shows the structure of the spatial multiplexing signal detection circuit by 2nd Embodiment of this invention. It is a block diagram which shows the structure of the spatial multiplexing signal detection circuit by 3rd Embodiment of this invention. It is a block diagram which shows the structure of the spatial multiplexing signal detection circuit by 4th Embodiment of this invention. It is a block diagram which shows the structure of the spatial multiplexing signal detection circuit by 5th Embodiment of this invention. It is a block diagram which shows the structure of the spatial multiplexing signal detection circuit by 6th Embodiment of this invention. It is a block diagram which shows the structure of the spatial multiplexing signal detection circuit by 7th Embodiment of this invention. It is a block diagram which shows the structure of the spatial multiplexing signal detection circuit by 8th Embodiment of this invention. It is a block diagram for demonstrating the conventional spatial multiplexing transmission. It is a conceptual diagram for demonstrating the conventional MLD system. It is a block diagram which shows the structure of the conventional spatial multiplexing signal detection circuit. It is a conceptual diagram which shows an example of the packet format used with a spatial multiplexing transmission system. It is a conceptual diagram at the time of showing in two dimensions in the frequency-time of an example packet format used with a spatial multiplexing transmission system.

Explanation of symbols

101 channel estimation circuit (channel estimation means)
102 Estimated channel matrix generation circuit (estimated channel matrix generation means)
103 QR decomposition circuit (QR decomposition means)
104 Complex conjugate transpose arithmetic circuit (complex conjugate transpose arithmetic means)
105 Matrix multiplication circuit (matrix multiplication means)
106 Multiplication result storage circuit (multiplication result storage means)
107 Transmission signal estimation circuit (transmission signal estimation means)
108 Transmission signal generation circuit (transmission signal generation means)
109 Transmission signal point distance calculation circuit (signal point distance calculation means)
110 Multiple transmission signal candidate narrowing circuit (Signal candidate narrowing means)
111 Transmission signal sequence storage circuit (signal sequence addition storage means)
112 Multiple transmission signal candidate metric calculation circuit (signal candidate metric calculation means)
113 Metric addition storage circuit (metric addition storage means)
114 Interference signal generation circuit (interference signal generation means)
115 Maximum likelihood estimation circuit (maximum likelihood estimation means)
216 Estimated channel matrix weighting circuit (weighting means)
217 Output signal switching circuit (sorting means)
316 Multiple transmission signal sequence metric calculation circuit (multiple signal sequence metric calculation means)
518 FFT circuit (multi-carrier demodulation means)

Claims (6)

A channel estimation means for receiving a plurality of received signals and estimating channel distortion of the propagation path between the transmitting and receiving antennas;
An estimated channel matrix generating means for generating an estimated channel matrix having the distortion of the channel estimated by the channel estimating means as a component;
QR decomposition means for performing unitary and triangulation (QR) decomposition operations on the estimated channel matrix generated by the estimated channel matrix generation means;
A complex conjugate transpose operation means for performing a Q ^H is the complex conjugate transpose operation with respect to the unitary matrix Q obtained by the QR decomposition unit,
Matrix multiplication means for performing a Q ^H × r matrix multiplication operation on a received column vector signal r having a plurality of received signals as constituent elements, using a calculation result obtained by the complex conjugate transposition calculating means;
Multiplication result storage means for storing calculation results of each transmission system of the matrix multiplication means;
Using the output signal of each transmission system obtained from the multiplication result storage means, the matrix element signal of the upper triangular matrix R which is another output signal of the QR decomposition means, and the interference signal which is a signal other than the desired transmission system A transmission signal estimation means for estimating a transmission signal of each desired transmission system;
Transmission signal generating means for generating a signal that may be transmitted from the transmitter;
Signal point distance calculation means for calculating a signal point distance between the estimated transmission signal estimated by the transmission signal estimation means and the transmission signal generated by the transmission signal generation means;
Among the signal point distances calculated by the signal point distance calculation means, a signal candidate narrowing means for selecting a plurality of estimated transmission signals of each transmission system as candidates in order from the smallest signal point distance,
Signal sequence addition storage means for storing a plurality of estimated transmission signals of each transmission system selected by the signal candidate narrowing means and information of each transmission system together as each estimated transmission signal sequence;
An upper triangle that is a plurality of estimated transmission signals of each transmission system selected by the signal candidate narrowing means, an output signal of each transmission system stored in the multiplication result storage means, and another output signal of the QR decomposition means Signal candidate metric calculation means for calculating each metric in a plurality of estimated transmission signals of each transmission system using a matrix element signal of the matrix R and an interference signal that is a signal other than a desired transmission system;
Metric addition storage means for adding and storing each metric calculated by the signal candidate metric calculation means according to a plurality of estimated transmission signals of each transmission system stored in the signal sequence storage means;
Other than the desired transmission system based on the estimated transmission signal of each transmission system stored in the signal sequence addition storage means and the matrix element signal of the upper triangular matrix R which is another output signal of the QR decomposition means Interference signal generating means for generating an interference signal that is a signal of
A signal indicating the smallest metric among the estimated transmission signal sequences stored in the signal sequence addition storage means and the already added metric signals corresponding to the estimated transmission signal sequence output from the metric addition storage means And a maximum likelihood estimating means for outputting the sequence as a finally estimated transmission signal sequence. The channel estimation means further generates a weighted information signal of an estimated channel matrix,
A weighting unit that performs weighting according to a transmission system of the estimated channel matrix generated by the estimated channel matrix generating unit using a weighting information signal separately output from the channel estimating unit;
The rearrangement means which rearranges the transmission signal series output from the maximum likelihood estimation means by using a weighted information signal separately output from the channel estimation means. Spatial multiplexed signal detection circuit. Multicarrier demodulation is performed on the plurality of received signals, and multicarrier demodulation is performed to output a subcarrier signal.
3. The spatial multiplexing signal detection circuit according to claim 1, wherein the subcarrier signal is used as an input signal to the channel estimation means and the matrix multiplication means. A channel estimation means for receiving a plurality of received signals and estimating channel distortion of the propagation path between the transmitting and receiving antennas;
An estimated channel matrix generating means for generating an estimated channel matrix having the distortion of the channel estimated by the channel estimating means as a component;
QR decomposition means for performing unitary and triangulation (QR) decomposition operations on the estimated channel matrix generated by the estimated channel matrix generation means;
A complex conjugate transpose operation means for performing a Q ^H is the complex conjugate transpose operation with respect to the unitary matrix Q obtained by the QR decomposition unit,
Matrix multiplication means for performing a Q ^H × r matrix multiplication operation on a received column vector signal r having a plurality of received signals as constituent elements, using a calculation result obtained by the complex conjugate transposition calculating means;
Multiplication result storage means for storing calculation results of each transmission system of the matrix multiplication means;
Using the output signal of each transmission system obtained from the multiplication result storage means, the matrix element signal of the upper triangular matrix R which is another output signal of the QR decomposition means, and the interference signal which is a signal other than the desired transmission system A transmission signal estimation means for estimating a transmission signal of each desired transmission system;
Transmission signal generating means for generating a signal that may be transmitted from the transmitter;
Signal point distance calculating means for calculating a signal point distance between the estimated transmission signal estimated by the transmission signal estimating means and the transmission signal generated by the transmission signal generating means;
Among the signal point distances calculated by the signal point distance calculation means, a signal candidate narrowing means for selecting a plurality of estimated transmission signals of each transmission system as candidates in order from the smallest signal point distance,
Signal sequence addition storage means for storing a plurality of estimated transmission signals of each transmission system selected by the signal candidate narrowing means and information of each transmission system together as each estimated transmission signal sequence;
An upper triangular matrix which is a plurality of estimated transmission signal sequences stored in the signal sequence addition storage means, an output signal of each transmission system stored in the multiplication result storage means, and another output signal of the QR decomposition means A plurality of signal sequence metric calculation means for calculating each metric in a plurality of estimated transmission signal sequences using an R matrix element signal and an interference signal other than a desired transmission system;
Other than the desired transmission system based on the estimated transmission signal of each transmission system stored in the signal sequence addition storage means and the matrix element signal of the upper triangular matrix R which is another output signal of the QR decomposition means Interference signal generating means for generating an interference signal that is a signal of
The smallest metric among the estimated transmission signal sequences stored in the signal sequence addition storage means and the already added metric signals corresponding to the estimated transmission signal sequences output from the multiple signal sequence metric calculation means. And a maximum likelihood estimator that outputs a signal sequence shown as a finally estimated transmission signal sequence. The channel estimation means further generates a weighted information signal of an estimated channel matrix,
A weighting unit that performs weighting according to a transmission system of the estimated channel matrix generated by the estimated channel matrix generating unit using a weighting information signal separately output from the channel estimating unit;
5. A rearrangement unit that rearranges a transmission signal sequence output from the maximum likelihood estimation unit using a weighted information signal separately output from the channel estimation unit. Spatial multiplexed signal detection circuit. Multicarrier demodulation is performed on the plurality of received signals, and multicarrier demodulation is performed to output a subcarrier signal.
6. The spatial multiplexing signal detection circuit according to claim 4, wherein the subcarrier signal is used as an input signal to the channel estimation means and the matrix multiplication means.

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