JP2014147029A - Mimo-ofdm reception device and program - Google Patents

Abstract

PROBLEM TO BE SOLVED: To improve reception characteristics by optimizing a parameter in the case of using a normalized UMP BP method, an offset UMP BP method or the like.SOLUTION: A multipath component power measurement section 21 of a parameter optimum value decision section 8-1 measures a D/U ratio of multipath component power as data on a state of a transmission path on the basis of a transmission path response, and a parameter decision section 23 extracts control information such as a carrier modulation system and an encoding rate from TMCC, and reads out a parameter β corresponding to the carrier modulation system, the encoding rate and the D/U ratio of the multipath component power from a DB 22 to decide an optimum value of the parameter β. The optimum value of the parameter β can be adaptively changed according to the D/U ratio of the multipath component power reflecting the state of the transmission path in the case of using the offset UMP BP method, which suppresses an effect of approximation to reduce degradation in a UMP BP method, as an LDPC decoding algorithm of an LDPC code decoding section 19.

Description

  The present invention relates to a MIMO (Multiple Input Multiple Output) -OFDM receiver and a program for receiving OFDM (Orthogonal Frequency Division Multiplexing) signals transmitted from a plurality of transmitting antennas by a plurality of receiving antennas, In particular, the present invention relates to a decoding process of an LDPC (Low Density Parity Check) code.

  ISDB-T (Integrated Services Digital Broadcasting-Terrestrial), a Japanese terrestrial digital broadcasting system, realizes high-definition (registered trademark) broadcasting (or multiple standard-definition broadcasting) for fixed reception. In the next-generation digital terrestrial broadcasting system, it is required to provide a service with a larger amount of information by 3D high-definition broadcasting or Super Hi-Vision having a resolution 16 times that of Hi-Vision instead of conventional Hi-Vision. Therefore, reducing the required C / N by increasing the data capacity and error correction technology has been an issue.

  In recent years, as a method for expanding the data transmission capacity by radio, a 2 × 2 polarization MIMO system that uses both horizontally polarized waves and vertically polarized waves simultaneously for the transmitting and receiving antennas has been proposed. The MIMO system can realize high-capacity transmission with high resistance against multipath by combining with the MIMO. In addition, LDPC codes are employed in many transmission systems as high-performance error correction codes that approach the Shannon limit.

  For example, a BP (Belief Propagation) algorithm is used as an LDPC code decoding process. The decoding process itself using the BP algorithm has extremely high decoding performance, but the calculation amount is enormous. For this reason, the UMP BP method (Uniformly Most Powerful BP method), the normalized UMP BP method, the offset UMP BP method, etc. which reduced the amount of calculation are proposed (refer nonpatent literature 1).

  The UMP BP method is a decoding algorithm that reduces the complexity by approximating a partial calculation of the BP algorithm with a minimum value. In addition, the normalized UMP BP method and the offset UMP BP method are decoding algorithms that correct the deviation of the log likelihood ratio and improve the accuracy of the likelihood by normalizing the calculation approximated by the UMP BP method. is there. In the calculation of these decoding algorithms, parameters having predetermined values are used (hereinafter, the parameter of the normalized UMP BP method is α, and the parameter of the offset UMP BP method is β).

[Conventional MIMO-OFDM Receiver]
FIG. 10 is a block diagram showing a configuration of a conventional MIMO-OFDM receiver. This MIMO-OFDM receiver 10 is a device that uses the normalized UMP BP method or the offset UMP BP method as an LDPC code decoding process. The MIMO-OFDM transmitter has two transmit antennas, and the number of receive antennas is two. The present invention is applied to the 2 × 2 polarization MIMO system using horizontal polarization and vertical polarization. In FIG. 10, the MIMO-OFDM receiver 10 includes an effective symbol period extraction and FFT (Fast Fourier Transform) units 11-1 and 11-2, and an SP (Scattered Pilot) extraction unit 12-1. 12-2, transmission line response calculation unit 13, MIMO equalization / polarization separation unit 14, symbol synthesis unit 15, likelihood calculation unit 16, TMCC (Transmission and Multiplexing Configuration Control) reading unit 17, parameter optimum value determination unit 18 and an LDPC code decoding unit 19. The effective symbol period extraction and FFT units 11-1 and 11-2, the SP extraction units 12-1 and 12-2, the transmission path response calculation unit 13, the MIMO equalization / polarization separation unit 14, and the symbol synthesis unit 15 -An OFDM demodulator is configured.

  The effective symbol period extraction and FFT unit 11-1 receives a horizontally polarized wave signal received via a receiving antenna Rx1 (not shown), detects the peak position of the guard correlation in one OFDM symbol period, and extracts the effective symbol period. To do. Then, the effective symbol period extraction and FFT unit 11-1 converts the time-axis waveform signal into the frequency-axis waveform signal by fast Fourier transform on the extracted horizontal polarization effective symbol period, and the horizontal polarization frequency. The shaft waveform signal is output to the SP extraction unit 12-1 and the TMCC reading unit 17. The effective symbol period extraction and FFT unit 11-2 receives a vertically polarized signal received via a reception antenna Rx2 (not shown), performs the same processing as the effective symbol period extraction and FFT unit 11-1, and performs vertical polarization. The frequency axis waveform signal of the wave is output to the SP extraction unit 12-2 and the TMCC reading unit 17.

  The SP extraction unit 12-1 receives the signal of the horizontal polarization frequency axis waveform from the effective symbol period extraction and FFT unit 11-1, and extracts the SP arranged at a predetermined carrier symbol position. The SP extraction unit 12-2 receives the signal of the vertical polarization frequency axis waveform from the effective symbol period extraction and FFT unit 11-2, performs the same processing as the SP extraction unit 12-1, and extracts the SP.

  The transmission path response calculation unit 13 calculates a transmission path response using the SP extracted by the SP extraction units 12-1 and 12-2 and a preset SP (SP for transmission). The MIMO equalization / polarization demultiplexing unit 14 performs the MIMO equalization process and the polarization demultiplexing process using the transmission path response calculated by the transmission path response calculation unit 13, and the symbol synthesis unit 15 performs the MIMO equalization / The symbol of the signal subjected to MIMO equalization and polarization separation by the polarization separation unit 14 is synthesized.

  That is, the effective symbol period extraction and FFT units 11-1 and 11-2, the SP extraction units 12-1 and 12-2, the transmission path response calculation unit 13, the MIMO equalization / polarization separation unit 14, and the symbol synthesis unit 15 Is demodulated into the original signal in the MIMO-OFDM transmission apparatus.

  The likelihood calculating unit 16 calculates, for each bit, the likelihood of the signal synthesized by the symbol synthesizing unit 15, that is, the likelihood of the original signal demodulated by the MIMO-OFDM demodulating unit.

  The TMCC reading unit 17 inputs the signal of the frequency axis waveform of the horizontal polarization from the effective symbol period extraction and FFT unit 11-1, and also outputs the frequency axis waveform of the vertical polarization from the effective symbol period extraction and FFT unit 11-2. A signal is input, TMCC stored at a predetermined carrier symbol position and storing control information such as coding rate and carrier modulation scheme is read, and the read TMCC is output to parameter optimum value determining section 18. Control information such as a coding rate and a carrier modulation scheme is stored in a TMCC arranged at a predetermined carrier symbol position in the MIMO-OFDM transmission apparatus.

  The parameter optimum value determination unit 18 receives TMCC from the TMCC reading unit 17, extracts control information such as a carrier modulation scheme and a coding rate from the TMCC, and determines an optimum parameter value based on the extracted control information. For example, the parameter optimum value determination unit 18 holds a table in which parameters and coding rates corresponding to each carrier modulation method are stored in advance, and sets the carrier modulation method and coding rate extracted from the TMCC. The corresponding parameter is read from the table, and the read parameter is determined as the optimum value.

  The LDPC code decoding unit 19 receives the likelihood from the likelihood calculating unit 16 and the parameter from the parameter optimum value determining unit 18, and uses the normalized UMP BP method as an LDPC code decoding process for the input likelihood. Alternatively, the offset UMP BP method is performed using the input parameters, restored to the original transmission data, and output.

[LDPC code decoding unit]
Next, the decoding process of the UMP BP method will be described. As described above, the UMP BP method is a decoding algorithm that reduces the complexity by approximating a partial calculation of the BP algorithm with a minimum value. In this BP algorithm, the initial likelihood of each bit is calculated from the power of the received signal, etc., and the original transmission data is restored by repeatedly calculating the likelihood using a predetermined check matrix consisting of 0 and 1 data. To do. In the iterative calculation process using this check matrix, bit nodes and check nodes are linked and connected based on the check matrix, and the likelihood calculation at the bit nodes and the likelihood calculation at the check nodes are alternately repeated. Do. The bit node corresponds to a column (n described later) of the check matrix, and the check node corresponds to a row (m described later) of the check matrix.

ここで、ｎはビットノードの番号、ｙ_ｎは受信信号、σ^２は雑音の分散を示す。 (BP algorithm)
Decoding processing by the BP algorithm will be described. For example, when BPSK (Binary Phase Shift Keying) is used as the modulation method, first, an initial LLR (Log Likelihood Ratio) F _n is calculated by the following equation. This calculation is performed for each bit by the likelihood calculation unit 16.

Here, n is the bit node number, the y _n received signals, sigma ² denotes the variance of the noise.

ここで、ｉは繰り返し回数を示し、ｍ，ｎは、検査行列における行の数及び列の数を示す。すなわち、ｍはチェックノードの番号、ｎはビットノードの番号を示す。Ｍ（ｎ）＼ｍは、ｎ番目のビットノードに接続される全てのチェックノードを示す（但し、ｍ番目のチェックノードは除かれる）。 Then, for each bit node (node corresponding to n), the likelihood L ⁽ⁱ⁾ _mn is collected from the connected check nodes and subjected to column processing, and the likelihood z ⁽ⁱ⁾ _mn is _calculated by the following equation: Calculated.

Here, i indicates the number of repetitions, and m and n indicate the number of rows and the number of columns in the parity check matrix. That is, m indicates the check node number, and n indicates the bit node number. M (n) \ m indicates all check nodes connected to the nth bit node (however, the mth check node is excluded).

ここで、Ｎ（ｍ）＼ｎは、ｍ番目のチェックノードに接続される全てのビットノードを示す（但し、ｎ番目のビットノードは除かれる）。 For each check node (node corresponding to m), likelihood z ⁽ⁱ⁾ _mn is collected from the connected bit nodes and row processing is performed, and likelihood L ⁽ⁱ⁾ _mn is _calculated by the following equation: Calculated.

Here, N (m) \ n indicates all bit nodes connected to the mth check node (however, the nth bit node is excluded).

By repeating a predetermined number of times i calculated by the formula (2) (3), as shown in the following equation, the likelihood z ⁽ⁱ⁾ _n is calculated, the data of the codes of the likelihood z ⁽ⁱ⁾ _n 0, 1 is decoded.

  However, in the decoding process by this BP algorithm, the amount of calculation of the equation (3) becomes enormous. Therefore, in order to reduce the amount of calculation, the UMP BP method that approximates a part of the equation (3) with a minimum value is used.

(UMP BP method)
In the UMP BP method, L ⁽ⁱ⁾ _mn is obtained using the following equation instead of the equation (3). This equation uses only the minimum likelihood z ⁽ⁱ⁾ _mn in the equation (3).

  On the other hand, in the UMP BP method using the equation (6), the influence of approximation is large and the deterioration becomes large. Therefore, the normalized UMP BP method or the offset UMP BP method is used.

ここで、Ｌ_UMPは、前記式（６）により算出された尤度Ｌ⁽ⁱ⁾ _mn、Ｅ｜Ｌ_BP｜は、ＢＰアルゴリズムの計算における平均尤度、Ｅ｜Ｌ_UMP｜は、ＵＭＰ ＢＰ法の計算における平均尤度を示す。パラメータαは、図１０に示したパラメータ最適値決定部１８により決定される。 (Normalized UMP BP method)
In the normalized UMP BP method, the likelihood L _NormUMP is obtained using the following equation.

Here, L _UMP is the likelihood L ⁽ⁱ⁾ _mn , E | L _BP | calculated by the equation (6) is the average likelihood in the calculation of the BP algorithm, and E | L _UMP | is the UMP BP method. The average likelihood in the calculation of The parameter α is determined by the parameter optimum value determination unit 18 shown in FIG.

ここで、Ｌ_UMPは、前記式（６）により算出された尤度Ｌ⁽ⁱ⁾ _mnを示す。パラメータβは、図１０に示したパラメータ最適値決定部１８により決定される。 (Offset UMP BP method)
In the offset UMP BP method, the likelihood L _offUMP is obtained using the following equation.

Here, L _UMP represents the likelihood L ⁽ⁱ⁾ _mn calculated by the equation (6). The parameter β is determined by the parameter optimum value determination unit 18 shown in FIG.

  In this way, by using the normalized UMP BP method and the offset UMP BP method, it is possible to correct the likelihood deviation in the UMP BP method, and to improve the accuracy of the likelihood. Since the decoding process of the BP algorithm, the UMP BP method, the normalized UMP BP method and the offset UMP BP method, and the optimization process of the parameters α and β are known, detailed description thereof is omitted here. For details, refer to Non-Patent Document 1, for example.

Ohashi and Ohtsuki, "Characteristic analysis of normalized BP-based algorithm and offset BP-based algorithm in high-speed fading channel", IEICE Technical Report, RCS2003-212 (2003)

  In the conventional MIMO-OFDM receiver 10 shown in FIG. 10, since the LDPC code decoding unit 19 performs the decoding process of the above-mentioned normalized UMP BP method or offset UMP BP method, the parameter optimum value determination unit 18 Based on the control information stored in the above, the optimum value of the parameter α in the equation (7) or the parameter β in the equation (8) is determined. Thus, the parameters α and β are the carrier modulation scheme and coding rate used in the MIMO-OFDM transmitter regardless of the state of the transmission path between the MIMO-OFDM transmitter and the MIMO-OFDM receiver 10. It was a constant value optimized from

  However, the transmission path for wireless transmission assuming terrestrial broadcasting has a deterioration factor of the received signal due to not only white noise but also multipath, etc., and polarization rotation occurs in the transmission path for polarization MIMO transmission. However, this becomes a deterioration factor. As a result, these deterioration factors affect the accuracy of data restored by the decoding process of the normalized UMP BP method or the offset UMP BP method. Therefore, in order to improve the accuracy of the decoding process and improve the reception characteristics, the optimum values of the parameters α and β that determine the contents of the decoding process of the normalized UMP BP method and the offset UMP BP method are set to the state of the transmission path. It is necessary to change according to.

  FIG. 11 is a diagram illustrating an optimum value of the parameter β in the offset UMP BP method. The vertical axis represents BER (Bit Error Rate), the horizontal axis represents parameter β, the square mark broken line is a characteristic assuming an AWGN (Additive White Gaussian Noise) environment, and the triangular mark broken line Indicates characteristics assuming a one-wave multipath environment. Further, these are characteristics obtained by computer simulation with a delay amount = 0.37 us and a horizontal / vertical polarization phase difference of 180 °. The value that minimizes the bit error rate when C / N is constant and the parameter β is changed is the optimum value. FIG. 11 shows that the optimum value of the parameter β in the offset UMP BP method differs depending on the transmission path. This difference is due to the difference in likelihood distribution depending on the state of the transmission path. Although FIG. 11 shows the optimum value of the parameter β in the offset UMP BP method, the optimum value of the parameter α in the normalized UMP BP method also differs depending on the transmission path.

  Thus, the optimum values of the parameters α and β when the normalized UMP BP method and the offset UMP BP method are used as the LDPC decoding algorithm vary depending on the state of the transmission path. Therefore, it is desirable that the reception side improve the reception characteristics by optimizing the parameters α and β according to the state of the transmission path, not by setting the parameters α and β to constant values regardless of the state of the transmission path.

  Therefore, the present invention has been made to solve the above-mentioned problems, and its purpose is to optimize parameters according to the state of the transmission path when performing LDPC code decoding processing using parameters. Another object of the present invention is to provide a MIMO-OFDM receiver and program capable of improving reception characteristics.

  To achieve the above object, the MIMO-OFDM receiver according to claim 1 receives the OFDM signal transmitted from a plurality of transmitting antennas in the MIMO-OFDM receiving apparatus that receives the signals through the plurality of receiving antennas. A MIMO-OFDM demodulator that demodulates an OFDM signal and performs MIMO equalization to generate an original signal, and calculates transmission path responses between the plurality of transmitting antennas and the plurality of receiving antennas, and the MIMO A likelihood calculating unit that calculates the likelihood of the original signal generated by the OFDM demodulating unit, a parameter optimal value determining unit that determines an optimal value of a parameter used for decoding processing of the LDPC code, and the likelihood calculating unit With respect to the calculated likelihood, an LDPC code decoding process is performed using the optimal parameter value determined by the optimal parameter value determination unit. An LDPC code decoding unit, wherein the parameter optimum value determination unit obtains data reflecting the state of the transmission path based on the transmission path response calculated by the MIMO-OFDM demodulation unit, and includes at least the parameter and A parameter corresponding to the obtained data is determined as an optimum value using a table in which data reflecting the state of the transmission path is stored in advance.

  The MIMO-OFDM receiver according to claim 2 is the MIMO-OFDM receiver according to claim 1, wherein the parameter optimum value determining unit is based on a transmission path response calculated by the MIMO-OFDM demodulator. As the data reflecting the state of the transmission path, there is a table corresponding to a multipath component power measurement unit that measures a D / U ratio of multipath component power and at least a parameter and a D / U ratio of multipath component power. A DB that is stored in advance and a parameter determination unit that determines a parameter corresponding to the D / U ratio of the multipath component power measured by the multipath component power measurement unit as an optimum value. .

  The MIMO-OFDM receiver according to claim 3 is the MIMO-OFDM receiver according to claim 1, wherein the parameter optimum value determination unit is based on a transmission path response calculated by the MIMO-OFDM demodulation unit. As the data reflecting the state of the transmission path, a condition number calculation unit for calculating the condition number of the transmission line response matrix and a table corresponding to at least the parameters and the condition number of the transmission line response matrix are stored in advance. And a parameter determination unit that determines a parameter corresponding to the condition number of the transmission path response matrix calculated by the condition number calculation unit as an optimum value.

  A MIMO-OFDM receiver according to claim 4 is the MIMO-OFDM receiver according to claim 2 or 3, wherein the LDPC code decoding process by the LDPC code decoding unit is a decoding process by a normalized UMP BP method. The DB parameter of claim 2 stores a value of a relationship that increases as the D / U ratio of the multipath component power increases and decreases as the D / U ratio of the multipath component power decreases. The DB parameter of claim 3 stores a relational value that decreases as the condition number of the transmission path response matrix increases and increases as the condition number of the transmission path response matrix decreases. And

  The MIMO-OFDM receiver according to claim 5 is the MIMO-OFDM receiver according to claim 2 or 3, wherein the LDPC code decoding process by the LDPC code decoding unit is a decoding process by an offset UMP BP method. The DB parameter of claim 2 stores a relational value that decreases as the D / U ratio of the multipath component power increases and increases as the D / U ratio of the multipath component power decreases. As a DB parameter of Item 3, a value of a relation that increases as the condition number of the transmission line response matrix increases and decreases as the condition number of the transmission line response matrix decreases is stored. To do.

  Furthermore, the program of claim 6 receives OFDM signals transmitted from a plurality of transmitting antennas via a plurality of receiving antennas, demodulates the received OFDM signals, performs MIMO equalization, and converts the original signals to And a MIMO-OFDM demodulator that calculates transmission path responses between the plurality of transmit antennas and the plurality of receive antennas, and a likelihood of the original signal generated by the MIMO-OFDM demodulator A parameter optimal value determining unit that determines an optimal value of a parameter used for decoding processing of an LDPC code, and a likelihood calculated by the likelihood calculating unit by the parameter optimal value determining unit. And an LDPC code decoding unit that performs an LDPC code decoding process using the optimum parameter values The computer obtains data reflecting the state of the transmission line based on the transmission line response calculated by the MIMO-OFDM demodulation unit, and at least the data reflecting the parameter and the state of the transmission line correspond to each other. A step of determining a parameter corresponding to the obtained data as an optimum value using a table stored in advance.

  As described above, according to the present invention, when an LDPC code decoding process is performed using a parameter, the optimum value of the parameter is determined according to the state of the transmission path. In particular, in terrestrial transmission in which the state of the transmission path changes depending on the reception point, the reception characteristics can be improved compared to the conventional technique in which the parameter is a constant value regardless of the transmission path.

It is a block diagram which shows the structure of the MIMO-OFDM receiving apparatus by embodiment of this invention. It is a block diagram which shows the 1st structure of a parameter optimal value determination part. It is a flowchart which shows the process by the 1st structure of a parameter optimal value determination part. It is a figure which shows the structural example of DB stored corresponding to parameter (beta), a carrier modulation system, a coding rate, and D / U ratio of multipath component electric power. (1) is a diagram showing a relationship between a parameter α and a D / U ratio of multipath component power in the normalized UMP BP method. (2) is a diagram showing a relationship between the parameter β and the D / U ratio of the multipath component power in the offset UMP BP method. It is a block diagram which shows the 2nd structure of a parameter optimal value determination part. It is a flowchart which shows the process by the 2nd structure of a parameter optimal value determination part. It is a figure which shows the structural example of DB in which parameter (beta), the carrier modulation system, the coding rate, and the condition number of the matrix of a transmission line response were stored correspondingly. (1) is a figure which shows the relationship between the parameter (alpha) in the normalization UMP BP method and the condition number of the matrix of a transmission line response. (2) is a diagram showing the relationship between the parameter β and the condition number of the channel response matrix in the offset UMP BP method. It is a block diagram which shows the structure of the conventional MIMO-OFDM receiver. It is a figure which shows the optimal value of parameter (beta) in the offset UMP BP method.

Hereinafter, embodiments for carrying out the present invention will be described in detail with reference to the drawings.
FIG. 1 is a block diagram showing a configuration of a MIMO-OFDM receiver according to an embodiment of the present invention. This MIMO-OFDM receiver 1 is a device that uses a normalized UMP BP method or an offset UMP BP method as an LDPC code decoding process, as in the MIMO-OFDM receiver 10 shown in FIG. The present invention is applied to a 2 × 2 polarization MIMO system using horizontal polarization and vertical polarization with two transmission antennas and two reception antennas. In FIG. 1, a MIMO-OFDM receiver 1 includes effective symbol period extraction and FFT units 11-1 and 11-2, SP extraction units 12-1 and 12-2, a transmission line response calculation unit 3, a MIMO equalization / bias. A wave separation unit 14, a symbol synthesis unit 15, a likelihood calculation unit 16, a TMCC reading unit 17, a parameter optimum value determination unit 8, and an LDPC code decoding unit 19 are provided. The effective symbol period extraction and FFT units 11-1 and 11-2, the SP extraction units 12-1 and 12-2, the transmission path response calculation unit 3, the MIMO equalization / polarization separation unit 14, and the symbol synthesis unit 15 -An OFDM demodulator is configured.

  Comparing the conventional MIMO-OFDM receiver 10 shown in FIG. 10 with the MIMO-OFDM receiver 1 shown in FIG. 1, both MIMO-OFDM receivers 1 and 10 are effective symbol period extraction and FFT unit 11-1. 11-2, SP extraction units 12-1, 12-2, MIMO equalization / polarization demultiplexing unit 14, symbol synthesis unit 15, likelihood calculation unit 16, TMCC reading unit 17, and LDPC code decoding unit 19. However, the MIMO-OFDM receiver 1 is different from the channel response calculator 13 and the parameter optimum value determiner 18 included in the MIMO-OFDM receiver 10 in that the channel response calculator 3 and the parameter optimum The difference is that a value determining unit 8 is provided. Further, the conventional MIMO-OFDM receiver 10 shown in FIG. 10 optimizes parameters based on control information extracted from TMCC, whereas the MIMO-OFDM receiver 1 shown in FIG. 1 extracts from TMCC. In addition to the control information, the parameter is optimized based on the state of the transmission path obtained from the transmission path response.

  Effective symbol period extraction and FFT units 11-1 and 11-2, SP extraction units 12-1 and 12-2, MIMO equalization / polarization separation unit 14, symbol synthesis unit 15, likelihood calculation unit 16, and TMCC reading unit 17 and the LDPC code decoding unit 19 have already been described with reference to FIG.

  Similarly to the transmission path response calculation section 13, the transmission path response calculation section 3 uses the SP extracted by the SP extraction sections 12-1 and 12-2 and a preset SP (SP for transmission). Calculate the response. Then, the transmission line response calculation unit 3 outputs the calculated transmission line response to the MIMO equalization / polarization separation unit 14 and the parameter optimum value determination unit 8.

  That is, the effective symbol period extraction and FFT units 11-1 and 11-2, the SP extraction units 12-1 and 12-2, the transmission path response calculation unit 3, the MIMO equalization / polarization separation unit 14, and the symbol synthesis unit 15 The MIMO-OFDM demodulator configured as described above is demodulated into an original signal in the MIMO-OFDM transmitter, and the likelihood of the original signal demodulated by the MIMO-OFDM demodulator by the likelihood calculator 16 is determined for each bit. Calculated.

  The parameter optimum value determination unit 8 holds a conversion table (DB (database)) in which parameters, carrier modulation scheme and coding rate control information, and data on the state of the transmission path are stored correspondingly. The parameter optimum value determination unit 8 receives the transmission line response from the transmission line response calculation unit 3 and the TMCC from the TMCC reading unit 17, obtains data on the state of the transmission line from the transmission line response, and performs carrier modulation from the TMCC. Control information such as the system and coding rate is extracted, data relating to the state of the transmission path and parameters corresponding to the control information are read from the conversion table, and the read parameters are determined as optimum values.

[Parameter optimum value determination unit / first configuration]
Next, the parameter optimum value determination unit 8 will be described in detail. FIG. 2 is a block diagram showing a first configuration of the parameter optimum value determining unit 8 shown in FIG. 1, and FIG. 3 is a flowchart showing processing by the first configuration of the parameter optimum value determining unit 8. The parameter optimum value determination unit 8-1 performs conversion processing on the multipath component reflecting the state of the transmission path and determines a parameter. The parameter optimum value determination unit 8-1 determines the parameter. The unit 23 is provided.

  When the parameter optimum value determination unit 8-1 receives the transmission line response from the transmission line response calculation unit 3 and the TMCC from the TMCC reading unit 17 (step S301), the multipath component power measurement unit 21 receives the input transmission line. Based on the response, the D / U ratio of the multipath component power that is the power of the delayed wave reflecting the state of the transmission path is measured (step S302). Specifically, the multipath component power measurement unit 21 obtains a delay profile by performing IFFT (Inverse Fast Fourier Transform) on the transmission line response, extracts the multipath component from the delay profile, and multipath component Measure power D / U ratio. In this case, the multipath component power measurement unit 21 extracts a plurality of multipath components from the delay profile, specifies a multipath component having the maximum power among the plurality of multipath components, and determines the multipath component having the specified maximum power. For the path component, the D / U ratio of the power may be measured. Further, the multipath component power measurement unit 21 may measure a D / U ratio obtained by adding these powers for a plurality of extracted multipath components. In this case, the D / U ratio of the multipath component power increases as the state of the transmission path improves, but the D / U ratio of the multipath component power decreases as the state of the transmission path deteriorates.

  In the DB 22, parameters, carrier modulation scheme and coding rate control information, and data on the state of the transmission path are stored in advance corresponding to each other. The parameters stored in the DB 22 are optimum values set in advance so as to improve the reception characteristics corresponding to the carrier modulation scheme and coding rate control information and the data regarding the state of the transmission path.

  FIG. 4 is a diagram illustrating a configuration example of the DB 22, and illustrates a configuration example in a case where the LDPC code decoding unit 19 performs a decoding process using the offset UMP BP method. The DB 22 stores the parameter β, the carrier modulation scheme, the coding rate, and the D / U ratio of the multipath component power reflecting the transmission path state. In addition, when the decoding process of the normalized UMP BP method is performed in the LDPC code decoding unit 19, the multipath in which the parameter α, the carrier modulation scheme, the coding rate, and the state of the transmission path are reflected in the DB 22 The D / U ratio of component power is stored correspondingly.

  FIG. 5A is a diagram illustrating a relationship between the parameter α used when the LDPC code decoding unit 19 performs the decoding process of the normalized UMP BP method and the D / U ratio of the multipath component power. . FIG. 5B is a diagram illustrating a relationship between the parameter β used when the LDPC code decoding unit 19 performs the decoding process of the offset UMP BP method and the D / U ratio of the multipath component power.

  As shown in FIG. 5 (1), the parameter α becomes a small value when the D / U ratio of the multipath component power becomes small, becomes a large value when the D / U ratio of the multipath component power becomes large, and the D / U ratio. The parameter α gradually decreases with the decrease in the parameter α, and the parameter α rapidly increases with the increase in the D / U ratio. The DB 22 stores the parameter α having such a relationship corresponding to the carrier modulation scheme, the coding rate, and the D / U ratio of the multipath component power. Further, as shown in FIG. 5 (2), the parameter β becomes a large value when the D / U ratio of the multipath component power becomes small, and becomes a small value when the D / U ratio of the multipath component power becomes large. The parameter β increases rapidly as the U ratio decreases, and the parameter β gradually decreases as the D / U ratio increases. In the DB 22, the parameter β having such a relationship is stored corresponding to the carrier modulation scheme, the coding rate, and the D / U ratio of the multipath component power.

  2 and 3, the parameter determination unit 23 extracts control information such as a carrier modulation scheme and a coding rate from the TMCC (step S303), and extracts the extracted carrier modulation scheme and coding rate, and multipath components. The parameter β corresponding to the D / U ratio of the multipath component power measured by the power measurement unit 21 is read from the DB 22 shown in FIG. 4 (step S304). Then, the parameter determination unit 23 determines the read parameter β as an optimal value (step S305), and outputs the optimal value of the parameter β to the LDPC code decoding unit 19 that performs the decoding process of the offset UMP BP method (step S306). ).

  When the LDPC code decoding unit 19 performs the decoding process of the normalized UMP BP method, the parameter determination unit 23 sets the parameter α corresponding to the carrier modulation scheme, the coding rate, and the D / U ratio of the multipath component power. Are read out from the DB 22, the read parameter α is determined as an optimal value, and the optimal value of the parameter α is output to the LDPC code decoding unit 19 that performs decoding processing of the normalized UMP BP method.

  As described above, according to the MIMO-OFDM receiver 1 according to the embodiment of the present invention, the multipath component power measurement unit 21 of the parameter optimum value determination unit 8-1 has the transmission path input from the transmission path response calculation unit 3. Based on the response, the D / U ratio of the multipath component power is measured as data regarding the state of the transmission path, and the parameter determination unit 23 controls the carrier modulation scheme, the coding rate, etc. from the TMCC input from the TMCC reading unit 17. Information is extracted, and the parameter β corresponding to the carrier modulation scheme, coding rate, and D / U ratio of the multipath component power is read from the DB 22, and the optimum value of the parameter β is determined. As a result, the state of the transmission path reflects the optimum value of the parameter β when the offset UMP BP method, in which the influence of approximation of the UMP BP method is suppressed and the deterioration is reduced, as the LDPC decoding algorithm in the LDPC code decoding unit 19 is reflected. Can be adaptively changed according to the D / U ratio of the generated multipath component power. Therefore, the reception characteristics can be improved according to the state of the transmission path.

  Even when the normalized UMP BP method is used as the LDPC decoding algorithm in the LDPC code decoding unit 19, the optimum value of the parameter α is adaptively determined by the D / U ratio of the multipath component power reflecting the state of the transmission path. The reception characteristics can be improved in accordance with the state of the transmission path.

[Parameter optimum value determination unit / second configuration]
Next, the second configuration of the parameter optimum value determination unit 8 will be described in detail. FIG. 6 is a block diagram showing a second configuration of the parameter optimum value determining unit 8 shown in FIG. 1, and FIG. 7 is a flowchart showing processing by the second configuration of the parameter optimum value determining unit 8. This parameter optimum value determination unit 8-2 performs a conversion process on the condition number (condition number) of the matrix of the transmission line response reflecting the state of the transmission line, determines a parameter, and calculates the condition number. Unit 24, DB 25, and parameter determination unit 26.

  When the parameter optimum value determination unit 8-2 inputs the transmission line response from the transmission line response calculation unit 3 and inputs the TMCC from the TMCC reading unit 17 (step S701), the condition number calculation unit 24 adds the transmission line response to the input transmission line response. Based on this, the condition number of the transmission line response matrix reflecting the state of the transmission line is calculated (step S702). Here, the condition number of the channel response matrix indicates the ratio of the eigenvalues of the channel response matrix.

  Specifically, the condition number calculation unit 24 calculates an eigenvalue from the transmission path response matrix, and calculates the condition number from the eigenvalue. For example, when the channel response matrix is a 2 × 2 matrix and the eigenvalues are λ1 and λ2, the condition number is a value obtained by dividing λ2 by λ1 (ratio of λ2 to λ1, λ2 / λ1). However, λ1 ≦ λ2 (λ2 / λ1 ≧ 1). The transmission line response matrix is ideally a unit matrix. The better the transmission line state is, the smaller the condition number approaches 1, but due to leakage between the receiving antennas Rx1 and Rx2, crosstalk, etc. The condition number increases as the state of the transmission line gets worse.

  Similarly to the DB 22 shown in FIG. 2, the DB 25 stores parameters, carrier modulation scheme and coding rate control information, and data related to the state of the transmission path in advance. The parameters stored in the DB 25 are optimum values set in advance so as to improve the reception characteristics corresponding to the carrier modulation scheme, the coding rate control information, and the data related to the state of the transmission path.

  FIG. 8 is a diagram illustrating a configuration example of the DB 25, and illustrates a configuration example in a case where the LDPC code decoding unit 19 performs a decoding process using the offset UMP BP method. The DB 25 stores the parameter β, the carrier modulation scheme, the coding rate, and the condition number of a transmission line response matrix indicating the state of the transmission line. In addition, when the decoding process of the normalized UMP BP method is performed in the LDPC code decoding unit 19, the DB 25 stores the parameter α, the carrier modulation scheme, the coding rate, and the transmission path response indicating the transmission path status. The condition number of the matrix is stored correspondingly.

  FIG. 9A is a diagram illustrating a relationship between the parameter α used when the LDPC code decoding unit 19 performs the decoding process of the normalized UMP BP method and the condition number of the channel response matrix. FIG. 9B is a diagram illustrating a relationship between the parameter β used when the LDPC code decoding unit 19 performs the decoding process of the offset UMP BP method and the condition number of the channel response matrix.

  As shown in FIG. 9A, the parameter α becomes a large value when the condition number becomes small, and becomes a small value when the condition number becomes large. As the condition number decreases, the parameter α rapidly increases, and the condition number As the value increases, the parameter α is gradually reduced. In the DB 25, the parameter α having such a relationship is stored corresponding to the carrier modulation scheme, the coding rate, and the condition number. Further, as shown in FIG. 9 (2), the parameter β becomes a small value when the condition number becomes small, becomes a large value when the condition number becomes large, and the parameter β gradually decreases as the condition number decreases. As the number increases, the parameter β increases rapidly. In the DB 25, the parameter β having such a relationship is stored corresponding to the carrier modulation scheme, the coding rate, and the condition number.

  Returning to FIGS. 6 and 7, the parameter determination unit 26 extracts control information such as a carrier modulation scheme and a coding rate from the TMCC (step S703), and calculates the extracted carrier modulation scheme and coding rate, and the condition number. The parameter β corresponding to the condition number of the transmission line response matrix calculated by the unit 24 is read from the DB 25 shown in FIG. 8 (step S704). Then, the parameter determination unit 26 determines the read parameter β as an optimal value (step S705), and outputs the optimal value of the parameter β to the LDPC code decoding unit 19 that performs the decoding process of the offset UMP BP method (step S706). ).

  When the LDPC code decoding unit 19 performs the decoding process of the normalized UMP BP method, the parameter determination unit 26 sets the parameter α corresponding to the condition number of the carrier modulation scheme, the coding rate, and the channel response matrix. The parameter α read out from the DB 25 is determined as an optimum value, and the optimum value of the parameter α is output to the LDPC code decoding unit 19 that performs the decoding process of the normalized UMP BP method.

  As described above, according to the MIMO-OFDM receiving apparatus 1 according to the embodiment of the present invention, the condition number calculation unit 24 of the parameter optimum value determination unit 8-2 determines the transmission path response input from the transmission path response calculation unit 3. Based on this, the condition number of the transmission path response matrix is calculated as data relating to the transmission path state, and the parameter determination unit 26 extracts control information such as a carrier modulation scheme and a coding rate from the TMCC input from the TMCC reading unit 17. Then, the parameter β corresponding to the condition number of the matrix of the carrier modulation scheme, the coding rate, and the transmission path response is read from the DB 25 and the optimum value of the parameter β is determined. As a result, the state of the transmission path reflects the optimum value of the parameter β when the offset UMP BP method, in which the influence of approximation of the UMP BP method is suppressed and the deterioration is reduced, as the LDPC decoding algorithm in the LDPC code decoding unit 19 is reflected. It can be adaptively changed according to the condition number of the determined channel response matrix. Therefore, the reception characteristics can be improved according to the state of the transmission path.

  Even when the normalized UMP BP method is used as the LDPC decoding algorithm in the LDPC code decoding unit 19, the optimum value of the parameter α is adaptively set according to the condition number of the matrix of the transmission line response reflecting the state of the transmission line. The reception characteristic can be improved according to the state of the transmission path.

  The present invention has been described with reference to the embodiment. However, the present invention is not limited to the above-described embodiment, and various modifications can be made without departing from the technical idea thereof. The present invention is not limited to the number of antennas, the type of polarization, and the like, and the parameter optimum value determination unit 8-1 shown in FIG. 2 is also applicable to the spatial MIMO scheme. In addition, the present invention is applicable to the normalized UMP BP method and the offset UMP BP method that use parameters in the UMP BP method as in the above-described embodiment, and further to a method that uses parameters in decoding methods other than the UMP BP method. Is also applicable. That is, the present invention is applicable to an LDPC code decoding technique in which decoding processing is performed using a parameter whose optimum value changes depending on the state of the transmission path.

  Moreover, in the said embodiment, although the parameter determination part 23 of the parameter optimal value determination part 8-1 determined the optimal value of parameter (beta) using DB22, instead of DB22, parameter (beta), a carrier modulation system The optimum value of the parameter β may be determined using a calculation formula in which the relationship between the coding rate and the D / U ratio of the multipath component power is defined. Similarly, the parameter determination unit 26 of the parameter optimal value determination unit 8-2 uses a calculation formula in which the parameter β, the carrier modulation scheme, the coding rate, and the condition number of the channel response matrix are defined instead of the DB 25. It may be used to determine the optimum value of the parameter β. The same applies to the parameter α.

  In the embodiment, the multipath component power measurement unit 21 of the parameter optimum value determination unit 8-1 measures the D / U ratio of the multipath component power reflecting the state of the transmission path, and determines the parameter optimum value. Although the condition number calculation unit 24 of the unit 8-2 calculates the condition number of the matrix of the transmission line response reflecting the state of the transmission line, the present invention determines the optimum values of the parameters α and β. The data required for this is not limited to these data, and any data reflecting the state of the transmission path may be used.

  Note that a normal computer can be used as the hardware configuration of the MIMO-OFDM receiver 1 according to the embodiment of the present invention. The MIMO-OFDM receiver 1 is configured by a computer including a volatile storage medium such as a CPU and a RAM, a non-volatile storage medium such as a ROM, an interface, and the like. The functions of the multipath component power measurement unit 21 and the parameter determination unit 23 included in the parameter optimum value determination unit 8-1 of the MIMO-OFDM receiver 1 are respectively executed by causing the CPU to execute a program describing these functions. Realized. Each function of the condition number calculation unit 24 and the parameter determination unit 26 included in the parameter optimum value determination unit 8-2 of the MIMO-OFDM receiver 1 is caused by causing the CPU to execute a program describing these functions. Realized. These programs can be stored and distributed on a storage medium such as a magnetic disk (floppy (registered trademark) disk, hard disk, etc.), optical disk (CD-ROM, DVD, etc.), semiconductor memory, etc., and sent and received via a network. You can also

DESCRIPTION OF SYMBOLS 1,10 MIMO-OFDM receiver 3,13 Transmission path response calculation part 8,18 Parameter optimal value determination part 11 Effective symbol period extraction and FFT part 12 SP extraction part 14 MIMO equalization / polarization separation part 15 Symbol synthesis part 16 Likelihood calculation unit 17 TMCC reading unit 19 LDPC code decoding unit 21 Multipath component power measurement units 22 and 25 DB
23, 26 Parameter determination unit 24 Condition number calculation unit

Claims (6)

In a MIMO-OFDM receiver that receives OFDM signals transmitted from a plurality of transmitting antennas via a plurality of receiving antennas,
A MIMO-OFDM demodulator that demodulates the received OFDM signal to perform MIMO equalization, generates an original signal, and calculates transmission path responses between the plurality of transmitting antennas and the plurality of receiving antennas; ,
A likelihood calculation unit for calculating the likelihood of the original signal generated by the MIMO-OFDM demodulation unit;
A parameter optimum value determination unit for determining an optimum value of a parameter used for decoding processing of the LDPC code;
An LDPC code decoding unit that performs an LDPC code decoding process on the likelihood calculated by the likelihood calculating unit using an optimum value of the parameter determined by the parameter optimal value determining unit,
The parameter optimum value determination unit
Based on the transmission path response calculated by the MIMO-OFDM demodulator, data that reflects the state of the transmission path is obtained, and at least a parameter and data that reflects the state of the transmission path are stored in advance correspondingly. The MIMO-OFDM receiving apparatus, wherein the parameter corresponding to the obtained data is determined to be an optimum value using. The MIMO-OFDM receiver according to claim 1,
The parameter optimum value determination unit
A multipath component power measurement unit that measures a D / U ratio of the multipath component power as data reflecting the state of the transmission path based on the transmission path response calculated by the MIMO-OFDM demodulation unit;
A DB in which a table corresponding to at least a parameter and a D / U ratio of multipath component power is stored in advance;
A parameter determination unit that determines a parameter corresponding to the D / U ratio of the multipath component power measured by the multipath component power measurement unit as an optimum value;
A MIMO-OFDM receiver characterized by comprising: The MIMO-OFDM receiver according to claim 1,
The parameter optimum value determination unit
A condition number calculation unit that calculates the condition number of the matrix of the transmission line response as data reflecting the state of the transmission line based on the transmission line response calculated by the MIMO-OFDM demodulation unit;
A DB in which a table corresponding to at least a parameter and a condition number of a channel response matrix is stored in advance;
A parameter determining unit that determines a parameter corresponding to the condition number of the transmission path response matrix calculated by the condition number calculating unit as an optimum value;
A MIMO-OFDM receiver characterized by comprising: The MIMO-OFDM receiver according to claim 2 or 3,
The decoding process of the LDPC code by the LDPC code decoding unit is a decoding process by the normalized UMP BP method,
As a parameter of the DB of claim 2, a value of a relation that increases as the D / U ratio of the multipath component power increases and decreases as the D / U ratio of the multipath component power decreases is stored.
The DB parameter of claim 3 stores a relational value that decreases as the condition number of the transmission path response matrix increases and increases as the condition number of the transmission path response matrix decreases. A MIMO-OFDM receiver. The MIMO-OFDM receiver according to claim 2 or 3,
The decoding process of the LDPC code by the LDPC code decoding unit is a decoding process by the offset UMP BP method,
The DB parameter of claim 2 stores a value of a relationship that decreases as the D / U ratio of the multipath component power increases and increases as the D / U ratio of the multipath component power decreases.
The DB parameter of claim 3 stores a relational value that increases as the condition number of the channel response matrix increases and decreases as the condition number of the channel response matrix decreases. A MIMO-OFDM receiver. OFDM signals transmitted from a plurality of transmission antennas are received via a plurality of reception antennas, and the received OFDM signals are demodulated to perform MIMO equalization to generate an original signal, and the plurality of transmission antennas A MIMO-OFDM demodulator that calculates a channel response between the receiver and the plurality of receiving antennas, a likelihood calculator that calculates the likelihood of the original signal generated by the MIMO-OFDM demodulator, and an LDPC code A parameter optimum value determining unit that determines an optimum value of a parameter used in the decoding process, and the likelihood calculated by the likelihood calculating unit using an optimum value of the parameter determined by the parameter optimum value determining unit An LDPC code decoding unit that performs LDPC code decoding processing, and a computer that configures a MIMO-OFDM receiver,
Obtaining data reflecting the state of the transmission path based on the transmission path response calculated by the MIMO-OFDM demodulation unit;
Determining a parameter corresponding to the obtained data as an optimum value using a table in which at least the parameter and data reflecting the state of the transmission path are stored in advance;
A program characterized by having executed.

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