WO2014045624A1 - Radio communication system, reception apparatus and reception method - Google Patents

Abstract

A radio communication system comprises a transmission apparatus and a reception apparatus that use subcarriers to perform communications therebetween. The reception apparatus comprises: a radio reception unit that performs, for a received signal, an over-sampling in accordance with a separation degree indicating a degree of separating, from the received signal, noise signals added to the signal, which was transmitted by the transmission apparatus, over the communication channel between the transmission apparatus and the reception apparatus; a demodulation unit that calculates, from a transformation matrix (H) defined on the basis of the intervals between the frequencies of the subcarriers, the number of the subcarriers and the separation degree and also from the signal obtained by the over-sampling, the signals on the subcarriers and the signals between the subcarriers; and a demapping unit that digitally demodulates the signals on the subcarriers, which were calculated by the demodulation unit, to calculate the received data.

Description

Wireless communication system, receiving apparatus, and receiving method

The present invention relates to a radio communication system, a receiving apparatus, and a receiving method using a frequency division multiplexing system.
This application claims priority based on Japanese Patent Application No. 2012-208647 filed in Japan on September 21, 2012, the contents of which are incorporated herein by reference.

Digital terrestrial television broadcasting started in Japan in 2003, and simultaneous broadcasting with analog terrestrial television broadcasting ended in March 2012. Even if the terrestrial analog television broadcast can be received by changing the frequency used, there is an area where the terrestrial digital television broadcast cannot be received (digital hard-to-see area). In order to be able to receive digital terrestrial television broadcasting in such areas, for example, the sensitivity of the receiving antenna is increased, or the NF (Noise Figure) of the preamplifier provided in the receiving device (receiver) is set. It is necessary to lower the sensitivity or increase the sensitivity of the receiving device.

In a wireless communication system, a signal obtained by adding a noise signal in a communication path to a transmission signal transmitted from a transmission device is received by a reception device. In general, reception processing is performed on the assumption that the transmission signal and the noise signal cannot be separated in the reception device. The channel capacity in such a wireless communication system has been studied by Claude Shannon (Non-Patent Document 1, Non-Patent Document 2).

According to Non-Patent Document 1 or Non-Patent Document 2, the channel capacity C _i of the binary code to which white noise is added has a bandwidth limited to W, and the average power of the signal is S _i . Under the condition that the noise power is _Ni , it is known that there is a limit expressed by the following equation (1) even if the best coding is used. Further, it is not possible to exceed this speed without producing a certain error rate no matter what skillful coding is performed. 2, which is called the Shannon limit.

In a wireless communication system in which a noise signal is added to a transmission signal in a communication channel, a communication method exceeding the Shannon limit has not been found in research over 60 years since the announcement of the Shannon limit. For example, if a communication method exceeding Shannon's limit is found and the reception method is improved by applying the communication method to a receiving apparatus for terrestrial digital television broadcasting, it is possible to reduce the digitally difficult viewing area.

The present invention provides a wireless communication system, a receiving apparatus, and a receiving method capable of improving reception performance when receiving a signal via a communication path affected by noise.

According to the first aspect of the present invention, the wireless communication system is a wireless communication system including a transmission device and a reception device that perform communication using subcarriers, and the reception device includes the transmission device and the reception device. A wireless receiver that performs oversampling on the received signal according to the degree of separation indicating the degree of separation of the noise signal added to the signal transmitted by the transmitting device from the received signal in the communication path between , A signal in each subcarrier, and a signal between the subcarriers from a transformation matrix H determined based on the frequency interval and number of the subcarriers and the degree of separation, and a signal obtained by the oversampling. And a demodulator that digitally demodulates the signal in each subcarrier calculated by the demodulator to calculate received data. It includes a mappings section.

According to the second aspect of the present invention, in the wireless communication system according to the first aspect, the signal obtained by the oversampling is a column vector x, and the signal in the subcarrier and the signal between the subcarriers are the column vector X. In this case, the demodulation unit may calculate a signal in each subcarrier by solving the following equation (A).
(The transformation matrix H) × (the column vector X) = (the column vector x) (A)

According to the third aspect of the present invention, in the wireless communication system according to the second aspect, when the number of subcarriers is N and the degree of separation is M, the signal obtained by the oversampling is Of the signals on the frequency axis obtained by performing DFT with the number of sample points (B (B is an integer equal to or greater than 1) × N × M), N signals on the lower frequency side are extracted, and the extracted signals are extracted. A filter unit that outputs a time-axis signal obtained by performing IDFT on the signal is further provided, and the demodulating unit outputs a signal in each subcarrier and a signal between the subcarriers from the signal output from the filter unit. It may be calculated.

According to the fourth aspect of the present invention, in the wireless communication system according to the second aspect or the third aspect, the transmitting apparatus transmits the transmission data to be transmitted to the receiving apparatus and the conversion matrix H to the receiving apparatus. A signal to be transmitted may be calculated.
According to the fifth aspect of the present invention, in the wireless communication system according to the second aspect or the third aspect, when the degree of separation is M, the transmission device adds 0 ( Zero) is added to convert the data amount to M times and IDFT is performed to convert it into a time axis signal. The time axis signal obtained by the conversion is divided into M equal parts, The signal of the head part may be transmitted to the receiving device.

According to the sixth aspect of the present invention, in the wireless communication system according to any one of the second aspect to the fifth aspect, the demodulation unit performs sweeping when calculating the upper triangular matrix from the conversion matrix H. When the transformation matrix H is a square matrix of N rows and N columns, the row vector having the largest norm with the kth (k <N) row vector is detected from the (k + 1) th row vector to the Nth row vector. The detected row vector and the (k + 1) th row vector may be exchanged, and the column vector including the largest element among the elements of the kth row vector may be exchanged.

According to the seventh aspect of the present invention, the reception device is a reception device in a wireless communication system including a transmission device that performs communication using subcarriers and the reception device, and is between the transmission device and the reception device. A radio receiving unit that performs oversampling on the received signal according to a degree of separation indicating a degree of separation of a noise signal added to the signal transmitted by the transmitting device from the received signal in the communication path of A signal in each subcarrier and a signal between the subcarriers are calculated from a transformation matrix H determined based on the frequency interval and the number of carriers, and the degree of separation, and a signal obtained by the oversampling. And a demapping unit that digitally demodulates a signal in each subcarrier calculated by the demodulation unit to calculate received data It comprises a part, a.

According to an eighth aspect of the present invention, a reception method is a reception method in a wireless communication system including a transmission device that performs communication using subcarriers and a reception device, and is between the transmission device and the reception device. A radio reception step of performing oversampling on the received signal according to a degree of separation indicating a degree of separation of a noise signal added to a signal transmitted by the transmitting device in a communication path of the received signal from the received signal; A signal in each subcarrier and a signal between the subcarriers are calculated from a transformation matrix H determined based on the frequency interval and the number of carriers, and the degree of separation, and a signal obtained by the oversampling. And a demodulation step for digitally demodulating the signal on each of the subcarriers calculated in the demodulation step. And a demapping step of calculating the data.

According to one embodiment of the present invention, the demodulator demodulates the signal between subcarriers together with the signal of each subcarrier, whereby the noise signal included in the received signal can be dispersed in the demodulated signal. The degree of the noise signal included in the carrier signal can be suppressed.
As a result, it is possible to reduce the influence of the noise signal added in the communication path and improve the reception performance of the receiving apparatus.

It is a functional block diagram which shows the outline | summary of this invention. It is a figure which shows the concept of DAT which concerns on this invention. It is a figure which shows the concept of DAT which concerns on this invention. It is a figure which shows the concept of DAT which concerns on this invention. It is a graph which shows the real part of each component of the matrix H in DAT when N = 2 and M = 4. It is a graph which shows the imaginary part of each component of the matrix H in DAT when N = 2 and M = 4. It is a graph which shows the real part of each component of the inverse matrix H- ^{1 in} IDAT when N = 2 and M = 4. It is a graph which shows the imaginary part of each component of the inverse matrix H- ^{1 in} IDAT when N = 2 and M = 4. It is a graph which shows the evaluation result of the effective bit in the product (H * H ^-1 ) of the matrix H and the inverse matrix H ^-1 in DAT. It is a graph which shows the computer simulation result of communication using DAT and IDAT. It is a figure which shows the outline | summary of a Norm pivot selection method. 1 is a schematic block diagram illustrating a configuration of a wireless communication system 100 according to a first embodiment of the present invention. It is a schematic block diagram which shows the structure of the filter part 152 in the 1st Embodiment of this invention. It is the schematic which shows the image of the signal processing in the filter part 152 in the 1st Embodiment of this invention. It is a schematic block diagram which shows the structure of the radio | wireless communications system 200 in the 2nd Embodiment of this invention. It is a schematic block diagram which shows the structure of the radio | wireless communications system 300 in the 3rd Embodiment of this invention.

Before describing a mode for carrying out the present invention (embodiment), an outline of the present invention will be described. FIG. 1 is a functional block diagram showing an outline of the present invention. In the wireless communication system 10 according to the present invention, the transmission data generated in the information source 11 is transmitted by the transmission device 12 as a transmission signal of transmission power (S _i ). The noise signal of power (N _i ) generated in the noise source 13 is added to the transmission signal of transmission power (S _i ) in the communication path. The reception device 14 receives a signal of power (S _i + N _i ) obtained by adding the transmission signal and the noise signal, and obtains reception data.

In the receiving device 14, the noise separator 15 separates a noise signal from the received signal (power: S _i + N _i ). The demapping unit 16 digitally demodulates a signal (power: S _i + N _i / M) obtained by separating the noise signal, thereby obtaining received data. Here, M is the degree of separation when noise is separated from the received signal (power: S _i + N _i ). The noise separator 15 separates the signal (power: S _i + N _i ) into a noise component (power: N _i (1-1 / M)) and a desired component (power: S _i + N _i / M). . The transmission device 12 and the reception device 14 communicate with each other by a frequency division multiplexing method using subcarriers.

Here, when the power of the noise component separated by the noise separator 15 is N ′ and the power of the desired component is S ′, N ′ and S ′ are expressed by the following equation (2).

When the noise separator 15 separates the noise component from the received signal (power: S _i + N _i ), the noise power added to the signal to be digitally demodulated by the demapping unit 16 is (N _i / M). That is, the noise power is (1 / M) times. At this time, the Shannon limit is applied to the power (S _i + N _i / M) of the signal to be demodulated by the demapping unit 16, so the Shannon channel capacity (equation (1)) is The following expression (3) corrected by the inventors of the present application is obtained.

In Formula (3), if the degree of separation M can be increased as much as possible (M → ∞), the power of the desired component becomes ((S ′ = (S _i + N _i / M)) → S _i ) The power of the noise component is ((N ′ = N _i (1-1 / M)) → N _i ).
If the degree of separation M increases as much as possible (M → ∞), the channel capacity _Co increases as much as possible (C _o → ∞). That is, there is no limitation on the transmission path capacity in form.

Hereinafter, a DAT (Discrete high Accuracy Transform or Discrete Arata Transform) used in the present invention, which is a conversion for separating a noise component from a received signal, is derived in three stages.
First, a thought experiment is performed in the Fourier transform of a continuous signal. The transmission signal is an OFDM (Orthogonal Frequency Division Multiplexing) signal X (ω) that has an infinite length and the modulation content does not change for an infinite time. Consider the case of addition.

2A, 2B and 2C are diagrams showing the concept of DAT according to the present invention. FIG. 2A is a schematic diagram illustrating the OFDM signal X (ω) and white noise. In FIG. 2A, the horizontal axis represents frequency and the vertical axis represents signal intensity (amplitude). The numbers shown along the horizontal axis are numbers for identifying subcarriers. Here, two OFDM signals X (0) and X (1) are shown. Each carrier signal of the OFDM signal X (ω), (ω = 0, 1) is converted into a δ function. The carrier signal represented by the δ function has a zero bandwidth, and a component exists only at each transmission frequency. Further, the power density of white noise is constant within the band. Therefore, it can be seen that the noise signal and the OFDM signal X (ω) can be separated by the Fourier transform of the continuous signal. However, it is difficult to physically realize a Fourier transform of a continuous signal.

Next, demodulation of the OFDM signal X (k) using M-times oversampled DFT (Discrete Fourier Transform) will be considered. At this time, the sampling frequency is M times the frequency interval of the subcarriers.
FIG. 2B is a schematic diagram showing OFDM signals X (0) and X (1) and white noise as in FIG. 2A. FIG. 2B shows an OFDM signal X (k) using oversampled DFT when M = 4. As shown in FIG. 2B, by setting M = 4, OFDM signals X (2),..., X corresponding to subcarriers having a frequency higher than the subcarrier frequency of OFDM signals X (0), X (1). (7) is obtained. However, the total power of white noise is assigned to each carrier X (0), X (1). That is, when demodulating the OFDM signal X (k) using DFT, white noise is added to the spectrum of the OFDM signal even though it is uniformly distributed at each frequency. This is the same even if the sampling frequency is increased in the DFT or the observation period is extended by repeatedly arranging the signals. This is a drawback of DFT.

Here, it is assumed that the frequency resolution of the spectrum for the OFDM signal X (k) can be increased M times. FIG. 2C is a schematic diagram illustrating a case where the frequency resolution can be increased by M (M = 4) times. As shown in FIG. 2C, by setting M = 4, in addition to signals X (0) and X (4) corresponding to each subcarrier, signals X (1) to X ( 3), X (5) to X (7) are present. In this case, white noise is assigned to each of the signals X (0) to X (7). When attention is paid to the signals X (0) and X (4), the assigned white noise becomes (1 / M) times. Thus, when the frequency resolution is M times and a spectrum between subcarrier frequencies is obtained, white noise in the spectrum of the subcarrier frequency can be separated.

Considering each time axis signal, OFDM DFT signals are orthogonal, and their complex amplitudes are Fourier coefficients. At this time, spectra appearing between the subcarrier frequencies, for example, X (1), X (2), and X (3) are Fouriers of complex sine waves whose frequencies are shifted by (1 / M) from the adjacent subcarriers. It is a coefficient and is considered to be a complex sine wave cut off at the end points. The signal X (0) and the signal X (4) having a frequency corresponding to DFT are orthogonal to each other, but are not orthogonal to other signals.

Next, we will consider obtaining the spectrum of a signal cut out in a finite interval. The arrangement of the frequency spectrum is considered to be a spectrum obtained by DFT divided into M pieces on the frequency axis. The signal is not a sum of orthogonal sine waves as in Fourier transform, but a sum of sine waves divided in intervals. The sine wave at this time does not necessarily have to be orthogonal. As will be described later, the time axis is also divided into M pieces because of the necessity of solving the square matrix. That is, the sampling frequency is set to M times. At this time, the time waveform of each signal is expressed by the following equation (4).

Based on the above examination, DAT (Discrete high Accuracy Transform or Discrete Arata Transform) is derived.
First, IDAT (Inverse Discrete high Accuracy Transform or Inverse Discrete Arata Transform), which is the inverse transformation of DAT, is defined by the following equation (5), then the matrix representation of IDAT is obtained, and finally the linear equation is solved to derive DAT. To do.

In Equation (5), X (k) is a column vector obtained by sampling the frequency spectrum, x (n) is a column vector obtained by sampling the time axis waveform, and M and N are It is a scalar. N corresponds to the total number of points in DFT (the number of calculation data points or the number of sample points), and M is an improvement factor of the frequency resolution on the frequency axis. That is, with respect to DFT, the sampling interval on the time axis is (1 / M) times and the spectral interval on the frequency axis is (1 / M) times.

Next, the relationship between the variable k on the frequency axis and the frequency f _k and the relationship between the variable n on the time axis and time t _n are obtained.
The spectral interval on the frequency axis is multiplied by (1 / M) (formula (6-1)). Further, the sampling interval on the time axis is multiplied by (1 / M) (formula (6-2)).

Subsequently, the IDAT expressed by Equation (5) is transformed into a linear equation using a matrix, and the frequency spectrum X (k) is derived from the time waveform x (n). The elements h _{n, k} , x _n , and X _k of the matrix H and the column vectors x and X are defined by the following equation (7). Further, the matrix H and the column vectors x and X are defined by the following equation (8). The size of the matrix H is MN × MN (MN rows and MN columns), the size of the column vector x is MN, and the size of the column vector X is MN.

If Expression (7) is used, Expression (5) of IDAT can be rewritten as the following Expression (9).

Furthermore, when Expression (8) is used, Expression (9) can be rewritten as the following Expression (10).

Thus, IDAT can be expressed by a linear equation using a matrix.
Here, if the matrix H is regular, a column vector X (signal on the frequency axis) can be obtained by finding a solution of a linear equation. DAT is defined by the following equation (11) obtained by formally solving equation (10).

In Equation (11), x is a column vector obtained by sampling the time axis waveform, M and N are scalars, and X is a column vector obtained by sampling the frequency spectrum. Therefore, the DAT frequency spectrum can be obtained from the time axis waveform by matrix calculation. In general, it is more advantageous in terms of calculation amount and error to solve the linear equation represented by the following equation (12) by the LU decomposition method or Gaussian elimination method.

Here, an example of the matrix H and the inverse matrix H ⁻¹ used in DAT and IDAT is shown.
3A and 3B are graphs showing the real part and the imaginary part of each component of the matrix H in DAT when N = 2 and M = 4. 3A and 3B show values of the elements h _{n, k} (n = 0,..., 7; k = 0,..., 7) of the matrix H. FIG. FIG. 3A shows the value of the real part, and the value of h _{n, k} is represented as a graph for each value of _n . The graph of n = 0 shows a direct current component, and the graph of n = 4 shows a sine wave for one cycle. The graphs of n = 1, 2, 3 indicate sine waves of 1/4 cycle, 1/2 cycle, and 3/4 cycle, respectively. In addition, the graphs of n = 5, 6, and 7 indicate sine waves of 5/4 period, 3/2 period, and 7/4 period, respectively.

FIG. 3B shows the value of the imaginary part, and similarly to FIG. 3A, the value of h _{n, k} is represented as a graph for each value of _n . n = 0 indicates the direct current component as in the real part, and the graph of n = 4 indicates a sine wave for one cycle. For example, the graph of n = 0, 4 corresponds to the subcarrier signals X (0) and X (1) in FIG. 2C. In addition, the graphs of n = 1, 2, 3, 5, 6, and 7 are each 1/4 cycle, 1/2 cycle, 3/4 cycle, 5/4 cycle, 3 like the real part value. A sine wave having a / 2 period and a 7/4 period is shown.

4A and 4B are graphs showing the real part and the imaginary part of each component of the inverse matrix H ^{−1 in} IDAT when N = 2 and M = 4. 4A and 4B show values of elements h ⁻¹ _{n, k} (n = 0,..., 7; k = 0,..., 7) of the inverse matrix H ⁻¹ . FIG. 4A shows real part values, and for each value of n, the value of h ⁻¹ _{n, k} is represented as a graph. FIG. 4B shows the value of the imaginary part, and the value of h ⁻¹ _{n, k} is represented as a graph for each value of _k .

As described above, the DAT is derived by solving the linear equation of IDAT formally, but if the matrix H is not regular, that is, if the determinant of the matrix H is 0, the inverse matrix H ⁻¹ does not exist, DAT cannot be defined. Also, it is not obvious whether the matrix H is regular in all M and N. Therefore, it is examined whether the matrix H is regular by a numerical experiment.

Using numerical analysis software (for example, GNU Octave), the ranks of the 8 × 8 complex matrix H and the inverse matrix H ⁻¹ in DAT were calculated, and both ranks were 16 (Rank (H) = 16, Rank (H ⁻¹ ) = 16).
However, although the matrix H and the inverse matrix H ⁻¹ are regular (the determinant is not 0), the condition number is very large and both are ill-posed conditioned matrices. This means that if the values of M and N are increased in the numerical calculation, the error increases, and it is likely that the calculation becomes impossible due to an easily ill-posed condition.

The condition numbers of the complex matrix H and the inverse matrix H ⁻¹ having a size of 8 × 8 were cond (H) = 9.47 × 10 ¹¹ and cond (H ⁻¹ ) = 9.47 × 10 ¹¹ , respectively. Incidentally, the Hilbert matrix is known as an ill-conditioned matrix. When the condition number and rank of the 16th-order Hilbert matrix are calculated by numerical analysis software, cond (Hilbert (16)) = 4.48. × 10 ¹⁷ , rank (Hilbert (16)) = 12.
The matrix H in the DAT is a better condition than the Hilbert matrix, but if the values of M and N are increased, it becomes an ill-posed condition, resulting in difficulty in calculation.

Here, the relationship between the effective bit length in DAT and M and N will be examined.
Using the method described in Reference 1, the effective bits in the product (H * H ⁻¹ ) of the matrix H and inverse matrix H ⁻¹ in DAT were evaluated (Reference 1: Shinichi Oishi, “MATLAB "Numerical calculation by" (mathematical information series), Baifukan, July 2001).
FIG. 5 is a graph showing an evaluation result of effective bits in the product (H * H ⁻¹ ) of the matrix H and the inverse matrix H ⁻¹ in DAT. In FIG. 5, the horizontal axis indicates the value of MN, and the vertical axis indicates the error. Here, since DAT in the case of M = 1 is the same as that in DFT, the effective bit length in M = 1 is the effective bit length in DFT. As M increases, the effective bit length of DAT decreases rapidly. For example, even when MN = 16, N = 4, and M = 4, the error is 5.0 × 10 ⁻⁴ .

DAT is not orthogonal transform like DFT. The DAT spectrum has a resolution M times as high as that of the rate N DFT, but the maximum frequency is (N− (1 / M)). In addition, M times oversampling is performed on the time axis. Therefore, when a signal generated using IDAT is demodulated using DFT, only the first N (K = 1,..., N) spectra can be demodulated correctly.
In order to generate a signal that can be demodulated by DAT using DFT, DFT is performed with M times the resolution. Since the length of the signal obtained at this time is M times, the first L pieces (K = 1,..., L) are cut out from the signal to make the length (1 / M) times. .

As described above, when M = 1, DAT matches DFT (formula (13-1)), and IDAT is IDFT (InverseInDiscrete Fourier Transform) (formula (13-2)). Matches.

BER (Bit Error Ratio) against CN (Carrier to Noise に お け る ratio) ratio in communication using DAT and IDAT was calculated by computer simulation. A wireless communication system targeted for computer simulation is a system that transmits in OFDM using BPSK (Binary Phase Shift Keying) and IDAT, and uses DAT and BPSK for demodulation. It is. Specifically, on the transmission side, a PN (Pseudo Random Noise) signal of length N is generated, the PN signal is mapped with BPSK, and the signal obtained by upsampling the frequency to IDAT Is converted into a frequency axis signal. Then, noise of length L was added to the signal obtained using IDAT, demodulated using DAT, resampled on the frequency axis, PBSK demapping was performed, and BER was measured. . The simulation was terminated when the number of errors reached 1000.

FIG. 6 is a graph showing a computer simulation result of communication using DAT and IDAT. In FIG. 6, the horizontal axis indicates the CN ratio, and the vertical axis indicates the BER. In the OFDM-BPSK-FFT demodulation, the CN ratio at which the BER is 1.0 × 10 ⁻⁴ is 8.4 [dB]. On the other hand, in the OFDM-PBSK-DAT demodulation, the CN ratio at which the BER is 1.0 × 10 ⁻⁴ is 5.4 [dB], and an improvement of 3 [dB] can be achieved. The logical improvement amount is also 3 [dB].

Actually, when DAT and IDAT are applied to a wireless communication system, if the number of subcarriers N, the degree of separation M, and the length L of a signal to be transmitted increase, the time required for the calculation of equation (12) increases, and the responsiveness Is considered to be reduced.

For example, when the Gaussian elimination method is used to solve equation (12), a matrix operation called sweeping is performed. In the sweep-out, in order to erase the elements on the left side of the matrix sequentially to 0 for each row, the reciprocal number of the elements on the diagonal line from the upper left to the lower right of the matrix is calculated. It is known that the error increases if the value of this diagonal element is small. The element on the diagonal line is called a pivot. In a general partial pivot selection method in the Gaussian elimination method, an element having the largest absolute value is selected as the element on the diagonal line (reference document 2). : Shoji Ura, “Introduction to FORTRAN 77 (Programming Computers)” (revised edition), Baifukan, September 1990).

However, since the absolute value of each element of the matrix H in DAT is all 1, the partial pivot selection method (reference 3) generally used does not operate because the pivot is not exchanged (reference). Reference 3: Toto Hayato, "Science and Technology Calculation Handbook on UNIX Workstations-Basic Edition C Language Version", Science, February 1998).

In the matrix H in DAT, the frequency of the row vector in the first row is 0, that is, the DC component is sampled, so each element of the row vector in the first row is always 1. The second row vector is a sample of a complex waveform having a very low frequency, and its absolute value is very close to 1. Therefore, if the value in the first column is erased to 0 in the second row vector, the value in the second column is very close to 0.
As a result, when sweeping is repeated using a value close to 0 as the pivot, the effective accuracy deteriorates rapidly. For example, if a highly accurate calculation is performed to compensate for this, the time required for the processing becomes longer, and the response performance is degraded.

Therefore, when solving the equation (12), the use of the Norm pivot selection method described below can suppress a decrease in effective accuracy and improve response performance.
In the Gaussian elimination method, the result of performing subtraction between row vectors is the next pivot row vector. Therefore, the row vectors are exchanged so that the row vector having the maximum norm between the pivot row vector and the row vector to be subtracted becomes the row vector next to the pivot row vector. This maximizes the vector of pivot rows at the next sweep.
Further, in the second and subsequent sweeps, column vectors are replaced so that the largest element among the elements of the pivot row vector is a pivot.

FIG. 7 is a diagram showing an outline of the Norm pivot selection method.
Here, a description will be given by taking as an example a case of performing sweeping to erase k columns of the row vector of the (k + 1) th row to 0.
First, with reference to the row vector [H (k, 1),..., H (k, k), H (k, k + 1),. , H (i, k), H (i, k + 1),..., H (i, N)], (i = k + 1,..., N ) And the k-th row vector, the norm Nr of the difference vector is calculated.

In the equation (14), the function Norm () for calculating the norm Nr is given by the following equation (15) when a vector X = [x (1), x (2),..., X (N)] is given. The square root of the sum of squares of each element, that is, the Euclidean norm is calculated.

The row vector corresponding to the largest norm among the calculated norms is exchanged with the row vector of the (k + 1) th row.
Next, paying attention to the row vector of the k-th row, the largest element among the elements H (k, k),..., H (k, N) is detected, and the column vector including the element and the k-th column Replace the column vector of.
The matrix operation described above is the Norm pivot selection method. By using the Norm pivot selection method, it is possible to suppress an error that occurs when solving the equation (12), and it is possible to perform DAT and IDAT without using a double precision calculation or the like. Thereby, the time required for calculation can be reduced, and the response performance of the wireless communication system can be improved.

Hereinafter, a wireless communication apparatus including a receiving apparatus that performs demodulation using DAT according to the present invention will be described with reference to the drawings. In the following description, it is assumed that the receiving apparatus performs processing in which the frequency resolution on the frequency axis is increased M times.

(First embodiment)
FIG. 8 is a schematic block diagram illustrating the configuration of the wireless communication system 100 according to the first embodiment of the present invention. The wireless communication system 100 is a system that performs wireless communication by a communication method (for example, OFDM method) using a plurality of orthogonal subcarriers, and includes a transmission device 110 and a reception device 150. The transmission device 110 transmits transmission data, and the reception device 150 demodulates the reception data from the signal received from the transmission device 110. In the following description, it is assumed that the number of subcarriers is N, the degree of separation is M, and the guard interval ratio + 1 is G.

As shown in FIG. 8, the transmission apparatus 110 includes a mapping unit 111, an IDFT unit 112, a GI (Guard Interval) insertion unit 113, and a wireless transmission unit 114. The receiving apparatus 150 includes a wireless reception unit 151, a filter unit 152, a DAT (Discrete high accuracy Transform ”or“ Discrete Arata Transform ”) 153, a resampling unit 154, and a demapping unit 155. The DAT unit 153 corresponds to the noise separator 15 in FIG. 1, and the demapping unit 155 corresponds to the demapping unit 16 in FIG.

Transmission data to be transmitted to the receiving device 150 is input to the mapping unit 111. The mapping unit 111 maps the input transmission data using digital modulation such as BPSK, QPSK (Quadrature Phase Shift Keying), and QAM (Quadrature Amplitude Modulation).
The IDFT unit 112 converts the data sequence obtained by mapping the transmission data by the mapping unit 111 into a plurality of data sequences corresponding to each subcarrier (serial-parallel conversion). The IDFT unit 112 performs IDFT conversion on a plurality of data strings obtained by the conversion, and converts the signal on the frequency axis into the signal on the time axis. Then, the IDFT unit 112 outputs the time axis signal obtained by the conversion to the GI insertion unit 113.

The GI insertion unit 113 adds a guard interval to the signal input from the IDFT unit 112 and outputs the signal to the wireless transmission unit 114. By adding the guard interval, the length of the signal output to the wireless transmission unit 114 is G times the length of the signal input from the IDFT unit 112.
The radio transmission unit 114 performs digital-analog conversion on the signal input from the GI insertion unit 113 and then transmits the signal from the antenna as an up-converter to the carrier frequency of each subcarrier. The processing in the transmission apparatus 110 is the same processing as the transmission processing in a general OFDM scheme.

The wireless reception unit 151 receives a signal transmitted from the transmission device 110 via an antenna. A signal received by the wireless reception unit 151 (hereinafter referred to as a reception signal) is added with a noise signal in a communication path between the transmission device 110 and the reception device 150. Radio receiving section 151 down-converts the component of the desired frequency band included in the received signal into the baseband band, and performs analog-digital conversion on the signal obtained by the down-conversion, and outputs it to filter section 152. Note that the sampling frequency in the analog-digital conversion of the wireless reception unit 151 is M times the sampling frequency for the transmission data. The digital signal output from the wireless reception unit 151 to the filter unit 152 is a signal obtained by sampling the complex envelope of the OFDM signal on the time axis.

The filter unit 152 extracts a signal in the subcarrier frequency band to be demodulated from the digital signal input from the wireless reception unit 151 and outputs the extracted signal to the DAT unit 153. FIG. 9 is a schematic block diagram showing the configuration of the filter unit 152 in the first embodiment. The filter unit 152 includes a blocking unit 501, a window function output unit 502, a blocking unit 503, a multiplication unit 504, a DFT unit 505, a bandpass filter unit 506, an IDFT unit 507, and an unblocking unit. 508, a GI removal unit 509, a GI removal unit 510, an inverse function generation unit 511, and a multiplication unit 512.

The block forming unit 501 blocks the digital signal (OFDM symbol) input from the radio receiving unit 151 from the block number B (B is an integer, and B ≧ M) continuous OFDM symbols and multiplies the signal as one signal. Output to 504. The length of the signal output from the blocking unit 501 to the multiplication unit 504 is (B × G × N × M).
The window function output unit 502 outputs a predetermined window function (for example, a Blackman-Harris window) in synchronization with the digital signal (OFDM symbol) output from the wireless reception unit 151. Here, the length of the window function is the same as the signal length (G × N × M) to be processed to which the guard interval is added.

The blocking unit 503 blocks the window function output from the window function output unit 502 for the number of blocks B, and outputs the block function to the multiplication unit 504 as one signal. The length of the signal (blocked window function) output from the blocking unit 503 to the multiplication unit 504 is (B × G × N × M).
The multiplication unit 504 multiplies the four consecutive OFDM symbols blocked by the blocking unit 501 by the four consecutive window functions blocked by the blocking unit 503, and performs a DFT on the signal obtained by the multiplication. Output to the unit 505. The length of the signal output from the multiplier 504 to the DFT unit 505 is (B × G × N × M).

The DFT unit 505 performs DFT on the signal output from the multiplying unit 504 with (B × G × N × M) as the total number of points, and converts the time-axis signal into a frequency-axis signal. The DFT unit 505 outputs the frequency axis signal obtained by the conversion to the bandpass filter unit 506.
The band-pass filter unit 506 selects (B × G × N) signals having a low frequency from the (B × G × N × M) frequency axis signals input from the DFT unit 505 to perform IDFT. Output to the unit 507. That is, a signal having a high frequency is removed from the signal input from the DFT unit 505 and output to the IDFT unit 507.
The IDFT unit 507 adds (B × G × N × (M−1)) “0” s to the (B × G × N) signals output from the bandpass filter unit 506 to obtain (B IDFT is performed with a total score of (× G × N × M), and a frequency axis signal is converted to a time axis signal. The IDFT unit 507 outputs the time axis signal obtained by the conversion to the unblocking unit 508.

The unblocking unit 508 performs unblocking to equally divide a signal having a length (B × G × N × M) output from the IDFT unit 507 into B signals. The (G × N × M) signal is output to the GI removal unit 509 in order.
The GI removal unit 509 removes the guard interval included in the signal output from the unblocking unit 508 and outputs the guard interval to the multiplication unit 512. The length of the signal output from the GI removal unit 509 to the multiplication unit 512 is (N × M).

The GI removal unit 510 removes a signal corresponding to the guard interval in the window function output from the window function output unit 502 and outputs the signal to the inverse function generation unit 511. The length of the signal output from the GI removal unit 509 to the inverse function generation unit 511 is (N × M).
The inverse function generation unit 511 calculates the inverse function of the window function from which the signal output from the GI removal unit 510, that is, the portion corresponding to the guard interval is removed, and outputs the calculated inverse function to the multiplication unit 512.

The multiplier 512 multiplies the signal of length (N × M) sequentially output from the GI removal unit 509 by the inverse function output from the inverse function generator 511, and obtains the length (N × M) obtained by the multiplication. M) is output to the DAT unit 153 as the output of the filter unit 152.
The filter unit 152 performs the above-described filtering process, so that even if band limiting is performed to leave a frequency to be demodulated for a digital signal obtained by performing M-times oversampling on the received signal, The signal component in between can be left.

Here, an outline of signal processing in the filter unit 152 will be described. FIG. 10 is a schematic diagram illustrating an image of signal processing in the filter unit 152. In FIG. 10, the signal input to the filter unit 152 ((a) input signal), the signal output from the blocking unit 501 ((b) blocked input signal), and the output from the blocking unit 503 Output signal ((c) window function blocked), a signal obtained by cutting the section defined by the window function by multiplication by the multiplication unit 504 ((d) window result), and output from the inverse function generation unit 511 The signal ((e) the inverse function of the window function) and the signal ((f) output signal) obtained by the multiplication by the multiplier 512 are shown. In FIG. 10, the horizontal axis represents the time axis. FIG. 10 shows a case where B = 4.

In FIG. 10, (a) the input signal is shown as a rectangle, but actually has a waveform close to noise. Here, in order to simplify the description, a rectangle is shown. The hatched areas on both sides of the input signal are guard intervals. In general, the guard interval is added to either the front or rear of the OFDM symbol, but here it is added to both the front and rear. A guard interval may be added to either the front or rear of the OFDM symbol.

(B) The blocked input signal represents a waveform in which four consecutive OFDM symbols are blocked by the blocking unit 501.
(C) The blocked window function represents a waveform obtained by blocking the window function W (G × N × M) into four blocks by the blocking unit 503.
(D) The window result represents a waveform obtained by multiplying the blocked input signal and the blocked window function on the time axis.
(E) The inverse function of the window function represents the waveform of the inverse window function (1 / W (G × N × M)) in the period excluding the guard interval period with the window function W (G × N × M).
(F) The output signal represents a signal output from the filter unit 152.

As described above, the signal (OFDM symbol) input to the filter unit 152 is subjected to filtering processing as one signal for each predetermined number of blocks B, and is divided into signals of the number of blocks B by the unblocking unit 508. Is output after
In the above description, the filtering process of the filter unit 152 for the signal to which the guard interval is added has been described. However, the guard interval may not be added. In this case, the GI removal units 509 and 510 are not necessary.

Returning to FIG. 8, the description of the receiving device 150 in the wireless communication system 100 will be continued.
The DAT unit 153 uses the matrix H (conversion matrix H) in the DAT for the signal (x (n); n = 0, 1,..., NM−1) input from the filter unit 152 to A frequency axis signal (X (k); k = 0, 1,..., NM−1) including a signal corresponding to the carrier and a signal between the subcarriers is calculated. Here, the signal corresponding to each subcarrier is, for example, the spectrum of X (0) and X (4) in FIG. 2C. On the other hand, the signals between the subcarriers are, for example, spectra of X (1) to X (3) and X (5) to X (7) in FIG. 2C. In other words, the DAT unit 153 demodulates the signal output from the filter unit 152 by DAT and outputs the demodulated signal to the resampling unit 154.

Specifically, the DAT unit 153 applies the signal (x (n)) input from the filter unit 152 and a predetermined matrix H to the equation (12), and generates a frequency-axis signal (X ( k)) is calculated. When the signal (X (k)) is calculated by applying Expression (12), simultaneous linear equations are solved. In this case, the DAT unit 153 calculates the upper triangular matrix using the above-described Norm pivot selection method.
Instead of applying Equation (12), Equation (11) may be applied to calculate the frequency axis signal (X (k)). In this case, multiplication of the inverse matrix H ^{−1 of the} matrix H and the signal (x (n)) is performed.

The frequency axis signal (X (k)) is input from the DAT unit 153 to the resampling unit 154. The resampling unit 154 selects the first, Mth, 2Mth,..., MNth signal from the top in the frequency axis signal (X (k); k = 0, 1,..., NM−1). Resampling is performed. Re-sampling takes signals X (0), X (4) from signals X (0), X (1),..., X (7) (N = 2, M = 4), taking FIG. It becomes processing to choose. The resampling unit 154 outputs the resampled signal to the demapping unit 155.

The demapping unit 155 performs (parallel-serial conversion) the signal input from the resampling unit 154 and performs digital demodulation corresponding to the digital modulation in the mapping unit 111. The demapping unit 155 outputs data obtained by digital demodulation as received data.

Since the receiving apparatus 150 converts the received signal using DAT, the noise signal included in the received signal can be separated as shown in FIG. Thereby, in the demapping unit 155, the Shannon's theorem is applied to the signal obtained by separating the noise signal from the received signal, so that reception exceeding the Shannon limit can be performed. As a result, reception performance can be improved when a signal is received via a communication path affected by noise.
Further, in the receiving apparatus 150, the filter unit 152 performs the above-described processing, so that a component (noise or the like) having a higher frequency than the frequency axis signal (X (NM-1)) can be suppressed, which is suitable for IDAT. Signal. Thereby, the degree of the noise signal contained in the signal of each subcarrier obtained by IDAT can be further suppressed, and the reception performance can be improved.

(Second Embodiment)
In the second embodiment, a configuration using an IDAT (Inverse Discrete high Accuracy Transform or Inverse Discrete Arata Transform) when generating a signal to be transmitted will be described.
FIG. 11 is a schematic block diagram illustrating a configuration of a wireless communication system 200 in the second embodiment. The wireless communication system 200 is different from the first embodiment in that a transmission device 210 that generates a transmission signal from transmission data using IDAT is provided instead of the transmission device 110 (FIG. 8). In the wireless communication system 200, the same components as those in the first embodiment are denoted by the same reference numerals and description thereof is omitted.

The wireless communication system 200 includes the transmission device 210 and the reception device 150 described above. The transmission apparatus 210 includes a mapping unit 111, an upsampling unit 214, an IDAT unit 212, a GI insertion unit 113, and a wireless transmission unit 114.
The upsampling unit 214 converts the data string obtained by mapping the transmission data by the mapping unit 111 into a data string of “number of subcarriers N” × “separation degree M”. The upsampling unit 214 outputs the data string obtained by the conversion to the IDAT unit 212. Specifically, the up-sampling unit 214 converts “number of subcarriers N” × “separation degree M” by adding “0” between the data in the data sequence. For example, when the input data string is “1111” and the separation degree M is 2, the upsampling unit 214 converts “1111” to “10101010”.

The IDAT unit 212 converts the data string input from the upsampling unit 214 into a time-axis signal using IDAT. The IDAT unit 212 outputs a signal obtained by IDAT to the GI insertion unit 113. When the input data string is converted into a time-axis signal, the IDAT unit 212 determines the input data string (X (k); k = 1, 2,..., NM-1) in advance. The matrix H is applied to Equation (10) to convert it into a time-axis signal (x (n); n = 1, 2,..., NM−1). Then, the IDAT unit 212 outputs the first, Mth, 2Mth,..., MNth signals from the top of the time axis signals obtained by the conversion to the GI insertion unit 113 as signals to be transmitted.
The signal output from the IDAT unit 212 to the GI insertion unit 113 is transmitted from the wireless transmission unit 114 after the guard interval is added by the GI insertion unit 113.

Also in the second embodiment, as in the first embodiment, since the receiving apparatus 150 converts the received signal using DAT, the noise signal included in the received signal is separated as shown in FIG. can do. Thereby, in the demapping unit 155, the Shannon's theorem is applied to the signal obtained by separating the noise signal from the received signal, so that reception exceeding the Shannon limit can be performed. As a result, reception performance can be improved when a signal is received via a communication path affected by noise.

In the second embodiment, the configuration in which “0” is added between data to be transmitted by the upsampling unit 214 in the transmission device 210 has been described. However, “0” may not be added to the data output to the IDAT unit 212, and all data to be transmitted may be output to the IDAT unit 212. In this case, the mapping unit 111 in the transmission device 210 outputs the signal (X (k); k = 1, 2,..., NM−1) to the IDAT unit 212, and the DAT unit 153 in the reception device 150 receives the signal (X ( k); k = 0, 1,..., NM-1) are output to the demapping unit 155. Thereby, the transmission capacity can be increased.

(Third embodiment)
In the third embodiment, a description will be given of a configuration in which a signal similar to the case where IDAT is used is generated by IDFT in a transmission apparatus.
FIG. 12 is a schematic block diagram illustrating a configuration of a wireless communication system 300 according to the third embodiment. The wireless communication system 300 is different from the first embodiment in that the wireless communication system 300 includes a transmission device 310 that generates a signal similar to that in the case of using IDAT by IDFT instead of the transmission device 110 (FIG. 8). Note that in the wireless communication system 300, the same reference numerals are given to the same components as those in the first embodiment, and description thereof is omitted.

The wireless communication system 300 includes the transmission device 310 and the reception device 150 described above. The transmission apparatus 310 includes a mapping unit 111, a signal extension unit 314, an IDFT unit 312, a signal extraction unit 315, a GI insertion unit 113, and a wireless transmission unit 114.

The data string output from the mapping unit 111 is input to the signal extension unit 314. The signal extension unit 314 adds “0 (zero)” after the data string for each data string corresponding to one OFDM symbol in order to multiply the data amount of the input data string by M times. Generate a column. The signal extension unit 314 outputs the generated data string to the IDFT unit 312. For example, when the data sequence of one OFDM symbol is “1111” and the data amount is 4 (M = 4) times, “000000000000” is added after “1111” and “1111000000000” is added. Generate.

The IDFT unit 312 performs IDFT on the data string input from the signal expansion unit 314 with N × M as the total number of points, and converts it into a time-axis signal. The IDFT unit 312 outputs the time axis signal obtained by the conversion to the signal extraction unit 315.
The signal extraction unit 315 outputs to the GI insertion unit 113 the signal at the head of the time-axis signal input from the IDFT unit 312 that is divided into M equal parts. That is, when the length of the time-axis signal input from the IDFT unit 312 is “1”, the signal extraction unit 315 extracts the signal at the head portion where the signal length is “1 / M”. The data is output to the GI insertion unit 113.
The signal output from the signal extraction unit 315 to the GI insertion unit 113 is transmitted from the wireless transmission unit 114 after a guard interval is added by the GI insertion unit 113.
In this way, by adding “0” to the data string to be transmitted and multiplying it by a factor of M, and extracting the first (1 / M) part after performing IDFT, IDAT is used. A similar transmission signal can be generated.

Also in the third embodiment, as in the first embodiment, since the receiving device 150 converts the received signal using DAT, the noise signal included in the received signal as shown in FIG. Can be separated. Thereby, in the demapping unit 155, the Shannon's theorem is applied to the signal obtained by separating the noise signal from the received signal, so that reception exceeding the Shannon limit can be performed. As a result, reception performance can be improved when a signal is received via a communication path affected by noise.

Note that a program for realizing the functions of the receiving device and the transmitting device in the present invention is recorded on a computer-readable recording medium, and the program recorded on the recording medium is read by a computer system and executed. Processing and transmission processing may be performed. Here, the “computer system” includes an OS and hardware such as peripheral devices. The “computer system” includes a WWW system having a homepage providing environment (or display environment). The “computer-readable recording medium” refers to a storage device such as a flexible medium, a magneto-optical disk, a portable medium such as a ROM or a CD-ROM, and a hard disk incorporated in a computer system. Further, the “computer-readable recording medium” refers to a volatile memory (RAM) in a computer system that becomes a server or a client when a program is transmitted via a network such as the Internet or a communication line such as a telephone line. In addition, those holding programs for a certain period of time are also included.

The program may be transmitted from a computer system storing the program in a storage device or the like to another computer system via a transmission medium or by a transmission wave in the transmission medium. Here, the “transmission medium” for transmitting the program refers to a medium having a function of transmitting information, such as a network (communication network) such as the Internet or a communication line (communication line) such as a telephone line. The program may be for realizing a part of the functions described above. Furthermore, what can implement | achieve the function mentioned above in combination with the program already recorded on the computer system, and what is called a difference file (difference program) may be sufficient.

The preferred embodiments of the present invention have been described and illustrated above, but these are merely examples of the present invention and should not be considered in a limited manner, and additions, deletions, substitutions, and other changes are not included in the spirit of the present invention. Alternatively, it is possible without departing from the scope. That is, the present invention is not limited by the above-described embodiments, but is limited by the scope of the following claims.

The present invention can be widely applied to a wireless communication system, a receiving device, and a receiving method, and can improve the receiving performance of the receiving device.

DESCRIPTION OF SYMBOLS 10 Radio communication system 11 Information source 12 Transmitter 13 Noise source 14 Receiver 15 Noise separator 16 Demapper 100 Radio communication system 110 Transmitter 111 Mapping unit 112 IDFT unit 113 GI insertion unit 114 Radio transmitter 150 Receiver 151 Radio Reception unit 152 Filter unit 153 DAT unit (demodulation unit)
154 Re-sampling unit 155 De-mapping unit 200 Wireless communication system 210 Transmitting device 212 IDAT unit 214 Upsampling unit 300 Wireless communication system 310 Transmitting device 312 IDFT unit 314 Signal expansion unit 315 Signal extraction unit,
501 Blocking unit 502 Window function output unit 503 Blocking unit 504 Multiplication unit 505 DFT unit 506 Band pass filter unit 507 IDFT unit 508 Unblocking unit 509 GI removal unit 510 GI removal unit 511 Inverse function generation unit 512 multiplication unit N _i Noise power _Si transmission power

Claims (8)

1. A wireless communication system comprising a transmission device and a reception device that perform communication using subcarriers,
   The receiving device is:
   Oversampling corresponding to the degree of separation indicating the degree of separation of the noise signal added to the signal transmitted by the transmission device from the reception signal in the communication path between the transmission device and the reception device is performed on the reception signal. A radio receiver for
   From the transformation matrix H determined based on the frequency interval and number of the subcarriers and the degree of separation, and the signal obtained by the oversampling, a signal in each subcarrier, and a signal between the subcarriers, A demodulation unit for calculating
   A demapping unit that digitally demodulates a signal in each of the subcarriers calculated by the demodulation unit to calculate received data;
   A wireless communication system comprising:
2. When the signal obtained by the oversampling is a column vector x, and the signal in the subcarrier and the signal between the subcarriers are column vectors X,
   The demodulator
   Formula (A)
   (The transformation matrix H) × (the column vector X) = (the column vector x) (A)
   The radio communication system according to claim 1, wherein a signal in the subcarrier is calculated by solving
3. When the number of subcarriers is N and the degree of separation is M,
   Of the signals on the frequency axis obtained by performing DFT with the number of sample points (B (B is an integer of 1 or more) × N × M) with respect to the signal obtained by oversampling, N on the lower frequency side A filter unit that extracts a plurality of signals and outputs a time-axis signal obtained by performing IDFT on the extracted signals;
   The radio communication system according to claim 2, wherein the demodulation unit calculates a signal in each subcarrier and a signal between the subcarriers from a signal output from the filter unit.
4. The transmitter is
   The radio communication system according to claim 2 or 3, wherein a signal to be transmitted to the receiving device is calculated from transmission data to be transmitted to the receiving device and the conversion matrix H.
5. When the degree of separation is M, the transmitter is
   IDFT is performed on the data obtained by adding 0 (zero) to the transmission data to be transmitted to the receiving apparatus and the data amount is multiplied by M, and converted to a time-axis signal, and the time-axis signal obtained by the conversion is converted. 4. The wireless communication system according to claim 2, wherein the signal is divided into M equal parts and a signal at a head portion of the divided M signals is transmitted to the receiving apparatus. 5.
6. The demodulator
   In sweeping out when calculating the upper triangular matrix from the transformation matrix H, when the transformation matrix H is a square matrix of N rows and N columns,
   The row vector having the largest norm with the kth (k <N) row vector is detected from the (k + 1) th row vector to the Nth row vector, and the detected row vector and the (k + 1) th row vector are exchanged. ,
   The radio communication system according to any one of claims 2 to 5, wherein a column vector including the largest element among the elements of the k-th row vector is exchanged with a k-th column vector. .
7. A reception device in a wireless communication system including a transmission device and a reception device that perform communication using subcarriers,
   Oversampling corresponding to the degree of separation indicating the degree of separation of the noise signal added to the signal transmitted by the transmission device from the reception signal in the communication path between the transmission device and the reception device is performed on the reception signal. A radio receiver for
   From the transformation matrix H determined based on the frequency interval and number of the subcarriers and the degree of separation, and the signal obtained by the oversampling, a signal in each subcarrier, and a signal between the subcarriers, A demodulation unit for calculating
   A demapping unit that digitally demodulates a signal in each of the subcarriers calculated by the demodulation unit to calculate received data;
   A receiving apparatus comprising:
8. A reception method in a wireless communication system including a transmission device and a reception device that perform communication using subcarriers,
   Oversampling corresponding to the degree of separation indicating the degree of separation of the noise signal added to the signal transmitted by the transmission device from the reception signal in the communication path between the transmission device and the reception device is performed on the reception signal. Wireless reception step to be performed,
   From the transformation matrix H determined based on the frequency interval and number of the subcarriers and the degree of separation, and the signal obtained by the oversampling, a signal in each subcarrier, and a signal between the subcarriers, A demodulation step to calculate
   A demapping step of calculating received data by digitally demodulating a signal in each of the subcarriers calculated in the demodulation step;
   A receiving method comprising:

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