JP5676513B2 - Receiver - Google Patents

Description

  The present invention relates to a receiving apparatus.

  In wireless communication such as digital terrestrial television broadcasting, distortion may occur in a transmission path due to multipath interference, and reception accuracy may decrease. For this reason, in a receiving apparatus such as a digital television receiver, equalization processing for correcting distortion generated in the transmission path is performed in order to prevent a decrease in reception accuracy.

  In the equalization processing, a transmission path response is estimated using a pilot signal included in a received signal after Fourier transform, and a data signal included in the received signal after Fourier transform is corrected based on the estimation result (for example, a patent) Reference 1).

JP 2010-268100 A

  However, the above-described prior art has room for further improvement in terms of increasing the pilot signal reception accuracy.

  The disclosed technique has been made in view of the above, and an object of the present invention is to provide a receiving apparatus capable of improving the reception accuracy of a pilot signal.

  The receiving device disclosed in the present application includes a Fourier transform unit and a noise removal unit. The Fourier transform unit performs a fast Fourier transform process on the orthogonal frequency division multiplexed signal. The noise removing unit performs noise removal using an averaging filter that performs averaging in the carrier direction on the pilot signal extracted from the orthogonal frequency division multiplexed signal after the fast Fourier transform processing.

  According to one aspect of the receiving device disclosed in the present application, it is possible to improve the reception accuracy of a pilot signal.

FIG. 1 is a block diagram illustrating the configuration of the receiving apparatus according to the first embodiment. FIG. 2 is a block diagram illustrating a configuration of the equalization processing unit. FIG. 3 is a block diagram illustrating a configuration of the first noise removing unit. FIG. 4A is an explanatory diagram illustrating an example of noise removal processing. FIG. 4B is an explanatory diagram illustrating an example of noise removal processing. FIG. 5 is an explanatory diagram illustrating an example of the weighting process. FIG. 6 is an explanatory diagram showing an example of the symbol direction averaging process. FIG. 7 is a block diagram illustrating a configuration of the second noise removing unit. FIG. 8A is a diagram illustrating an example of filter characteristics obtained by a conventional method. FIG. 8B is a diagram illustrating an example of filter characteristics obtained by applying a window function. FIG. 9 is a diagram illustrating an operation example of the carrier direction averaging filter included in the second noise removing unit. FIG. 10 is an explanatory diagram illustrating an example of a conventional tap coefficient update process. FIG. 11 is an explanatory diagram of an example of the tap coefficient update process according to the first embodiment. FIG. 12 is a diagram illustrating an example of a circuit configuration of the second noise removing unit. FIG. 13A is an explanatory diagram illustrating an example of a conventional tap coefficient initial value determination process. FIG. 13B is an explanatory diagram of an example of a tap coefficient initial value determination process according to the first embodiment. FIG. 14 is an explanatory diagram illustrating an example of the reset process. FIG. 15 is an explanatory diagram illustrating another example of the reset process. FIG. 16 is a block diagram illustrating another configuration of the first noise removing unit. FIG. 17A is an explanatory diagram illustrating an example of symbol interpolation processing. FIG. 17B is an explanatory diagram illustrating an example of symbol interpolation processing. FIG. 18 is a block diagram illustrating a configuration of an equalization processing unit according to the second embodiment. FIG. 19A is an explanatory diagram of an example of noise removal processing according to the second embodiment. FIG. 19B is an explanatory diagram of an example of noise removal processing according to the second embodiment. FIG. 19C is an explanatory diagram of an example of noise removal processing according to the second embodiment. FIG. 19D is an explanatory diagram of an example of noise removal processing according to the second embodiment. FIG. 20 is a block diagram showing another configuration of the receiving apparatus.

  Exemplary embodiments of a receiving device disclosed in the present application will be described below in detail with reference to the accompanying drawings. Below, although the example in case a receiver is mounted in moving bodies, such as a motor vehicle, is demonstrated, this invention is not limited by the illustration in these Examples.

  First, the configuration of the receiving apparatus according to the first embodiment will be described with reference to FIG. FIG. 1 is a block diagram illustrating the configuration of the receiving apparatus according to the first embodiment. In FIG. 1, constituent elements necessary for explaining the characteristics of the receiving device are shown, and descriptions of general constituent elements are omitted as appropriate.

  As illustrated in FIG. 1, the receiving device 1 according to the first embodiment includes a tuner unit 11, an FFT unit 12, an equalization processing unit 13, and a demodulation unit 14.

  The tuner unit 11 is a processing unit that detects and amplifies the reception signal input from the antenna 5. The tuner unit 11 also performs processing of converting the received signal after detection / amplification from an analog signal to a digital signal and outputting the digital signal to the FFT unit 12.

  The FFT unit 12 performs FFT (Fast Fourier Transform) processing on the orthogonal frequency division multiplexed signal (hereinafter referred to as “received signal”) input from the tuner unit 11, thereby processing the received signal in the time domain. It is a fast Fourier transform unit for converting a signal into a signal in the frequency domain. The FFT unit 12 also performs a process of outputting the received signal after the FFT process to the equalization processing unit 13.

  The equalization processing unit 13 estimates a transmission path response for each carrier of the reception signal input from the FFT unit 12, and corrects the reception signal input from the FFT unit 12 based on the estimated transmission path response. It is. The equalization processing unit 13 also performs processing for outputting the corrected received signal to the demodulation unit 14. A specific configuration of the equalization processing unit 13 will be described with reference to FIG.

  The demodulator 14 performs OFDM demodulation on the equalized reception signal input from the equalization processor 13 and outputs the demodulated signal to the output device 7. The output device 7 is, for example, a display device that displays digital television broadcast video, a speaker that outputs digital television broadcast audio, and the like.

  Next, the configuration of the equalization processing unit 13 will be described with reference to FIG. FIG. 2 is a block diagram illustrating a configuration of the equalization processing unit 13. In FIG. 2, constituent elements necessary for explaining the characteristics of the equalization processing unit 13 are shown, and descriptions of general constituent elements are omitted as appropriate.

  As shown in FIG. 2, the equalization processing unit 13 includes a first noise removal unit 31, an upsampling unit 32, a carrier interpolation unit 33, a first equalization unit 34, a temporary determination unit 35, and a temporary transmission. A road response estimation unit 36, a weighting unit 37, and a symbol direction averaging filter 38 are provided. The equalization processing unit 13 includes a second noise removal unit 39 and a second equalization unit 40.

  In FIG. 2, among the received signals input from the FFT unit 12, a scattered pilot signal that is a pilot signal (hereinafter referred to as “SP signal”) is indicated by “SP”, and a data signal is indicated by “data”. Is shown. As shown in FIG. 2, in the equalization processing unit 13, among the reception signals input from the FFT unit 12, the SP signal is sent to the first noise removal unit 31, and the data signal is sent to the first equalization unit 34, temporary transmission path Input to the response estimation unit 36 and the second equalization unit 40, respectively.

  The first noise removing unit 31 is a processing unit that removes a noise component included in the SP signal and outputs the SP signal after the noise removal to the upsampling unit 32. Here, the configuration of the first noise removing unit 31 will be described with reference to FIG. FIG. 3 is a block diagram illustrating a configuration of the first noise removing unit 31.

  The first noise removing unit 31 is an adaptive filter that self-adapts tap coefficients according to an optimization algorithm called an LMS (Least Mean Square) algorithm. Specifically, as shown in FIG. 3, the first noise removing unit 31 includes a carrier direction averaging filter 31a and an LMS unit 31b.

  The carrier direction averaging filter 31a is, for example, an FIR (Finite Impulse Response) filter, and performs a process of averaging the SP signal in the carrier direction using the tap coefficient input from the LMS unit 31b. The LMS unit 31b is a coefficient updating unit that updates the tap coefficient of the carrier direction averaging filter 31a according to the LMS algorithm. The first noise removal unit 31 performs noise removal of the SP signal using the carrier direction averaging filter 31a and the LMS unit 31b.

  Here, the content of the noise removal process which the 1st noise removal part 31 performs is demonstrated using FIG. 4A and 4B. 4A and 4B are explanatory diagrams illustrating an example of noise removal processing. Here, tap coefficient update processing will be described with reference to FIG. 4A, and SP signal averaging processing will be described with reference to FIG. 4B. 4A and 4B show an example where the number of taps is four, the number of taps of the carrier direction averaging filter 31a is not limited to four.

  For example, as shown in FIG. 4A, consider a case where the tap coefficient corresponding to the SP signal SP3 is updated. In such a case, in the first noise removing unit 31, first, the carrier direction averaging filter 31a includes four SP signals SP1, SP2, SP4, SP5 existing around the SP signal SP3, and the SP signals SP1, SP2, SP4. , The weighted average value using the tap coefficient W corresponding to SP5 is calculated.

  Subsequently, the LMS unit 31b updates the tap coefficients WA to WD based on the weighted average value calculated by the carrier direction averaging filter 31a (that is, the estimated value of the SP signal SP3) and the measured value of the SP signal. To do.

That is , the LMS unit 31b obtains an error between the estimated value of the SP signal and the actual measurement value, and updates the tap coefficient W so that the error is reduced. The updated tap coefficient W is output to the carrier direction averaging filter 31a. The first noise removing unit 31 updates the tap coefficient W corresponding to each SP signal by sequentially performing such processing along the carrier direction, in other words, along the frequency axis direction.

  Then, as shown in FIG. 4B, the carrier direction averaging filter 31a performs the above averaging process again using the updated tap coefficient W ′, and the up-sampling unit 32 (see FIG. 2). In this way, by performing the weighted average process using the peripheral SP signal, noise components such as AWGN (Additive White Gaussian Noise) having no correlation with the peripheral SP signal can be removed from the original SP signal. it can.

  As described above, in the receiving device 1 according to the first embodiment, the first noise removing unit 31 is used to remove noise from the SP signal. As a result, the receiving apparatus 1 according to the first embodiment can perform the subsequent process using the SP signal after noise removal with high accuracy.

  For example, conventionally, noise removal is performed on a temporary transmission path response estimated value calculated based on the result of the temporary determination process. That is, conventionally, a tap coefficient update process is performed using a temporary transmission path response estimated value calculated based on a result of the temporary determination process, and an averaging process is performed on the temporary transmission path response estimated value in the carrier direction. Had gone. However, if there is an error in the result of the provisional determination process, the provisional transmission line response estimation value also becomes inaccurate, and a correct tap coefficient cannot be obtained, which may reduce the estimation accuracy of the transmission line response.

  On the other hand, in the receiving apparatus 1 according to the first embodiment, noise removal processing is performed on a known SP signal before the temporary determination unit 35, specifically, before the upsampling unit 32. For this reason, it is possible to improve the estimation accuracy of the transmission path response and to demodulate received data with high reliability.

  Further, in the receiving apparatus 1 according to the first embodiment, the SP signal noise removal processing is performed before the carrier interpolation unit 33, so that the processing can be performed using the noise-removed SP signal, which will be described later. The calculation process of the transmission path response estimated value h1 by the carrier interpolation unit 33 can also be performed with high accuracy.

  Here, an example in which the SP signal is input to the first noise removing unit 31 in a state where the SP signal is preliminarily packed for each carrier has been described. However, the SP signal is a predetermined signal at a place where the data signal was present. The value may be input to the first noise removing unit 31 with a value (for example, zero) inserted. In such a case, the equalization processing unit 13 may perform a downsampling process that removes a value inserted between the SP signals in the previous stage of the first noise removal unit 31 and packs the SP signals for each carrier.

  The first noise removing unit 31 further increases symbol accuracy by increasing the SP signal inserted at a rate of 1 in 12 carriers, for example, at a rate of 1 in 3 carriers, in order to further improve the estimation accuracy of the transmission path response. It is good also as performing. This will be described later.

  Returning to FIG. 2, the description of the configuration of the equalization processing unit 13 will be continued. The SP signal from which noise has been removed by the first noise removing unit 31 is output to the upsampling unit 32.

  The upsampling unit 32 performs a process of returning the interval between the SP signals to the original interval by inserting zero between the SP signals. The SP signal after the upsampling is output to the carrier interpolation unit 33.

  The carrier interpolation unit 33 is, for example, a SINC filter, and estimates the distortion (that is, the transmission path response) of the received signal by performing a carrier interpolation process for interpolating the SP signals after upsampling smoothly. It is a processing unit. The channel response estimated value h1 obtained by the carrier interpolation unit 33 is input to the first equalization unit 34 and the weighting unit 37, respectively.

  In the receiving apparatus 1 according to the first embodiment, the noise removal process of the SP signal is performed before the carrier interpolation unit 33. For this reason, even if a SINC filter having a relatively wide band is used as the carrier interpolation unit 33, the noise component passing through the SINC filter is small, and the influence on the subsequent temporary determination processing and the like can be suppressed.

  The first equalization unit 34 is a processing unit that performs equalization processing for correcting distortion of the data signal using the transmission path response estimated value h1. The first equalizer 34 corrects the distortion of the data signal by dividing the data signal by the transmission path response estimated value h1. The data signal after the equalization process is input to the temporary determination unit 35.

  The temporary determination unit 35 is a processing unit that performs a temporary determination process for estimating a position on the IQ plane at the time of transmission of each data signal using the data signal after the equalization process. The data signal after the temporary determination process (hereinafter referred to as “temporary determination value”) is input to the temporary transmission path response estimation unit 36 and the weighting unit 37.

  The temporary transmission path response estimation unit 36 is the amount of distortion actually received from the position (provisional determination value) at the time of transmission of the data signal estimated by the temporary determination unit 35 and the position of the actually received data signal. Is a processing unit for estimating. The temporary transmission path response estimation unit 36 calculates a temporary transmission path response estimated value h2 by dividing the input data signal by the temporary determination value. The calculated temporary transmission path response estimated value h2 is input to the weighting unit 37.

  The weighting unit 37 is a processing unit that weights the temporary transmission line response estimation value h2 calculated by the temporary transmission line response estimation unit 36 according to the size of the temporary determination value. Here, the weighting process performed by the weighting unit 37 will be described with reference to FIG. FIG. 5 is an explanatory diagram illustrating an example of the weighting process.

  Assuming that the amount of noise is constant, the ratio of the noise component included in the data signal increases as the power of the data signal decreases. This point will be described using equations (1) to (3).

式（１）のようにあらわされる。 n is a carrier number, r (n) is a received signal, d (n) is a transmitted signal, n (n) is noise, H (n) is a transmission path response, and H ^ (n) is a temporary transmission path response estimate ( That is, assuming that h2), the received signal r (n) is

It is expressed as in equation (1).

式（２）のようにあらわされ、さらに、式（２）を仮伝送路応答推定値Ｈ＾（ｎ）について解くと、

式（３）のようにあらわされる。 Further, when equation (1) is solved for the transmission line response H (n),

It is expressed as equation (2), and further, when equation (2) is solved for the provisional transmission line response estimation value H ^ (n),

It is expressed as equation (3).

  As shown in Expression (3), an error between the actual transmission line response H (n) and the temporary transmission line response estimated value H ^ (n) is expressed by n (n) / d (n). From this, when the magnitude of the noise n (n) is the same, the provisional channel response estimated value H ^ (n as the transmission signal d (n) is smaller (that is, the data signal is smaller in power). ) Increases in error.

  Therefore, in the receiving apparatus 1 according to the first embodiment, the weight of the data signal with low power is set to be smaller than the weight of the data signal with high power.

式（４）のようにあらわされる。 Specifically, h _data is a temporary transmission path response estimated value calculated from a data signal (ie, temporary transmission path response estimated value h2), and h _SP is a transmission path response estimated value calculated from an SP signal (ie, transmission). If the path response estimated value h1) and d _data are assumed to be temporary determination values, the temporary transmission path response estimated value h3 after weighting processing is

It is expressed as equation (4).

That is, as shown in FIG. 5, when the temporary determination value is large (that is, when the power of the data signal is large), the weighting unit 37 increases the weight of the temporary transmission path response estimated value h _data and transmits the transmission value. to reduce the weight of the road-response estimate h _SP. On the other hand, heavy with section 37, if the temporary decision value is small (i.e., when the power of the data signal is small), the by increasing the weight of the transmission channel response estimation value h _SP, unreliable tentative transmission path The weight of the response estimated value h _data is reduced.

  As described above, the receiving apparatus 1 according to the first embodiment reestimates the provisional transmission line response by reducing the weight of the data signal with low power. As a result, the estimation accuracy of the transmission path response can be improved, and the received signal can be demodulated with high reliability.

  Here, an example in which the weighting unit 37 performs weighting processing on the temporary transmission channel response estimation value h2 calculated by the temporary transmission channel response estimation unit 36 has been described. The unit 36 may perform the weighting process and output the provisional transmission path response estimated value h3 after the weighting process.

  Returning to FIG. 2, the symbol direction averaging filter 38 will be described. The symbol direction averaging filter 38 is a processing unit that averages the temporary transmission path response estimated value h3 acquired from the weighting unit 37 in the symbol direction, in other words, in the time direction. The symbol direction averaging process by the symbol direction averaging filter 38 will be described with reference to FIG. FIG. 6 is an explanatory diagram showing an example of the symbol direction averaging process.

  As illustrated in FIG. 6, the temporary transmission path response estimated value h3 is output from the weighting unit 37 for each symbol. The symbol direction averaging filter 38 outputs, for example, a value obtained by averaging the temporary transmission path response estimated value h3 for 20 symbols to the second noise removing unit 39 as the temporary transmission path response estimated value h4. Specifically, assuming that the temporary transmission path response estimation value before symbol direction averaging processing is h3_n (n is a symbol number), the temporary transmission path response estimation value h4 after symbol direction averaging processing is h4 = (h3_1 + h3_2 +... h3_n) / n.

  Thus, in the receiving apparatus 1 according to the first embodiment, the symbol direction averaging filter 38 averages the temporary transmission path response estimated value h3 in the symbol direction and outputs the average value. As a result, noise components such as AWGN having no correlation between symbols can be reduced, and the estimation accuracy of the transmission path response can be increased.

  As the symbol direction averaging filter 38, for example, a digital filter such as a SINC filter can be used.

  The equalization processing unit 13 may change the time constant of the symbol direction averaging filter 38, that is, the number of symbols used for averaging, according to the amount of fluctuation of the temporary transmission path response estimated value h3. For example, the symbol direction averaging filter 38 increases the time constant when the fluctuation amount of the temporary transmission path response estimated value h3 is small, in other words, increases the number of symbols used for averaging. On the other hand, the symbol direction averaging filter 38 reduces the time constant when the fluctuation amount of the temporary transmission path response estimated value h3 is large, in other words, reduces the number of symbols used for averaging. As a result, the noise component can be more appropriately reduced by placing importance on the responsiveness when the fluctuation is severe, and placing importance on the stability when the fluctuation is moderate.

  For example, a fading frequency can be used as the fluctuation amount of the temporary transmission path response estimated value h3. That is, the equalization processing unit 13 changes the time constant of the symbol direction averaging filter 38 according to the fading frequency. In such a case, the equalization processing unit 13 may include a processing unit that estimates a fading frequency. Any known technique may be used for fading frequency estimation.

  Further, when considering a reduction in circuit scale, a symbol direction averaging filter in which the number of symbols used for averaging is fixed to a small number such as 3 symbols may be used.

  Returning to FIG. 2, the second noise removing unit 39 will be described. The second noise removal unit 39 removes a noise component included in the temporary transmission path response estimated value h4 after the symbol direction averaging process, and removes the temporary transmission path response estimated value h4 after noise removal (hereinafter referred to as a transmission path response estimated value). h5), which is output to the second equalization unit 40. Here, the configuration of the second noise removing unit 39 will be described with reference to FIG. FIG. 7 is a block diagram illustrating a configuration of the second noise removing unit 39.

  Similar to the first noise removing unit 31, the second noise removing unit 39 is an adaptive filter that self-adapts tap coefficients according to the LMS algorithm. Specifically, as shown in FIG. 7, the second noise removal unit 39 includes a window function application unit 39a, a carrier direction averaging filter 39b, an LMS unit 39c, and an initialization unit 39d.

  The window function applying unit 39a multiplies the temporary transmission path response estimated value h4 input from the symbol direction averaging filter 38 by the window function, and the multiplied temporary transmission path response estimated value h4 is the carrier direction averaging filter 39b. And a processing unit for outputting to the LMS unit 39c.

  The fast Fourier transform processing by the FFT unit 12 (see FIG. 1) originally requires an infinitely long signal sequence, but actually the processing is performed by cutting the signal sequence to an arbitrary finite length. Conventionally, when the tap coefficient is obtained, a spectrum due to the effect of such truncation appears, and the stop band (frequency band for blocking the input signal) has fluttered (see FIG. 8A). If such fluttering occurs, it may be difficult to detect a small signal.

  Therefore, the receiving apparatus 1 according to the first embodiment uses the window function application unit 39a to multiply the temporary transmission path response estimated value h4 by the window function. Thereby, the part cut off in the fast Fourier transform process is smoothed. As a result, as shown in FIG. 8B, the flutter of the stop band can be suppressed, and a small signal can be detected.

  As the window function used by the window function application unit 39a, various window functions such as a rectangular window function, a Hanning window function, a Hamming window function, and a Gauss window function can be used as appropriate. Note that the rectangular window function has a characteristic that the frequency resolution of the main component is high because the width of the main lobe is small, whereas the spectrum of low power is difficult to detect because the side lobe is large. The Hanning window function has a characteristic that the frequency resolution of the main component is slightly inferior, but the side lobe is relatively small, so that a low-power spectrum is easily detected.

  The Hamming window function is a modification of the Hanning window function that the signal components located at both ends of the window are not reflected in the spectrum. Like the Hanning window function, this Hamming window function has a characteristic that the frequency resolution of the main component is slightly inferior, but the side lobe is relatively small, so that a low-power spectrum is easily detected. In addition, the Gaussian window function has a characteristic that the frequency resolution of the main component is inferior, but it is excellent in detecting a low-power spectrum. The window function used in the window function application unit 39a may be determined in consideration of the characteristics of each window function and the spectrum to be detected.

  Returning to FIG. 7, the carrier direction averaging filter 39b will be described. The carrier direction averaging filter 39b is, for example, an FIR (Finite Impulse Response) filter, and performs a process of averaging the temporary transmission path response estimated value h4 in the carrier direction using the tap coefficient input from the LMS unit 39c.

  Here, when the FIR filter removes noise from the temporary transmission line response estimation value of a certain frequency, the noise is removed by performing averaging using the temporary transmission line response estimation value of the surrounding frequency. A temporary transmission path response estimated value is calculated. Therefore, at the end of the band (the carrier frequency range of the number of taps / 2), there are not enough temporary transmission path response estimation values used for averaging, and noise removal cannot be performed.

  Therefore, the carrier direction averaging filter 39b according to the first embodiment has a smaller number of taps than the FIR filter (first filter) used in a band other than the band edge (hereinafter referred to as “band central part”). The FIR filter (second filter) is used as a band edge FIR filter. This point will be described with reference to FIG. FIG. 9 is a diagram illustrating an operation example of the carrier direction averaging filter 39b.

  As shown in FIG. 9, the carrier direction averaging filter 39b includes two FIR filters, a band edge filter F1 and a band center filter F2. The number of taps of the band edge filter F1 (4 in FIG. 9) is smaller than the number of taps of the band center filter F2 (6 in FIG. 9).

  The carrier direction averaging filter 39b includes a band edge filter F1 and a band center filter F2, and performs carrier direction averaging processing in parallel using the band edge filter F1 and band center filter F2. To do. The carrier direction averaging filter 39b outputs the output value from the band edge filter F1 (temporary transmission line response after noise removal) while the band edge filter F1 and the band center filter F2 are processing the band edge. Estimate). When the band being processed moves from the band edge to the band center, the carrier direction averaging filter 39b switches the input and receives the output value from the band center filter F2. When the band being processed again moves to the band edge, the carrier direction averaging filter 39b switches the input again and receives the output value from the band edge filter F1.

  In this way, the carrier direction averaging filter 39b is for the band center part for averaging the channel response estimated values corresponding to the received signal in the band center part of the frequency band of the received signal (orthogonal frequency division multiplex signal). A filter F2 and a band edge filter F1 that has a smaller number of taps than the band center filter F2 and averages the channel response estimation value corresponding to the received signal at the band edge. Prepare.

  As a result, compared to the case where averaging is performed with the same number of taps over the entire band, it is possible to reduce the band where noise removal processing cannot be performed, and thus it is possible to improve the estimation accuracy of the temporary transmission path response. it can.

  Incidentally, here, an example in which the carrier direction averaging process using the band edge filter F1 and the carrier direction averaging process using the band center filter F2 are executed in parallel has been described. However, the present invention is not limited to this, and the carrier direction averaging filter 39b serially performs carrier direction averaging processing using the band edge filter F1 and carrier direction averaging processing using the band center filter F2. It may be executed. In such a case, the carrier direction averaging filter 39b may receive the band edge output value from the band edge filter F1 and the band center output value from the band center filter F2 afterwards.

  As described above, the carrier direction averaging filter 39b executes the averaging process using one of the band edge filter F1 and the band center filter F2, and then performs the averaging process using the other filter. May be executed. By doing so, the circuit scale of the carrier direction averaging filter 39b can be reduced. The carrier direction averaging filter 39b increases the processing speed compared to the case where the carrier direction averaging process is performed in parallel in order to realize the processing speed equivalent to the case where the carrier direction averaging process is performed in parallel. May be.

  Here, an example in which the carrier direction averaging filter 39b includes two FIR filters has been described, but the number of FIR filters may be two or more. That is, three or more types of FIR filters with different numbers of taps may be provided. In such a case, the number of taps of the FIR filter may be set smaller as it is closer to the end of the band.

  Returning to FIG. 7, the description of the configuration of the second noise removing unit 39 is continued. The LMS unit 39c is a coefficient updating unit that updates the tap coefficients of the carrier direction averaging filter 39b, specifically, the tap coefficients of the band edge filter F1 and the band center filter F2 according to the LMS algorithm.

  The LMS unit 39c receives the temporary transmission path response estimated value h4 input from the symbol direction averaging filter 38 and the temporary transmission path response estimated value input from the carrier direction averaging filter 39b (from the surrounding temporary transmission path response estimated values). An error with the estimated value) is obtained, and the tap coefficient is updated so that this error is reduced. For example, 5617 carriers are included in one symbol. The LMS unit 39c performs the above update processing for each carrier in order from the end of the band (that is, the tap coefficient is updated 5617 times), and finally updates the tap coefficient (the tap coefficient convergence value). The resulting tap coefficient is output to the carrier direction averaging filter 39b.

  Here, conventionally, when noise (colored noise) peculiar to a digital filter such as a SINC filter used in the preceding stage is generated, there is a possibility that an optimum tap coefficient cannot be obtained. This point will be described with reference to FIG. FIG. 10 is an explanatory diagram illustrating an example of a conventional tap coefficient update process.

  As shown in FIG. 10, conventionally, the noise component N that has passed through the previous SINC filter is gradually accumulated as the tap coefficient is repeatedly updated, and finally, the noise component N is finally stored in the previous SINC filter (for example, the carrier interpolation unit). There is a risk of convergence to a tap coefficient with a close characteristic. Thus, if the tap coefficient does not converge to an appropriate value, there is a risk that the estimation accuracy of the provisional transmission line response is lowered.

  Therefore, every time the tap coefficient is updated, the LMS unit 39c according to the first embodiment obtains the tap coefficient while performing correction to reduce the passing amount of the entire band, thereby preventing accumulation of noise components. This point will be described with reference to FIG. 11 and equations (5) to (9). FIG. 11 is an explanatory diagram of an example of the tap coefficient update process according to the first embodiment.

  As shown in FIG. 11, assuming that the accumulation amount of the signal component S in one update is v1, and the accumulation amount of the noise component N is v2, the LMS unit 39c is more than v2 and v1 for each update. By subtracting the smaller amount v3 from the entire band, accumulation of the noise component N is prevented. The tap coefficient update process will be described more specifically.

式（５）のようにあらわされる。 The tap coefficient number is n, the tap coefficient is W (n), the input signal (temporary transmission line response estimated value h4) is X (n), the step size is μ (0 <μ <1), and the error is e (n). Then, the updated tap coefficient W (n + 1) is

It is expressed as in equation (5).

式（６）のようにあらわされる。また、入力信号Ｘ（ｎ）は、

式（７）のようにあらわされる。また、誤差ｅ（ｎ）は、キャリア方向平均化フィルタ３９ｂからの入力値と、シンボル方向平均化フィルタ３８（図２参照）からの入力値（仮伝送路応答推定値ｈ４）との誤差であり、

式（８）のようにあらわされる。 It should be noted that the tap coefficient W (n)

It is expressed as in equation (6). The input signal X (n) is

It is expressed as in equation (7). The error e (n) is an error between the input value from the carrier direction averaging filter 39b and the input value from the symbol direction averaging filter 38 (see FIG. 2) (temporary transmission line response estimated value h4). ,

It is expressed as in equation (8).

  As shown in Expression (5), the LMS unit 39c multiplies the tap coefficient W (n) before update by a coefficient α (0 <α <1). That is, the LMS unit 39c regards (1−α) · W (n) as a noise component in the tap coefficient W (n) before the update, and performs correction to reduce the passing amount of the entire band by this amount. .

式（９）のようにあらわされる。このように、係数αは、ステップサイズμおよび誤差ｅ（ｎ）に依存する値である。なお、係数βは、たとえば、全成分Ｓ＋Ｎ中におけるノイズ成分Ｎの割合等に基づいてあらかじめ決定される値である。全成分Ｓ＋Ｎ中におけるノイズ成分Ｎの割合は、たとえばシミュレーションや実験等によって推定することができる。 Here, when the coefficient α is β, the predetermined coefficient is

It is expressed as in equation (9). Thus, the coefficient α is a value that depends on the step size μ and the error e (n). The coefficient β is a value determined in advance based on, for example, the ratio of the noise component N in the total component S + N. The ratio of the noise component N in all the components S + N can be estimated by simulation or experiment, for example.

  By using the coefficient α, the LMS unit 39c can subtract an amount v3 larger than the accumulated amount v2 of the noise component N and smaller than the accumulated amount v1 of the signal component S from the entire band (see FIG. 10). Accumulation of component N can be prevented.

  The receiving apparatus 1 according to the first embodiment includes the first noise removing unit 31 before the carrier interpolation unit 33 (for example, the SINC filter), and performs carrier interpolation processing using the SP signal from which the noise component has been removed. To do. As a result, the noise component passing through the carrier interpolation unit 33 can be reduced compared to the conventional case, and it is difficult for the carrier direction averaging filter 39b to converge to tap coefficients having characteristics close to those of the carrier interpolation unit 33. can do.

  Incidentally, the error e (n) tends to vary from carrier to carrier. For this reason, when the tap coefficient is updated, the time required for the tap coefficient to converge may become longer due to the variation in the error e (n).

  Therefore, the LMS unit 39c suppresses variations in the error e (n) by performing a moving average in the carrier direction (frequency axis direction) on the error e (n). Thereby, the time required for convergence of tap coefficients can be shortened.

  This point will be described with reference to FIG. FIG. 12 is a diagram illustrating an example of a circuit configuration of the second noise removing unit 39. Although FIG. 12 shows an example in which the number of taps of the carrier direction averaging filter 39b is four, the number of taps of the carrier direction averaging filter 39b is not limited to four. In FIG. 12, the configuration of a part of the second noise removal unit 39 such as the window function application unit 39a and the initialization unit 39d is omitted.

  As shown in FIG. 12, the carrier direction averaging filter 39b estimates a transmission path response of a certain frequency based on provisional transmission path response estimation values of four surrounding frequencies. For example, when the carrier direction averaging filter 39b estimates the transmission channel response of the carrier of the temporary transmission channel response estimation value h4_3, the temporary transmission channel response estimation values h4_1, h4_2, and h4_4 of four carriers located around the carrier. , H4_5 is multiplied by a tap coefficient W0 corresponding to each carrier, and values obtained thereby are added. As a result, a carrier channel response estimated value of the temporary channel response estimated value h4_3 is obtained.

  The LMS unit 39c includes a subtraction unit 39c_1, a moving average unit 39c_2, and an LMS execution unit 39c_3. The subtraction unit 39c_1 subtracts the error e by subtracting the transmission channel response estimation value obtained by the carrier direction averaging filter 39b from the temporary transmission channel response estimation value obtained by the symbol direction averaging filter 38 (see FIG. 2) for each carrier. (N) is calculated. The calculated error e (n) is input to the moving average unit 39c_2.

  The moving average unit 39c_2 performs a moving average process on the error e (n) input for each carrier from the subtracting unit 39c_1. For example, the moving average unit 39c_2 stores a predetermined number of errors e (n) input from the subtracting unit 39c_1, and when a new error e (n) is input, the stored error e (n ) And the average value of newly input error e (n). Here, although the simple moving average is performed as the moving average process, the moving average unit 39c_2 is not limited to the simple moving average, and may perform a weighted moving average, an exponential moving average, or the like.

  As described above, the moving average unit 39c_2 smoothes the error e (n) by performing a moving average in the carrier direction on the error e (n). The moving average unit 39c_2 outputs the error e (n) after the moving average process to the LMS execution unit 39c_3. Then, the LMS execution unit 39c_3 updates the tap coefficient according to the LMS algorithm using the error e (n) after the moving average process input from the moving average unit 39c_2. As described above, the second noise removal unit 39 can reduce the time required for the tap coefficient to converge by suppressing the fluctuation of the error e (n) using the moving average unit 39c_2. The estimation accuracy can be increased.

  Note that, as another method for suppressing the flutter of the error e (n), it is conceivable to reduce the step size μ. However, reducing the step size μ is not preferable because it takes a long time to converge the tap coefficients. In addition to multipath noise, noise that is peculiar to a certain frequency may occur in the received signal. However, the moving average of the error e (n) is performed as in the receiving apparatus 1 according to the first embodiment. If so, it is possible to suppress the influence of such specific noise.

  Incidentally, the moving average unit 39c_2 may fix the number of errors e (n) used in the moving average process, but may change the number of errors e (n) according to the frequency. For example, the moving average unit 39c_2 initially sets the number of errors e (n) used in the moving average process to be low so that the tap coefficient convergence is prioritized, and the moving average process is first performed as the frequency increases. The increase in the number of errors e (n) used in the above may be prioritized to suppress variation in the error e (n).

  The carrier direction averaging filter 39b re-executes the carrier direction averaging process using the updated tap coefficient input from the LMS unit 39c, and obtains the transmission path response estimated value h5 obtained thereby as the second etc. To the conversion unit 40. The updated tap coefficient is also output to the initialization unit 39d.

  The initialization unit 39d is a processing unit that performs initialization processing for initializing the coefficient of the carrier direction averaging filter 39b for each symbol, and outputs the initial value of the tap coefficient to the LMS unit 39c for each symbol.

  Here, the initialization unit 39d according to the first embodiment determines the initial value of the tap coefficient used in the current symbol based on the tap coefficient (convergence value) used in the past symbol. This point will be described with reference to FIGS. 13A and 13B. FIG. 13A is an explanatory diagram of a conventional tap coefficient initial value determining method, and FIG. 13B is an explanatory diagram illustrating an example of a tap coefficient initial value determining method according to the first embodiment.

  As shown in FIG. 13A, conventionally, a fixed value, specifically, the 1 / tap number is used as the initial value of the tap coefficient. For example, when the number of taps is 70, 1/70 is used as the initial value of the tap coefficient for each symbol.

  As described above, if a predetermined fixed value is used as the initial value and updating of the tap coefficient is started from this value, the amount of variation from the initial value to the convergence value is large, and it is necessary until the tap coefficient converges. Time can be long.

  The convergence value of the tap coefficient does not vary greatly from symbol to symbol. Therefore, as illustrated in FIG. 13B, the initialization unit 39d according to the first embodiment uses the convergence value of the tap coefficient in the previous symbol as the initial value of the current tap coefficient. Thereby, the fluctuation amount from the initial value to the convergence value can be reduced, and the time required for the tap coefficient to converge can be shortened. As a result, it is possible to prevent a situation in which the tap coefficient does not converge and an accurate provisional transmission line response estimation value cannot be calculated, so that the estimation accuracy of the transmission line response can be improved.

  Here, an example in which the initialization unit 39d uses the convergence value of the tap coefficient in the previous symbol as the initial value of the tap coefficient in the current symbol has been described. However, the present invention is not limited to this, and the initialization unit 39d holds, for example, the convergence values for a plurality of past symbols, and uses (for example, averages) the convergence values of the current tap coefficient. An initial value may be determined.

  Further, the initialization unit 39d may predict the convergence value of the current tap coefficient from the convergence values of a plurality of past symbols, and use the predicted convergence value as the initial value of the current tap coefficient. Thereby, the time required for the tap coefficient to converge can be further shortened.

  The initialization unit 39d may perform a reset process for returning the initial value of the tap coefficient to a predetermined value every time the initialization process is performed a predetermined number of times. By performing such a reset process, even if an error is accumulated in the initial value of the tap coefficient and changed to an inappropriate value, it is possible to return to the original state. As an initial value immediately after resetting, for example, the same 1 / tap number as in the prior art can be used. Hereinafter, such reset processing will be described with reference to FIG. FIG. 14 is an explanatory diagram illustrating an example of the reset process. In performing such processing, it is assumed that two configurations shown in FIG. 4A are provided.

  As illustrated in FIG. 14, the initialization unit 39d includes two processing systems (line A and line B) that execute the reset process at different timings, and the initialization process is performed in parallel using these lines A and B. Do.

  Here, the solid thick line shown in FIG. 14 is a period in which the initial value output from the processing system is used. 14 is a period during which the use of the initial value output from the processing system is prohibited (hereinafter referred to as “use prohibited period”). As shown in FIG. 14, a predetermined period after the reset process is set as a use prohibition period.

  That is, immediately after the reset process of the initial value of the tap coefficient, it may take a long time for the tap coefficient to converge as in the conventional case. For this reason, when the reset timing of the currently used line (for example, line A) approaches, the initialization unit 39d switches to another line (for example, line B) at a timing before the reset timing. .

  Similarly, when the reset timing of the currently used line B approaches, the initialization unit 39d performs switching to the line A at a timing before the reset timing. Thereby, use of the initial value of the tap coefficient immediately after resetting can be avoided.

  Although FIG. 14 illustrates an example in which the initialization unit 39d includes two processing systems, the initialization unit 39d may include three or more processing systems having different reset timings.

  Further, the second noise removal unit 39 may perform the reset process using only one processing system. Below, the example in the case of performing a reset process using one processing system is demonstrated using FIG. FIG. 15 is an explanatory diagram illustrating another example of the reset process.

  As shown in FIG. 15, for example, it is assumed that the processing period of the tap coefficient update process in the normal time is T. That is, the second noise removal unit 39 updates the tap coefficient at an update pace once every time T. On the other hand, immediately after the initial value of the tap coefficient is reset, the second noise removal unit 39 executes the tap coefficient update process a plurality of times within the time T by increasing the processing speed. Thereby, the second noise removal unit 39 can use the initial value in a state close to the convergence value in the next processing cycle.

  As described above, the LMS unit 39c increases the processing speed of the coefficient update process in a predetermined period after the reset process by the initialization unit 39d in comparison with a period other than the predetermined period, thereby reducing only one processing system. Can be used to perform the reset process. If the reset process is performed using only one processing system, an increase in circuit scale can be suppressed.

  Returning to FIG. 2, the second equalization unit 40 will be described. The second equalization unit 40 performs equalization processing for correcting the distortion of the data signal input from the FFT unit 12 (see FIG. 1) using the transmission path response estimated value h5 received from the second noise removal unit 39. It is a processing unit. The second equalization unit 40 corrects the distortion of the data signal by dividing the data signal by the transmission path response estimated value h5. The data signal after the equalization processing is input to the demodulator 14 (see FIG. 1).

  As described above, the receiving device 1 according to the first embodiment includes the FFT unit 12 and the first noise removing unit 31. The FFT unit 12 performs a fast Fourier transform process on the orthogonal frequency division multiplexed signal. Then, the first noise removing unit 31 performs noise removal using an averaging filter that performs averaging in the carrier direction on the SP signal extracted from the orthogonal frequency division multiplexed signal after the fast Fourier transform processing. . Therefore, according to the first embodiment, it is possible to improve the reception accuracy of the SP signal that is a pilot signal.

  In the first embodiment, the initialization unit 39d determines the initial value of the tap coefficient in the current symbol based on the convergence value of the tap coefficient obtained by the coefficient update process for the past symbol. Therefore, according to the first embodiment, it is possible to improve the estimation accuracy of the transmission path response.

  Further, in the first embodiment, the carrier direction averaging filter 39b averages the band center for averaging the channel response estimation value corresponding to the orthogonal frequency division multiplexed signal in the center of the band in the frequency band of the orthogonal frequency division multiplexed signal. The band edge for averaging the channel response estimation values corresponding to the orthogonal frequency division multiplex signal at the band edge having a smaller number of taps than the band filter F2 and the band center filter F2 Filter F1. Therefore, according to the first embodiment, it is possible to improve the estimation accuracy of the transmission path response.

  By the way, the SP signal is inserted into the received signal at a rate of, for example, one for every 12 carriers. The 1st noise removal part 31 is good also as improving the precision of the noise removal of SP signal by performing the symbol interpolation process which increases this SP signal artificially. Therefore, a modification of the first noise removing unit 31 will be described below.

  FIG. 16 is a block diagram illustrating another configuration of the first noise removing unit 31. As illustrated in FIG. 16, the first noise removing unit 31_1 further includes a symbol interpolation unit 31c in addition to the carrier direction averaging filter 31a and the LMS unit 31b.

  The symbol interpolation unit 31c is a processing unit that performs symbol interpolation processing on the SP signal input from the FFT unit 12 and outputs the processed SP signal to the carrier direction averaging filter 31a and the LMS unit 31b, respectively. Here, symbol interpolation processing executed by the symbol interpolation unit 31c will be described with reference to FIGS. 17A and 17B. 17A and 17B are explanatory diagrams illustrating an example of symbol interpolation processing.

  In FIG. 17A and FIG. 17B, “black circles” indicate SP signals, and “white circles” indicate data signals. 17A and 17B are assumed to be developed in the symbol direction (vertical axis in the figure) and the carrier direction (horizontal axis in the figure).

  As shown in FIG. 17A, when viewed in the symbol direction, the SP signal appears every four symbols. Here, the SP signal indicated by 51 in FIG. 17A and the data signal sandwiched between the SP signals indicated by 52 in FIG. 17 (see 53 in FIG. 17) are subject to interpolation processing using the SP signal 51 and SP signal 52. Become.

  A data signal corrected by symbol interpolation is indicated by “square” in FIG. 17B. For example, the three data signals 53 (see FIG. 17A) sandwiched between the SP signal 51 and the SP signal 52 are corrected by symbol interpolation to become a pseudo SP signal that can be used as a pseudo SP signal. (See FIG. 17B). Similarly, symbol direction interpolation processing is performed for the carrier direction, and all pseudo SP signals are generated as shown in FIG. 17B.

  Thus, the first noise removal unit 31_1 uses the symbol interpolation unit 31c to increase the SP signal in a pseudo manner. Thereby, since noise removal processing can be performed using more SP signals than when symbol interpolation processing is not performed, the accuracy of noise removal can be improved.

  In the first embodiment described above, an example in which the noise removal of the SP signal is performed using the first noise removal unit 31 has been described, but the noise removal method of the SP signal is not limited to this. Thus, in the second embodiment, another example of the SP signal noise removal method will be described. FIG. 18 is a block diagram illustrating a configuration of an equalization processing unit according to the second embodiment.

  As illustrated in FIG. 18, the equalization processing unit 13 ′ according to the second embodiment includes an IFFT unit 41, a carrier interpolation unit 42, instead of the first noise removal unit 31, the upsampling unit 32, and the carrier interpolation unit 33. , And an FFT unit 43. Other configurations are the same as those of the equalization processing unit 13 according to the first embodiment, and a description thereof is omitted here.

  The IFFT unit 41 is a processing unit that converts the SP signal from the signal in the frequency domain to the signal in the time domain by performing an IFFT (Inverse Fast Fourier Transform) process on the SP signal input from the FFT unit 12. is there. Thus, in the second embodiment, the SP signal converted into the frequency domain by the FFT unit 12 is converted again into a signal in the time domain by the IFFT unit 41. The SP signal converted into the signal in the time domain is output to the carrier interpolation unit 42.

  The carrier interpolation unit 42 is a processing unit that performs carrier interpolation processing using an adaptive time window method on the SP signal converted into a signal in the time domain by the IFFT unit 41. The SP signal carrier-interpolated by the carrier interpolation unit 42 is output to the FFT unit 43, and is again converted from a signal in the time domain to a signal in the frequency domain by the FFT unit 43.

  Here, the contents of the SP signal noise removal processing performed by the IFFT unit 41, the carrier interpolation unit 42, and the FFT unit 43 will be described with reference to FIGS. 19A to 19D. 19A to 19D are explanatory diagrams illustrating an example of the noise removal process according to the second embodiment.

  The IFFT unit 41 converts the SP signal in the frequency domain (see FIG. 19A) into a signal in the time domain by performing IFFT processing (see FIG. 19B). As shown in FIGS. 19A and 19B, a noise component is superimposed on the SP signal.

  The carrier interpolation unit 42 detects a signal equal to or higher than a predetermined threshold among the SP signals converted into signals in the time domain. Here, a value larger than the value of the noise component included in the SP signal is set as the predetermined threshold. Subsequently, the carrier interpolation unit 42 applies a time window to the periphery of the signal detected by the threshold processing, that is, cuts out a signal (data string) within a predetermined period including the detected signal. Thereby, as shown in FIG. 19C, most of the noise components are removed.

  Then, the FFT unit 43 converts the SP signal from which the noise component has been removed by the carrier interpolation unit 42 into a signal in the frequency domain again by FFT processing. As a result, as shown in FIG. 19D, an SP signal from which noise components have been removed can be obtained.

  As described above, in the second embodiment, the IFFT unit 41 converts the SP signal converted into the frequency domain by the FFT unit 12 into a signal in the time domain, and the carrier interpolation unit 42 is converted into a signal in the time domain. The SP signal is subjected to noise removal by an adaptive time window method. Then, the FFT unit 43 converts the SP signal from which noise has been removed by the carrier interpolation unit 42 into a signal in the frequency domain again. Therefore, according to the second embodiment, it is possible to improve the reception accuracy of the pilot signal.

  Next, a modification of the receiving device will be described. FIG. 20 is a block diagram showing another configuration of the receiving apparatus. 20 has a branch corresponding to each of the plurality of antennas 5_1 to 5_4, the data signal after the equalization processing output from each equalization processing unit 13_1 to 13_4 is used as the maximum ratio combining unit. 15 for synthesis.

  As illustrated in FIG. 20, the receiving device 1 ′ includes a first branch including an antenna 5_1, a tuner unit 11_1, an FFT unit 12_1, and an equalization processing unit 13_1. , A third branch, and a fourth branch.

  Each equalization processing unit 13-1 to 13-4 outputs the data signal after the equalization processing to the maximum ratio combining unit 15. The maximum ratio combining unit 15 performs a process of combining the received signals from the respective branches with a maximum ratio, and outputs the data signal after the maximum ratio combining process to the selecting unit 16.

  Here, the maximum ratio combining unit 15 performs the maximum ratio combining process on both the data signal after the equalization process by the first equalization unit 34 and the data signal after the equalization process by the second equalization unit 40, respectively. The result of the maximum ratio combining process for both is output to the selection unit 16. Then, the selection unit 16 selects one of the data signals after the maximum ratio combining process received from the maximum ratio combining unit 15 and outputs the selected data signal to the demodulation unit 14. The data signal selected by the selection unit 16 is determined by a user operation or the like.

  As described above, the receiving device 1 ′ uses the data signal after the equalization processing by the first equalization unit 34 as well as the data signal of the equalization processing by the second equalization unit 40 to perform the demodulation processing by the demodulation unit 14. Can also be done. That is, each equalization processing unit 13_1 to 13_4 performs the SP signal noise interpolation processing by the first noise removal unit 31 before the first equalization unit 34. For this reason, even if processing subsequent to the first equalization unit 34 is omitted, it is possible to perform equalization processing with relatively high accuracy.

  Note that, if it is desired to reduce the circuit scale of the equalization processing units 13_1 to 13_4, a processing unit subsequent to the first equalization unit 34 may be omitted.

  Further, in the embodiment described above, an example in which the data signal after the equalization processing by the first equalization unit 34 is output to the temporary determination unit 35 has been described. On the other hand, the receiving apparatus 1 ′ performs the maximum ratio combining process on the data signal after the equalization processing by the first equalization unit 34 using the maximum ratio combining unit 15, and then the data signal of the maximum ratio combining process. Is output to the provisional determination unit 35. That is, the temporary determination unit 35 performs the temporary determination process using the data signal after the maximum ratio combining process. Thereby, each equalization process part 13_1-13_4 can perform the temporary determination by the temporary determination part 35, the equalization process by the 2nd equalization part 40, etc. more accurately.

  The maximum ratio combining unit 15 may combine the data signals from the respective branches based on the gains of the respective branches, or may be selected after selecting a predetermined number of branches from the larger gain. It is also possible to synthesize data signals related to the branches. Furthermore, the data signal related to the branch having the best reception condition may be used as it is.

  Further effects and modifications can be easily derived by those skilled in the art. Thus, the broader aspects of the present invention are not limited to the specific details and representative embodiments shown and described above. Accordingly, various modifications can be made without departing from the spirit or scope of the general inventive concept as defined by the appended claims and their equivalents.

  As described above, the receiving device disclosed in the present application is effective when it is desired to increase the reception accuracy of the pilot signal, and in particular, application to an in-vehicle receiving device can be considered.

1, 1 'receiver 11 tuner unit 12 FFT unit 13, 13' equalization processing unit 31 first noise removal unit 31a carrier direction averaging filter 31b LMS unit 31c symbol interpolation unit 32 upsampling unit 33 carrier interpolation unit 34 first Equalization unit 35 Temporary determination unit 36 Temporary transmission path response estimation unit 37 Weighting unit 38 Symbol direction averaging filter 39 Second noise removal unit 39a Window function application unit 39b Carrier direction averaging filter 39c LMS unit 39c_1 Subtraction unit 39c_2 Moving average Unit 39c_3 LMS execution unit 39d initialization unit 40 second equalization unit 41 IFFT unit 42 carrier interpolation unit 43 FFT unit 14 demodulation unit 15 maximum ratio combining unit 16 selection unit

Claims (6)

A Fourier transform unit for performing a fast Fourier transform process on an orthogonal frequency division multiplexed signal;
Among the plurality of pilot signals extracted from the orthogonal frequency division multiplexed signal after the fast Fourier transform processing, taps respectively corresponding to pilot signals existing on both sides in the carrier frequency direction across the pilot signal to be averaged A noise removal unit that performs noise removal using an averaging filter that performs averaging in a carrier direction on the pilot signal to be averaged by multiplying a coefficient and adding the multiplication results. Receiving device. The noise removing unit
The receiving apparatus according to claim 1, further comprising: a coefficient updating unit configured to update the tap coefficient of the averaging filter according to a predetermined optimization algorithm. The coefficient updating unit
The receiving apparatus according to claim 2, wherein the tap coefficient of the averaging filter is updated based on an error between a result of the addition processing output from the averaging filter and an actual measurement value of the pilot signal. . The coefficient updating unit
The receiving apparatus according to claim 2, wherein an LMS algorithm is used as the optimization algorithm. A channel response estimation unit that estimates a channel response using the pilot signal denoised by the noise removal unit;
The equalizer according to claim 1, further comprising: an equalizer that corrects distortion of the orthogonal frequency division multiplex signal using the channel response estimated by the channel response estimation unit. The receiving device described. A symbol interpolation unit that artificially increases the pilot signal included in each symbol by performing interpolation processing in the symbol direction on the pilot signal;
The noise removing unit
The receiving apparatus according to claim 1, wherein the noise removal is performed on a pilot signal after interpolation processing by the symbol interpolation unit.

Images