Frequency domain super-resolution reconstruction OFDM waveform distortion suppression method

Abstract

The invention discloses a frequency domain super-resolution reconstruction OFDM (Orthogonal Frequency Division Multiplexing) waveform distortion suppression method, and belongs to the field of wireless communication. The method solves the problems that an existing method is high in complexity, sensitive to channel conditions and poor in error rate performance. The method comprises the following steps: constructing an interpolation matrix at a receiving end, and carrying out weighted interpolation on a frequency domain receiving signal by utilizing adjacent spectral line weighting to generate an interpolated frequency domain signal; the method comprises the following steps of: deducing to obtain a time domain equivalent relation of interpolation processing of a transmitting end and a receiving end by combining the logic of performing frequency domain zero insertion on an original frequency domain signal by a transmitting end, further jointly estimating an interpolated channel, and designing an equalizer according to a minimum mean square error criterion to perform equalization processing on the interpolated frequency domain signal to complete data recovery. According to the method, the problem of inter-symbol interference caused by insufficient CP of a common OFDM system with insufficient cyclic prefixes is solved, inter-symbol interference and inter-subcarrier interference caused by insufficient cyclic prefixes can be effectively suppressed, and accurate demodulation data can be obtained. The method can be applied to the field of wireless communication.

Description

Technical Field

[0001] This invention belongs to the field of wireless communication, and specifically relates to a method for suppressing waveform distortion in frequency domain super-resolution reconstructed OFDM. Background Technology

[0002] Driven by both the deepening commercialization of 5G and the surge in IoT terminals, the imbalance between the supply and demand of spectrum resources has evolved into a core bottleneck restricting the development of wireless communication. 4G systems widely use Orthogonal Frequency Division Multiplexing (OFDM) technology and employ a Cyclic Prefix (CP) to combat inter-symbol interference (ISI) and inter-subcarrier interference (ICI) caused by multipath fading. While the CP plays an irreplaceable role in combating multipath fading, the introduced spectrum overhead leads to a reduction in system spectral efficiency, which is inconsistent with the goals pursued in the development of communication systems. This has prompted OFDM technology research to shift towards using shorter CPs to suppress distortion.

[0003] Research on short CP reconstructed signals mainly falls into the following categories: 1. Zero-padding the received signal followed by decimation at intervals allows the receiver to perform frequency domain equalization to eliminate ISI; 2. Iterative elimination methods reconstruct interference using the frequency domain signal of the previous frame, as well as the interference of the current frame signal on the next frame; 3. CP recovery algorithms based on band-limited signal extrapolation. Furthermore, although several CP-free transmission algorithms exist, current short CP and CP-free transmission algorithms still suffer from high complexity, sensitivity to channel conditions, and poor bit error rate performance. Summary of the Invention

[0004] The purpose of this invention is to address the problems of high complexity, sensitivity to channel conditions, and poor bit error rate performance of existing methods, and to propose a frequency domain super-resolution reconstructed OFDM waveform distortion suppression method.

[0005] The technical solution adopted by the present invention to solve the above-mentioned technical problems is: a method for suppressing waveform distortion in frequency domain super-resolution reconstruction OFDM, the method specifically including the following steps:

[0006] At the launch end

[0007] Step A1: Digitally modulate the bit data generated by the digital source to obtain a serial modulated symbol stream;

[0008] Step A2: The modulation symbols in the modulation symbol stream are grouped, and each group includes... One modulation symbol;

[0009] Step A3: Construct the frequency domain signal vector corresponding to each group of modulation symbols in step A2;

[0010] Step A4: The frequency domain signal vectors corresponding to each group of modulation symbols are subjected to Inverse Fast Fourier Transform (IFFT), and then the IFFT results corresponding to each group of modulation symbols are converted from parallel to serial to obtain the time domain signal vectors. ;

[0011] Step A5: Assign time-domain signal vector Adding a cyclic prefix yields the time-domain signal after adding the cyclic prefix. ;

[0012] Step A6: For the time-domain signal after adding the cyclic prefix The digital-to-analog conversion and up-conversion processes are performed sequentially, and the processed signal is sent to the channel.

[0013] At the receiving end

[0014] Step B1: After the signal reaches the receiver via the wireless channel, the received signal undergoes down-conversion and analog-to-digital conversion to obtain a discrete time-domain signal. ;

[0015] Step B2, for the time domain signal After synchronization, the cyclic prefix before the time-domain signal is removed to obtain the data after removing the cyclic prefix. ;

[0016] Step B3: Perform serial-to-parallel conversion on the data after removing the cyclic prefix, and then perform Fast Fourier Transform (FFT) on each group of data obtained from the serial-to-parallel conversion to obtain the frequency domain received signal vector corresponding to each group of data. The length of the frequency domain received signal vector corresponding to each group of data is 1. ;

[0017] Step B4: Extract the original data from each frequency domain received signal vector, and then send the extracted data to the OFDM receiver for decision-making;

[0018] The extraction of raw data from each frequency domain received signal vector specifically involves:

[0019] Step B41: For any frequency domain received signal vector For the frequency domain received signal vector Perform frequency domain weighted interpolation to obtain the frequency domain weighted interpolated signal vector. ;

[0020] Step B42: Weighted interpolation of the signal in the frequency domain Perform IDFT to obtain OFDM time-domain waveform signal of a point For OFDM time-domain signals Perform MMSE equalization to obtain OFDM time-domain signal after point equalization ;

[0021] Step B43: Equalize the OFDM time-domain signal Perform a Fourier transform to obtain OFDM frequency domain signal after point equalization ;

[0022] Step B44: Equalize the OFDM frequency domain signal Extraction is performed to obtain OFDM frequency domain signal after point equalization Then from the OFDM frequency domain signal Extract the original data portion;

[0023] Step B45: Process each frequency domain received signal vector using the methods from steps B41 to B44.

[0024] The beneficial effects of this invention are:

[0025] This invention constructs an interpolation matrix at the receiver and performs weighted interpolation on the received frequency domain signal using adjacent spectral lines to generate an interpolated frequency domain signal. Combining this with the logic of zero-placing the original frequency domain data signal at the transmitter, the time-domain equivalence relationship of the interpolation processing at the transmitter and receiver is derived. The interpolated channel is then jointly estimated. Subsequently, an equalizer is designed based on the minimum mean square error criterion to equalize the interpolated frequency domain signal, completing data recovery. Compared to existing short cyclic prefix OFDM systems, this invention can effectively suppress inter-symbol interference and inter-subcarrier interference caused by insufficient cyclic prefixes, enabling the acquisition of accurate demodulated data. Although this invention retains the short cyclic prefix at the transmitter, the frequency domain interpolation and joint equalization at the receiver result in a significant optimization effect compared to existing short cyclic prefix OFDM systems. This improves bit error rate performance while reducing the system's sensitivity to channel variations and system complexity.

[0026] The method of this invention does not require an additional increase in the length of the cyclic prefix, thus avoiding the waste of spectrum resources caused by extending the cyclic prefix and improving spectrum utilization efficiency. At the same time, through collaborative processing at the receiving end, it ensures communication quality and effectively balances system performance and resource utilization. Attached Figure Description

[0027] Figure 1 This is a flowchart of a frequency domain super-resolution reconstructed OFDM waveform distortion suppression method according to the present invention;

[0028] Figure 2 This is a flowchart of frequency domain interpolation and joint equalization at the receiver.

[0029] Figure 3 This is a comparison of the bit rate performance of direct MMSE equalization and the frequency domain interpolation-based MMSE equalization method of this invention under Rayleigh fading channel, 16QAM modulation, and a maximum Doppler frequency shift of 300Hz.

[0030] Figure 4 This is a comparison of the bit rate performance of direct MMSE equalization and the frequency domain interpolation-based MMSE equalization method of this invention under Rayleigh fading channel, 16QAM modulation, and a maximum Doppler frequency shift of 3000Hz. Detailed Implementation

[0031] Specific implementation method one: Combining Figure 1 This embodiment describes a frequency domain super-resolution reconstructed OFDM waveform distortion suppression method, which specifically includes the following steps:

[0032] At the launch end

[0033] Step A1: Digitally modulate the bit data generated by the digital source to obtain a serial modulated symbol stream;

[0034] It should be noted that in step A1, every several consecutive binary bits are mapped to a modulation symbol, and the sequence of all the modulation symbols obtained is the serial modulation symbol stream.

[0035] Step A2: Perform grouping processing on the modulation symbols in the modulation symbol stream. In the grouping processing result, each group includes... One modulation symbol;

[0036] The first modulation symbol to the second modulation symbol in the modulation symbol stream The modulation symbols are grouped into groups, and the first modulation symbol in the modulation symbol stream is divided into groups. +1 modulation symbol to the 2nd Each modulation symbol is grouped into a subcarrier, and so on. Each modulation symbol occupies one subcarrier, so each group of data requires 1 carrier. Subcarriers;

[0037] Step A3: Construct the frequency domain signal vector corresponding to each group of modulation symbols in step A2;

[0038] Step A4: The frequency domain signal vectors corresponding to each group of modulation symbols undergo inverse fast Fourier transform (IFFT) respectively. Then, the IFFT results for each group of modulation symbols are converted from parallel to serial to obtain the time domain signal vectors. ;

[0039] Step A5: Assign time-domain signal vector Adding a cyclic prefix yields the time-domain signal after adding the cyclic prefix. ;

[0040] Step A6: For the time-domain signal after adding the cyclic prefix The digital-to-analog conversion and up-conversion processes are performed sequentially, and the processed signal is sent to the channel.

[0041] At the receiving end

[0042] Step B1: After the signal reaches the receiver via the wireless channel, the received signal undergoes down-conversion and analog-to-digital conversion to obtain a discrete time-domain signal. ;

[0043] Step B2, for the time domain signal After synchronization, the cyclic prefix before the time-domain signal is removed to obtain the data after removing the cyclic prefix. ;

[0044] Step B3: Perform serial-to-parallel conversion on the data after removing the cyclic prefix, and then perform Fast Fourier Transform on each group of data obtained from the serial-to-parallel conversion to transform the signal from the time domain to the frequency domain, obtaining the frequency domain received signal vector corresponding to each group of data, and the length of the frequency domain received signal vector corresponding to each group of data is 1. ;

[0045] Step B4: Extract the original data from each frequency domain received signal vector, and then send the extracted data to the OFDM receiver for decision-making;

[0046] The extraction of raw data from each frequency domain received signal vector specifically involves:

[0047] Step B41: For any frequency domain received signal vector For the frequency domain received signal vector Perform frequency domain weighted interpolation to obtain the frequency domain weighted interpolated signal vector. ;

[0048] Step B42: Weighted interpolation of the signal in the frequency domain Performing the IDFT (Inverse Discrete Fourier Transform) yields... OFDM time-domain waveform signal of a point For OFDM time-domain signals Perform MMSE equalization to obtain OFDM time-domain signal after point equalization ;

[0049] Step B43: Equalize the OFDM time-domain signal Perform a Fourier transform to obtain OFDM frequency domain signal after point equalization ;

[0050] Step B44: Equalize the OFDM frequency domain signal Extraction is performed to obtain OFDM frequency domain signal after point equalization Then from the OFDM frequency domain signal Extract the original data portion;

[0051] Step B45: Process each frequency domain received signal vector using the methods from steps B41 to B44.

[0052] Specific Implementation Method Two: This implementation method differs from Specific Implementation Method One in that the specific process of step A3 is as follows:

[0053] For any set of modulation symbols, zero-padding is applied to both the leading and trailing zeros of the set. The resulting zero-padding is used as the frequency domain signal vector corresponding to that set of modulation symbols. The length of the frequency domain signal vector is... .

[0054] The other steps and parameters are the same as in Specific Implementation Method 1.

[0055] Specific Implementation Method Three: This implementation method differs from Specific Implementation Method One or Two in that the zero-padding lengths for leading and trailing zeros are respectively:

[0056] like If the number is even, then the length of the leading zero and the length of the trailing zero are both 1. ;

[0057] like If the number is odd, then the length of the leading zeros is... The length of the zero padding is .

[0058] Other steps and parameters are the same as in specific implementation method one or two.

[0059] Specific Implementation Method Four: This implementation method differs from Specific Implementation Methods One to Three in that the specific process of step A5 is as follows:

[0060] Copy the signal vector in the time domain The length of the end is The symbol sequence is then copied and added to the time-domain signal vector. At the beginning position, the time-domain signal after adding the cyclic prefix is ​​obtained. .

[0061] The other steps and parameters are the same as those in one of the specific implementation methods one to three.

[0062] Specific Implementation Method Five: This implementation method differs from Specific Implementation Methods One to Four in that the specific process of step B41 is as follows:

[0063] Construction dimension Receiver frequency domain interpolation matrix , matrix The Middle Line number Set the value of each element in the column to 1, and set the value of the first element to 1. Line number Set the values ​​of the column elements to coefficients. The first Line number Set the values ​​of the column elements to coefficients. All other elements are set to 0;

[0064] Using matrices For the frequency domain received signal vector Perform a linear transformation, that is, a matrix With frequency domain received signal vector Perform multiplication operations and use the result of the multiplication operations as the interpolated signal vector. .

[0065] The other steps and parameters are the same as those in one of the specific implementation methods one to four.

[0066] The following is combined Figure 2 Explain the specific process of frequency domain weighted interpolation in step B41:

[0067] Assume the frequency domain received signal vector is The interpolated frequency domain signal vector is According to the matrix With frequency domain received signal vector The result of the multiplication operation shows that the frequency domain received signal vector The first in Each sample point is directly placed in the output vector. The One location;

[0068] Received signal vector in the frequency domain The sample points With frequency domain received signal vector The sample points Insert a new sample point between the two points, and the value of the inserted sample point is... and The weighted sum, with weight coefficients respectively and This new sample point is placed in the output vector. The At each position, that is:

[0069]

[0070] Received signal vector in the frequency domain The last sample point Then, a new sample point is inserted, and the value of this new sample point is determined solely by... Sum of coefficients Decide, .

[0071] Specific Implementation Method Six: This implementation method differs from Specific Implementation Methods One through Five in that the coefficients... The value range of is from -1 to 1, and the coefficient It is a function of maximum multipath delay spread and maximum Doppler shift, with coefficients... Specifically:

[0072] in, , Indicates the maximum multipath delay spread. , Indicates the maximum Doppler frequency shift. , All are polynomial coefficients.

[0073] The other steps and parameters are the same as those in one of the specific implementation methods one to five.

[0074] Specific Implementation Method Seven: This implementation method differs from Specific Implementation Methods One through Six in that the coefficients... The value range of is from -1 to 1, and the coefficient It is a function of maximum multipath delay spread and maximum Doppler shift, with coefficients... Specifically: in, All are polynomial coefficients.

[0075] The other steps and parameters are the same as those in one of the specific implementation methods one to six.

[0076] In this invention, the coefficients of each polynomial are all in the range of -50 to 50.

[0077] Specific implementation method eight: Combination Figure 2 This embodiment is described below. The difference between this embodiment and any one of specific embodiments one through seven is that, in step B42, the OFDM time-domain signal... The specific process of performing MMSE equalization is as follows:

[0078] Step B421, constructing the dimension as Transmitter frequency domain transformation matrix , matrix The Middle Line number Set the elements of the column to 1, and set all other elements to 0;

[0079] Step B422: Calculate the frequency domain transformation matrix of the transmitter. Equivalent form in the time domain and the receiver frequency domain interpolation matrix Equivalent form in the time domain :

[0080]

[0081]

[0082] in, The dimension is The inverse fast Fourier transform matrix, matrix The Middle Line number Column elements , ; The dimension is The fast Fourier transform matrix, matrix The Middle Line number Column elements , , The base of the natural logarithm. Represents the imaginary unit;

[0083] Step B423, based on and The construction dimension is Interpolated equivalent channel matrix :

[0084]

[0085] in, The dimension is The channel matrix, where the superscript -1 represents the inverse of the matrix;

[0086] Step B424: Based on the interpolated equivalent channel matrix Perform MMSE equalization to obtain the dimension as Equalizer coefficient matrix :

[0087]

[0088] in, Indicates the average power of the signal. Indicates the average noise power. Represents the identity matrix. express The conjugate transpose of;

[0089] Step B425: Convert the OFDM time-domain waveform signal With equalizer coefficient matrix Multiply, we get OFDM time-domain signal after point equalization .

[0090] The other steps and parameters are the same as those in any of the specific implementation methods one to seven.

[0091] This invention assumes that the channel the signal traverses is a Rayleigh fading channel, and the impulse response of the Rayleigh fading channel... for:

[0092]

[0093] Where L is the multipath number, It is the first The complex gain of each path follows a Rayleigh distribution; This is the Doppler frequency shift, used to simulate the frequency shift caused by the relative motion between the transmitting and receiving ends, and the maximum Doppler frequency shift is... It is a random variable The maximum value; It is the first The delay of each path, from 0 to the maximum multipath delay spread. Linear distribution within the range; It is the Dirac function, where t is time;

[0094] Yes The discrete-time impulse response of the described channel. It is a complex vector of length L, whose elements represent the complex gain of each path at discrete time points;

[0095] Based on the obtained discrete-time channel impulse response Channel matrix can be constructed The channel matrix enables vector multiplication. The result is mathematically equivalent to the effective data portion of the transmitted signal. Channel impulse response The linear convolution; since the scenario addressed by this invention is one of insufficient cyclic prefix and channel non-cyclic stationarity, therefore the matrix It is a non-cyclic Topulitz matrix.

[0096] It should be noted that even if the channel state is unknown, channel estimation can be achieved by inserting pilot signals into the transmitted signal. Therefore, the method of the present invention is still applicable when the channel state is unknown.

[0097] Specific Implementation Method Nine: This implementation method differs from Specific Implementation Methods One through Eight in that the equalized OFDM frequency domain signal... Extraction is performed specifically by extracting the equalized OFDM frequency domain signal. The odd points in the sample are used to form the equalized OFDM frequency domain signal. (The odd-numbered points to be extracted will be arranged according to...) Simply sort them according to their order.

[0098] The other steps and parameters are the same as those in one of the specific implementation methods one to eight.

[0099] Specific Implementation Method Ten: This implementation method differs from Specific Implementation Methods One to Nine in that the OFDM frequency domain signal... The original data portion was extracted, specifically as follows:

[0100] like Since the number is even, the length of the leading zeros and the length of the trailing zeros in each data set are both... Then from the equalized OFDM frequency domain signal The first in Starting from a point, extract continuously Points, will be extracted These points serve as the raw data for extraction;

[0101] like Since the number is odd, the length of the leading zeros in each data set is... The length of the trailing zeros in each data set is 1. Then from the equalized OFDM frequency domain signal The Starting from a point, extract continuously Points, will be extracted These points serve as the raw data extracted.

[0102] The other steps and parameters are the same as those in any of the specific implementation methods one to nine.

[0103] Simulation section

[0104] The simulation parameter settings for this invention are shown in Table 1:

[0105]

[0106] The transmitting end first generates a random binary bit stream to be transmitted and maps the data bits. The modulation method is selected based on the amount of data to be transmitted; in the simulation, 16QAM digital signal modulation is chosen. Then, the modulation result undergoes serial-to-parallel conversion, converting the serial data into 192 parallel data subcarriers. Due to the large number of subcarriers, OFDM modulation is performed using IFFT (Inverse Fast Fourier Transform) to generate an OFDM signal. The last 32 subcarriers are then extracted and added to the signal front-end as a cyclic prefix. Finally, the parallel data is converted back to serial data, then converted from digital to analog, and the signal is transmitted through the transmitting antenna.

[0107] A Rayleigh fading channel model based on Gaussian white noise and the Doppler effect was established to simulate the noise interference, phase shift, and signal attenuation processes of OFDM signals as they pass through the channel environment. The simulation signal-to-noise ratio (SNR) was set to 0–20 dB, and the simulation was run 1000 times under each SNR condition.

[0108] After removing the cyclic prefix at the receiving end, frequency domain interpolation is performed on the OFDM signal, and the expression for the calculated interpolation coefficients is as follows:

[0109]

[0110] At the receiving end, the frequency-interpolated OFDM signal is subjected to MMSE equalization to obtain the signal. ,pass Figure 3 and Figure 4 It can be seen that when the maximum Doppler frequency shift is 300Hz and 3000Hz, the frequency domain interpolation equalization effect of the present invention is significantly better than the direct equalization effect.

[0111] For the signal after MMSE equalization The signal is extracted; then 16QAM demapping is performed on the extracted signal to demodulate the signal; finally, the demodulated signal is converted from parallel to serial and output as a bit stream for subsequent result processing.

[0112] The above examples of the present invention are merely illustrative of the computational model and process of the present invention, and are not intended to limit the implementation of the present invention. Those skilled in the art will recognize that other variations or modifications can be made based on the above description. It is impossible to exhaustively list all possible implementations here. Any obvious variations or modifications derived from the technical solutions of the present invention are still within the scope of protection of the present invention.

Claims

1. A method for suppressing waveform distortion in frequency domain super-resolution reconstructed OFDM, characterized in that, The method specifically includes the following steps: At the launch end Step A1: Digitally modulate the bit data generated by the digital source to obtain a serial modulated symbol stream; Step A2: The modulation symbols in the modulation symbol stream are grouped, and each group includes... One modulation symbol; Step A3: Construct the frequency domain signal vector corresponding to each group of modulation symbols in step A2; Step A4: The frequency domain signal vectors corresponding to each group of modulation symbols undergo inverse fast Fourier transform (IFFT) respectively. Then, the IFFT results for each group of modulation symbols are converted from parallel to serial to obtain the time domain signal vectors. ; Step A5: Assign time-domain signal vector Adding a cyclic prefix yields the time-domain signal after adding the cyclic prefix. ; Step A6: For the time-domain signal after adding the cyclic prefix The digital-to-analog conversion and up-conversion processes are performed sequentially, and the processed signal is sent to the channel. At the receiving end Step B1: After the signal reaches the receiver via the wireless channel, the received signal undergoes down-conversion and analog-to-digital conversion to obtain a discrete time-domain signal. ; Step B2, for the time domain signal After synchronization, the cyclic prefix before the time-domain signal is removed to obtain the data after removing the cyclic prefix. ; Step B3: Perform serial-to-parallel conversion on the data after removing the cyclic prefix, and then perform Fast Fourier Transform on each group of data obtained from the serial-to-parallel conversion to obtain the frequency domain received signal vector corresponding to each group of data. The length of the frequency domain received signal vector corresponding to each group of data is 1. ; Step B4: Extract the original data from each frequency domain received signal vector, and then send the extracted data to the OFDM receiver for decision-making; The extraction of raw data from each frequency domain received signal vector specifically involves: Step B41: For any frequency domain received signal vector For the frequency domain received signal vector Perform frequency domain weighted interpolation to obtain the frequency domain weighted interpolated signal vector. ; Step B42: Weighted interpolation of the signal in the frequency domain Perform IDFT to obtain OFDM time-domain waveform signal of a point For OFDM time-domain signals Perform MMSE equalization to obtain OFDM time-domain signal after point equalization ; Step B43: Equalize the OFDM time-domain signal Perform a Fourier transform to obtain OFDM frequency domain signal after point equalization ; Step B44: Equalize the OFDM frequency domain signal Extraction is performed to obtain OFDM frequency domain signal after point equalization Then from the OFDM frequency domain signal Extract the original data portion; Step B45: Process each frequency domain received signal vector using the methods from steps B41 to B44.

2. The method for suppressing waveform distortion in frequency domain super-resolution reconstruction OFDM according to claim 1, characterized in that, The specific process of step A3 is as follows: For any set of modulation symbols, zero-padding is applied to both the leading and trailing zeros of the set. The resulting zero-padding is used as the frequency domain signal vector corresponding to that set of modulation symbols. The length of the frequency domain signal vector is... .

3. The method for suppressing waveform distortion in frequency domain super-resolution reconstruction OFDM according to claim 2, characterized in that, The zero-padding lengths for the leading and trailing zeros are as follows: like If the number is even, then the length of the leading zero and the length of the trailing zero are both 1. ; like If the number is odd, then the length of the leading zeros is... The length of the zero padding is .

4. The method for suppressing waveform distortion in frequency domain super-resolution reconstruction OFDM according to claim 3, characterized in that, The specific process of step A5 is as follows: Copy the time-domain signal vector The length of the end is The symbol sequence is then copied and added to the time-domain signal vector. At the beginning position, the time-domain signal after adding the cyclic prefix is ​​obtained. .

5. The frequency domain super-resolution reconstructed OFDM waveform distortion suppression method according to claim 4, characterized in that, The specific process of step B41 is as follows: Construction dimension Receiver frequency domain interpolation matrix , matrix The Middle Line number Set the value of each element in the column to 1, and set the value of the first element to 1. Line number Set the values ​​of the column elements to coefficients. The first Line number Set the values ​​of the column elements to coefficients. All other elements are set to 0; Using matrices For the frequency domain received signal vector Perform a linear transformation, that is, a matrix With frequency domain received signal vector Perform multiplication operations and use the result of the multiplication operations as the interpolated signal vector. .

6. The frequency domain super-resolution reconstructed OFDM waveform distortion suppression method according to claim 5, characterized in that, The coefficient It is a function of maximum multipath delay spread and maximum Doppler shift, with coefficients... Specifically: in, , Indicates the maximum multipath delay spread. , Indicates the maximum Doppler frequency shift. , All are polynomial coefficients.

7. The method for suppressing waveform distortion in frequency domain super-resolution reconstruction OFDM according to claim 6, characterized in that, The coefficient It is a function of maximum multipath delay spread and maximum Doppler shift, with coefficients... Specifically: in, All are polynomial coefficients.

8. The method for suppressing waveform distortion in frequency domain super-resolution reconstruction OFDM according to claim 7, characterized in that, In step B42, the OFDM time-domain signal The specific process of performing MMSE equalization is as follows: Step B421, constructing the dimension as Transmitter frequency domain transformation matrix , matrix The Middle Line number Set the elements of the column to 1, and set all other elements to 0; Step B422: Calculate the frequency domain transformation matrix of the transmitter. Equivalent form in the time domain and the receiver frequency domain interpolation matrix Equivalent form in the time domain : in, The dimension is The inverse fast Fourier transform matrix, matrix The Middle Line number Column elements , ; The dimension is The fast Fourier transform matrix, matrix The Middle Line number Column elements , , The base of the natural logarithm. Represents the imaginary unit; Step B423, based on and The construction dimension is Interpolated equivalent channel matrix : in, The dimension is The channel matrix, where the superscript -1 represents the inverse of the matrix; Step B424: Based on the interpolated equivalent channel matrix Perform MMSE equalization to obtain the dimension as Equalizer coefficient matrix : in, Indicates the average power of the signal. Indicates the average noise power. Represents the identity matrix. express The conjugate transpose of; Step B425: Convert the OFDM time-domain waveform signal With equalizer coefficient matrix Multiply, we get OFDM time-domain signal after point equalization .

9. The method for suppressing waveform distortion in frequency domain super-resolution reconstruction OFDM according to claim 8, characterized in that, The equalized OFDM frequency domain signal Extraction is performed specifically by extracting the equalized OFDM frequency domain signal. The odd points in the sample are used to form the equalized OFDM frequency domain signal. .

10. The method for suppressing waveform distortion in frequency domain super-resolution reconstruction OFDM according to claim 9, characterized in that, The OFDM frequency domain signal The original data portion was extracted, specifically as follows: like If the number is even, then from the equalized OFDM frequency domain signal The first in Starting from a point, extract continuously Points, will be extracted These points serve as the raw data for extraction; like If the number is odd, then from the equalized OFDM frequency domain signal The Starting from a point, extract continuously Points, will be extracted These points serve as the raw data extracted.

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