CN118214520A - MIMO detection method for multi-user interference suppression based on FRESH filter - Google Patents
MIMO detection method for multi-user interference suppression based on FRESH filter Download PDFInfo
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Abstract
本发明提出了一种基于FRESH滤波器进行多用户干扰抑制的MIMO检测方法，首先，确定2×2MIMO通信系统中不同发射天线发送的不同码率数据信号，得到不同发射天线发送信号的循环频率和共轭循环频率；然后，生成发送数据序列进行LDPC编码，块交织，OQAM调制，添加前导序列，进行成型滤波，通过射频部分的天线发出；接着，两根接收天线对接收到的信号，分别通过WL‑MMSE先进行滤波均衡，将前导用于训练WL‑FRESH的自适应系数，将有用信号通过WL‑FRESH滤波，经过匹配滤波器和抽样OQAM解调、解交织和解LDPC，得到估计值。本发明方法基于多输入FRESH滤波器利用信号的循环平稳性进一步消除多用户干扰，进一步提升了系统的整体误码率性能。
The present invention proposes a MIMO detection method for multi-user interference suppression based on FRESH filter. First, different code rate data signals sent by different transmitting antennas in a 2×2 MIMO communication system are determined to obtain the cyclic frequency and conjugate cyclic frequency of the signals sent by different transmitting antennas; then, a transmission data sequence is generated for LDPC encoding, block interleaving, OQAM modulation, a preamble sequence is added, and a shaping filter is performed, which is then sent through the antenna of the radio frequency part; then, the two receiving antennas filter and equalize the received signals through WL-MMSE respectively, and the preamble is used to train the adaptive coefficient of WL-FRESH, and the useful signal is filtered through WL-FRESH, and then demodulated, deinterleaved and de-LDPCed by a matched filter and sampling OQAM to obtain an estimated value. The method of the present invention further eliminates multi-user interference based on the cyclostationarity of the signal based on the multi-input FRESH filter, and further improves the overall bit error rate performance of the system.
Description
Technical Field
The invention belongs to the technical field of communication, and particularly relates to a MIMO detection method for multi-user interference suppression based on a FRESH filter.
Background
In a MIMO (multiple-transmission multiple-reception) communication system, a receiving end receives a plurality of signal waveforms from a transmitting end, and for a signal at the receiving end, signals from the remaining users except for a signal of its target user can be regarded as interference signals. Interference is a performance limiting factor in wireless communication systems, which needs to be minimized or mitigated. That is, to improve the performance of the MIMO wireless communication system, it is important to solve the problem of multi-user interference.
In common receiver implementations, the Minimum Mean Square Error (MMSE) and Zero Forcing (ZF) methods are similar, requiring a known channel matrix. ZF is able to completely cancel multi-antenna interference, but it does not cancel noise, but instead amplifies it, which can be very poor when the signal-to-noise ratio is low. MMSE minimizes multi-user interference and noise over mean square error, and its performance is optimal. MMSE can be extended to WL-MMSE (wide linear minimum mean square error) using the concept of WL (wide linear), and it has been demonstrated that WL-MMSE performance is significantly better than MMSE for complex signals, with considerable gain in terms of both Mean Square Error (MSE) and Bit Error Rate (BER).
WL-MMSE can obtain the most gain in uncorrelated channels, however in practical communication environments, channels often have a certain correlation due to factors such as distance. As the channel correlation increases, the performance of the WL-MMSE may be degraded, i.e., a significant portion of the multi-user interference may still remain after passing through the WL-MMSE receiver.
For surviving interference, a common approach is to filter the signal. The signals obtained by the common modulation mode, such as BPSK, QAM, OQAM, have cyclostationarity, and when the signals have cyclostationarity, the signals have the cyclic frequency related to the modulation parameter, i.e. the new signals obtained after the signals are shifted to the cyclic frequency have strong correlation with the signals. A FRESH (frequency shift) filter is a filter that estimates a signal using a signal cyclic frequency, and can enhance or attenuate a signal of a specific frequency component by shifting a target Signal (SOI) spectrum to its cyclic frequency and then performing an appropriate weighting process. Because the cyclic frequency of interference and noise is different from that of the SOI signal, the FRESH filter will improve the output signal-to-noise ratio of the SOI signal.
Because the cyclic non-circular signal contains both cyclic characteristics and extremely non-circular characteristics, besides the cyclic characteristics, the non-circular characteristics can be used for performing wide linear processing, namely WL-FRESH, on the FRESH filter.
WL-FRESH filters have the ability to perform Single Antenna Interference Cancellation (SAIC) on one straight line (R) or quasi-straight line (QR) co-channel interference (CCI). The QR signal has a conjugated cyclic spectrum, and the information in the QR signal cyclic spectrum and the conjugated cyclic spectrum can be fully mined through the WL-FRESH filter, so that a larger output signal-to-noise ratio gain is obtained.
The multi-branch input WL-FRESH filter is adopted to better eliminate the same-frequency interference of different code rates, and the five-input, seven-input and nine-input FRESH filters are further provided based on the three-input WL-FRESH, so that the cyclostationary characteristic of the communication signal can be better utilized, and the method has important practical application significance.
Disclosure of Invention
The invention aims to solve the problems that: the MIMO detection method for multi-user interference suppression based on the FRESH filter is provided, the multi-user interference is further eliminated based on the cyclic stability of the signals of the multi-input FRESH filter, and the overall bit error rate performance of the system is improved.
The invention adopts the following technical scheme: a MIMO detection method for multiuser interference suppression based on a FRESH filter comprises the following steps:
Step S1, determining the code rate, carrier frequency and sampling frequency of data signals transmitted by different transmitting antennas in a 2X 2MIMO communication system, and obtaining the cycle frequency and conjugate cycle frequency of the signals transmitted by different transmitting antennas based on a FRESH filter;
The FRESH filter comprises two antennas at the receiving end, and transmits by adopting different baud rates to obtain different circulating frequencies; the receiving end uses WL-MMSE to connect with the multi-input FRESH filter structure, and the multi-user interference is further eliminated by utilizing the cyclic stability of the signal on the basis of WL-MMSE.
Step S2, based on the frequency shift amounts corresponding to the nonconjugated and conjugated branches of the FRESH filter, a transmission data sequence { a n}、{bm } is generated, LDPC coding is carried out, the coded data is processed through a block interleaving module to obtain a corresponding bit sequence, the corresponding bit sequence is sent to an OQAM modulation module, constellation mapping processing is carried out to obtain a sequence { A n}、{Bm }, then a preamble sequence is added, shaping filtering is carried out, and the sequence is sent out through an antenna of a radio frequency part of the FRESH filter.
Step S3, the two receiving antennas of the FRESH filter respectively carry out filtering equalization on the received signals through WL-MMSE, then the preamble sequence is used for training the self-adaptive coefficient of WL-FRESH, the residual signals after the preamble is removed, namely the useful signals pass through the trained WL-FRESH filter, and the maximum signal to noise ratio at the sampling moment is ensured through the matched filter and sampling; OQAM demodulation is carried out on the preamble sequence to obtain a sequenceAnd performing de-interleaving and de-LDPC to obtain an estimated value/> And further obtaining an output signal of the FRESH filter system.
Further, the low-pass equivalent expression of the FRESH filter transmit signal x (t) is:
Wherein b k is a real-value symbol with zero mean value, T is a half period of a corresponding OQAM signal, T is the time of the signal, k is the number of a transmitting symbol at the current moment, and a function g represents a matrix pulse signal; j k is a symbol representing the rotation of the currently transmitted symbol, i.e. OQAM modulation.
Further, in step S1, a cycle frequency and a conjugate cycle frequency of the transmission signal are obtained, which includes the following sub-steps:
S1.1 defining a time-varying autocorrelation function R x (t, τ), a cyclic autocorrelation function The expression is as follows:
Wherein, E function represents expectations, alpha represents cyclic frequency, tau represents time delay, E j2παt represents Fourier series, and E -j2παt represents inverse Fourier series;
S1.2, carrying out Fourier transformation on the cyclic autocorrelation function and having a cyclic spectral density function
Wherein X (f) represents the frequency spectrum of the signal X (t), the cyclic frequency alpha k＝k/T＝k/RS,k∈Z,Rs represents the transmission code rate, and Z represents the integer set;
S1.3, deriving by utilizing the characteristic of conjugate cyclostationarity and a formula of a conjugate cyclic spectrum to obtain a conjugate cyclic spectrum density function The expression is as follows:
Wherein, the cyclic frequency beta k＝(2k+1)/2T＝(2k+1)/2RS, k epsilon Z.
Further, in step S2, the cyclic spectrum and the conjugated cyclic spectrum of the OQAM signal are analyzed, when α 0＝0、α±1＝±1/T、α±2 = ±2/T, the cyclic spectrum has a larger peak value, when β ±1＝±1/2T、β±2 = ±3/2T, the conjugated cyclic spectrum has a larger peak value, when α and β are at the above values, the cyclic spectrum of the OQAM signal has a larger information amount, and the seven cyclic frequencies and the conjugated cyclic frequency offset are selected to form a seven-branch FRESH filter.
Further, in step S3, each antenna performs FRESH filtering on the received complex signal x (t) to generate an estimate of the expected response d (t)The equation is as follows:
Wherein x (t) and x * (t) respectively represent input signals of non-conjugated and conjugated branches of the FRESH filter, { alpha n } and { beta m } respectively represent frequency shift amounts corresponding to the non-conjugated and conjugated branches, { a n (t) } and { b m (t) } respectively represent frequency shift amounts corresponding to the non-conjugated and conjugated branches;
Where N and M represent the selected nonconjugated cyclic frequencies and the number of conjugated cyclic frequencies.
Further, the unconjugated filtering part and the conjugated filtering part of the FRESH filter are two parallel systems, the excitation of the unconjugated filtering part and the conjugated filtering part is r (t) and r * (t) respectively, the input of the filter is equivalent to a multi-branch signal obtained after the original input signals r (t) and r * (t) are subjected to frequency shift operation respectively, the frequency shift amounts are alpha p and beta q respectively, and the signals after the frequency shift operation are respectively sent into impulse responsesAnd/>In the finite impulse response FIR filter, the output of each branch is subjected to superposition summation operation to obtain the final output of the FRESH filter, namely the signal reconstructed by the FRESH filter, and then LDPC decoding and data processing are performed.
The adaptive optimization of the FRESH filter adopts an RLS adaptive algorithm, the input of the RLS adaptive algorithm is an error signal between an output signal and an expected signal of the FRESH filter, the weight vector of each branch is optimized in real time, and the RLS adaptive algorithm comprises the following substeps:
s3.1, calculating the output of the FRESH filter to obtain a signal estimated value The formula is as follows:
Wherein r (t) represents a FRESH filter input obtained by combining r (t) and r * (t), H H (t) represents a filter parameter, and H represents a conjugate transpose;
s3.2, obtaining an error between the signal estimated value and the expected signal, wherein the formula is as follows:
Wherein s (n) is a desired signal value;
s3.3, carrying out error introduction according to an iterative formula of the self-adaptive algorithm to obtain a new weight vector, namely a weight vector h (n+1) at the next moment;
After the preamble training is finished, the FRESH filter is in a stable state, then filtering processing is carried out on the signals, each frequency shift branch respectively uses a trained FIR filter to filter the corresponding input signals of each branch, and the optimal estimated value of the signals obtained by iterative optimization of the RLS adaptive algorithm is used as the final output of the WL-FRESH filter, so that the reconstruction of the signals is realized.
The technical scheme of the invention also provides: an electronic device, comprising:
one or more processors;
A storage device having one or more programs stored thereon;
The one or more programs, when executed by the one or more processors, cause the one or more processors to implement any of the methods for multi-user interference suppression based on a FRESH filter described above.
The technical scheme of the invention also provides a computer readable storage medium, on which a computer program is stored, which when being executed by a processor, realizes the steps in any of the above MIMO detection methods for multi-user interference suppression based on a FRESH filter.
Compared with the prior art, the technical scheme provided by the invention has the following technical effects:
The MIMO detection method for multi-user interference suppression based on the FRESH filter solves the problem that the capacity of eliminating multi-user interference of a receiving end under a related channel in a 2X 2MIMO communication system is limited, can obviously obtain good arrival detection performance under a lower signal-to-noise ratio, and does not obviously improve the complexity of the system.
Drawings
Fig. 1 is a flow chart of a MIMO detection method of multi-user interference suppression of the present invention;
FIG. 2 is a cyclic spectrum of an OQAM signal for the MIMO detection method of the present invention;
FIG. 3 is a conjugated cyclic spectrum of an OQAM signal for the MIMO detection method of the present invention;
FIG. 4 is a block diagram of a FRESH filter using seven inputs for the MIMO detection method of the present invention;
FIG. 5 is a comparison of error rate curves of three detection algorithms when the channel correlation coefficient is 0.9 according to the embodiment of the present invention;
Fig. 6 is a graph showing error rate curves of the full communication link system when the channel correlation coefficient is 0.9 according to the embodiment of the present invention.
Detailed Description
In order to make the objects, technical solutions and advantages of the present invention more apparent, the technical solutions of the application will be further elaborated in conjunction with the accompanying drawings, and the described embodiments are only a part of the embodiments to which the present invention relates. All non-innovative embodiments in this example by others skilled in the art are intended to be within the scope of the invention. Meanwhile, the step numbers in the embodiments of the present invention are set for convenience of illustration, the order between the steps is not limited, and the execution order of the steps in the embodiments can be adaptively adjusted according to the understanding of those skilled in the art.
In one embodiment of the present invention, a communication link for multiuser interference suppression based on a FRESH filter is provided for the problem that the capability of canceling multiuser interference by a receiving end under a correlated channel is limited in a2×2MIMO communication system.
The two antennas at the receiving end of the FRESH filter of the embodiment adopt different baud rates for transmitting so as to obtain different circulating frequencies; the receiving end uses the WL-MMSE to connect the structure of the multi-input WL-FRESH filter in series, and further eliminates multi-user interference by utilizing the cyclic stability of the signals on the basis of WL-MMSE, thereby further improving the overall error rate performance of the system.
Specifically, the MIMO detection method for multiuser interference suppression based on the FRESH filter, as shown in step1, includes the following steps:
Step S1, determining code rate R s, carrier frequency f c and sampling frequency f s of data signals transmitted by different transmitting antennas in a 2X 2MIMO communication system, and obtaining cycle frequency and conjugate cycle frequency of the signals transmitted by different transmitting antennas based on a FRESH filter;
step S2, generating a transmission data sequence { a n}、{bm } based on frequency shift amounts corresponding to non-conjugated and conjugated branches of a FRESH filter, performing LDPC coding, processing the coded data through a block interleaving module to obtain a corresponding bit sequence, sending the corresponding bit sequence into an OQAM modulation module, performing constellation mapping processing to obtain a sequence { A n}、{Bm }, adding a preamble sequence, performing shaping filtering, and transmitting through an antenna of a radio frequency part of the FRESH filter;
Step S3, the two receiving antennas of the FRESH filter respectively carry out filtering equalization on the received signals through WL-MMSE, then the preamble sequence is used for training the self-adaptive coefficient of WL-FRESH, and the useful signals pass through the trained WL-FRESH filter and are subjected to matched filter and sampling to ensure that the signal to noise ratio is highest at the sampling moment; OQAM demodulation is carried out on the preamble sequence to obtain a sequence And performing de-interleaving and de-LDPC to obtain an estimated value/>And further obtaining an output signal of the FRESH filter system.
In this embodiment, it is assumed that the low-pass equivalent expression of the emission signal x (t) of the FRESH filter is:
wherein b k is the real-valued symbol of zero mean, directly related to the useful symbol; t represents a half period of the corresponding OQAM signal, k is the transmission symbol number at the current time, the function g represents the matrix pulse signal, and j k is the rotation of the current transmission symbol, namely the OQAM modulation.
The time-varying autocorrelation function R x (t, τ), the cyclic autocorrelation function by definition
Fourier transforming the cyclic autocorrelation function has a cyclic spectral density function
Where X (f) represents the spectrum of the signal X (t), the available cyclic frequency α k＝k/T＝k/Nsym,k∈Z,Nsym represents the transmission code rate.
Similarly, the conjugate cyclic spectrum density function can be obtained by utilizing the characteristic of conjugate cyclic stability and the formula derivation of conjugate cyclic spectrumHas the following expression forms:
where the cyclic frequency β k＝(2k+1)/2T＝(2k+1)/2Nsym,k∈Z,Nsym represents the transmission code rate.
In this embodiment, the cyclic spectrum of the OQAM signal is shown in fig. 2, and the conjugated cyclic spectrum of the OQAM signal is shown in fig. 3.
Analysis of the cyclic spectrum and the conjugated cyclic spectrum of the OQAM signal revealed that the cyclic spectrum had a large peak when α 0＝0、α±1＝±1/T、α±2 = ±2/T and a large peak when β ±1＝±1/2T、β±2 = ±3/2T was located.
When α and β are at the above values, there is more information in the OQAM signal cyclic spectrum, which greatly improves the performance of the FRESH filter, so seven cyclic frequencies and conjugate cyclic frequencies are selected to form a FRESH filter with seven branches, as shown in fig. 4, the seven cyclic frequencies and conjugate cyclic frequency offsets are respectively:
By definition, each antenna performs FRESH filtering on the received complex signal x (t) to produce an estimate of the expected response d (t) The equation for (2) is as follows:
Wherein x (t) and x * (t) represent input signals of non-conjugated and conjugated branches of the FRESH filter, respectively, { α n } and { β m } represent frequency shift amounts corresponding to the non-conjugated and conjugated branches, respectively, { a n (t) } and { b m (t) } represent frequency shift amounts corresponding to the non-conjugated and conjugated branches, respectively, wherein:
n and M represent the selected nonconjugated cyclic frequency and the number of conjugated cyclic frequencies.
In this embodiment, the whole FRESH filter can be regarded as two parallel systems, the excitation of which is r (t) and r * (t), the input of the filter is equivalent to the multi-branch signal obtained by performing a series of frequency shift operations on the original input signals r (t) and r * (t), the frequency shift amounts are alpha p and beta q, and the signals after the frequency shift operations are sent to impulse responses respectivelyAnd/>And finally, carrying out superposition summation operation on the output of each branch in the Finite Impulse Response (FIR) filter to obtain the final output of the FRESH filter, namely the reconstructed signal.
In particular, for the FRESH filter of the present embodiment, the adaptive optimization section employs an RLS adaptive algorithm.
Regarding the adaptive algorithm, the input is an error signal between the output signal of the FRESH filter and the desired signal, the weight vector of each branch is optimized in real time by the algorithm, and the process mainly calculates the output (signal estimation value) of the FRESH filter, which is specifically as follows:
Where r (t) represents the FRESH filter input after r (t) and r * (t) are combined.
Error between signal estimate and desired signalThe new weight vector (weight vector at the next time) is expressed as: h (n+1).
After the preamble training is finished, the filter is basically in a stable state, and then useful signals are filtered, and each frequency shift branch respectively filters input signals corresponding to each branch by using the trained FIR filter.
And finally, taking the optimal signal estimated value obtained by iterative optimization of the adaptive algorithm as the final output of the WL-FRESH filter, and realizing the reconstruction of the signal.
As shown in fig. 5, the error rates of the two antennas after WL-MMSE and FRESH are combined under the condition that the relevant channel parameter is 0.9 are lower than the error rates of the pure WL-MMSE, WL-MMSE and RLS after being combined, and the error rate curve of the MIMO communication system for multi-user interference suppression based on the FRESH filter under the condition that the relevant channel parameter is 0.9 is shown in fig. 6.
In summary, compared with the traditional autocorrelation algorithm, the technical scheme of the embodiment can obviously obtain good arrival detection performance under lower signal-to-noise ratio, and meanwhile, the complexity of the system is not obviously improved.
In an embodiment of the present invention, there is also provided an electronic device including: one or more processors; a storage device having one or more programs stored thereon; when the one or more programs are executed by the one or more processors, the one or more processors implement the MIMO detection method for multiuser interference suppression based on the FRESH filter.
In an embodiment of the present invention, there is further provided a computer readable storage medium having stored thereon a computer program which, when executed by a processor, implements the steps in the above MIMO detection method for multiuser interference suppression based on a FRESH filter.
The foregoing is only a preferred embodiment of the invention, it being noted that: it will be apparent to those skilled in the art that various modifications and adaptations can be made without departing from the principles of the present invention, and such modifications and adaptations are intended to be comprehended within the scope of the invention.
Claims (10)
1. The MIMO detection method for multi-user interference suppression based on the FRESH filter is characterized by comprising the following steps:
Step S1, determining the code rate, carrier frequency and sampling frequency of data signals transmitted by different transmitting antennas in a 2X 2MIMO communication system, and obtaining the cycle frequency and conjugate cycle frequency of the signals transmitted by different transmitting antennas based on a FRESH filter;
step S2, generating a transmission data sequence { a n}、{bm } based on frequency shift amounts corresponding to non-conjugated and conjugated branches of a FRESH filter, performing LDPC coding, processing the coded data through a block interleaving module to obtain a corresponding bit sequence, sending the corresponding bit sequence into an OQAM modulation module, performing constellation mapping processing to obtain a sequence { A n}、{Bm }, adding a preamble sequence, performing shaping filtering, and transmitting through an antenna of a radio frequency part of the FRESH filter;
Step S3, the two receiving antennas of the FRESH filter respectively carry out filtering equalization on the received signals through WL-MMSE, then the preamble sequence is used for training the self-adaptive coefficient of the FRESH, the residual signals after the preamble removal pass through the trained FRESH filter, and the highest signal to noise ratio at the sampling moment is ensured through the matched filter and sampling; then OQAM demodulation is carried out to obtain a sequence And performing de-interleaving and de-LDPC to obtain an estimated value/>And further obtains an output signal of the 2×2MIMO communication system.
2. The MIMO detection method for multiuser interference suppression based on a FRESH filter according to claim 1, wherein the FRESH filter has two antennas at a receiving end, and transmits with different baud rates to obtain different cyclic frequencies; the receiving end uses WL-MMSE to connect with the multi-input FRESH filter structure, and the multi-user interference is further eliminated by utilizing the cyclic stability of the signal on the basis of WL-MMSE.
3. The method for MIMO detection based on FRESH filter for multiuser interference suppression according to claim 2, wherein the low-pass equivalent expression of the transmitted signal x (t) of the FRESH filter is:
Wherein b k is a real-value symbol with zero mean value, T is a half period of a corresponding OQAM signal, T is the time of the signal, k is the number of a transmitting symbol at the current moment, and a function g represents a matrix pulse signal; j k is a symbol representing the rotation of the currently transmitted symbol, i.e. OQAM modulation.
4. The method for MIMO detection based on FRESH filter for multiuser interference suppression according to claim 3, wherein in step S1, a cyclic frequency and a conjugated cyclic frequency of a transmission signal are obtained, comprising the following sub-steps:
S1.1 defining a time-varying autocorrelation function R x (t, τ), a cyclic autocorrelation function The expression is as follows:
Wherein, E function represents expectations, alpha represents cyclic frequency, tau represents time delay, E j2παt represents Fourier series, and E -j2παt represents inverse Fourier series;
S1.2, carrying out Fourier transformation on the cyclic autocorrelation function and having a cyclic spectral density function
Wherein X (f) represents the frequency spectrum of the signal X (t), the cyclic frequency alpha k＝k/T＝k/RS,k∈Z,Rs represents the transmission code rate, and Z represents the integer set;
S1.3, deriving by utilizing the characteristic of conjugate cyclostationarity and a formula of a conjugate cyclic spectrum to obtain a conjugate cyclic spectrum density function The expression is as follows:
Wherein, the cyclic frequency beta k＝(2k+1)/2T＝(2k+1)/2RS, k epsilon Z.
5. The method for detecting MIMO interference suppression based on FRESH filter as claimed in claim 4, wherein in step S2, the cyclic spectrum and the conjugated cyclic spectrum of the OQAM signal are analyzed, the peak value of the cyclic spectrum is larger when alpha 0＝0、α±1＝±1/T、α±2 = + -2/T, the conjugated cyclic spectrum has larger peak value when beta ±1＝±1/2T、β±2 = + -3/2T, and the cyclic spectrum of the OQAM signal has more information when alpha and beta are in the above values, and the method is selectedThe seven cyclic frequencies and the conjugate cyclic frequency offset form a seven-branch FRESH filter.
6. The method of claim 5, wherein in step S3, each antenna performs FRESH filtering on the received complex signal x (t) to generate an estimate of the expected response d (t)The equation is as follows:
Wherein x (t) and x * (t) respectively represent input signals of non-conjugated and conjugated branches of the FRESH filter, { alpha n } and { beta m } respectively represent frequency shift amounts corresponding to the non-conjugated and conjugated branches, { a n (t) } and { b m (t) } respectively represent frequency shift amounts corresponding to the non-conjugated and conjugated branches;
Where N and M represent the selected nonconjugated cyclic frequencies and the number of conjugated cyclic frequencies.
7. The method for multi-user interference suppression MIMO detection based on FRESH filter according to claim 1, wherein in step S3, the unconjugated filtering part and conjugated filtering part of the FRESH filter are two parallel systems, the excitation is r (t) and r * (t), the input of the filter is equivalent to the multi-branch signal obtained by frequency shifting the original input signals r (t) and r * (t), the frequency shifting amounts are alpha p and beta q, and the signals after frequency shifting are sent to impulse responseAnd/>In the finite impulse response FIR filter, the output of each branch is subjected to superposition summation operation to obtain the final output of the FRESH filter, namely the signal reconstructed by the FRESH filter, and then LDPC decoding and data processing are performed.
8. The method for MIMO detection based on FRESH filter for multiuser interference suppression according to claim 7, wherein in step S3, RLS adaptive algorithm is adopted for adaptive optimization of FRESH filter, and the input is an error signal between an output signal of FRESH filter and a desired signal, and the method for performing real-time optimization on weight vectors of each branch comprises the following sub-steps:
s3.1, calculating the output of the FRESH filter to obtain a signal estimated value The formula is as follows:
Wherein r (t) represents a FRESH filter input obtained by combining r (t) and r * (t), H H (t) represents a filter parameter, and H represents a conjugate transpose;
s3.2, obtaining an error between the signal estimated value and the expected signal, wherein the formula is as follows:
Wherein s (n) is a desired signal value;
s3.3, carrying out error introduction according to an iterative formula of the self-adaptive algorithm to obtain a new weight vector, namely a weight vector h (n+1) at the next moment;
After the preamble training is finished, the FRESH filter is in a stable state, then filtering processing is carried out on the signals, each frequency shift branch respectively uses a trained FIR filter to filter the corresponding input signals of each branch, and the optimal estimated value of the signals obtained by iterative optimization of the RLS adaptive algorithm is used as the final output of the WL-FRESH filter, so that the reconstruction of the signals is realized.
9. An electronic device, comprising:
one or more processors;
A storage device having one or more programs stored thereon;
the one or more programs, when executed by the one or more processors, cause the one or more processors to implement the method for multi-user interference suppression based on a FRESH filter MIMO detection as claimed in any one of claims 1 to 8.
10. A computer-readable storage medium, having stored thereon a computer program which, when executed by a processor, implements the method for multi-user interference suppression based on a FRESH filter according to any one of claims 1 to 8.
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