A Wavelet Weighted Multimodal Blind Equalization Method Based on Mixed Monkey Group Optimization
A technology of multi-mode blind equalization and optimization method, which is applied in the baseband system, baseband system components, shaping network in the transmitter/receiver, etc., can solve the problem of reducing the signal-to-noise ratio, unable to overcome local extreme values, and difficult to further improve issues of balance
Inactive Publication Date: 2019-12-31
HEFEI CAREER TECHNICAL COLLEGE
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The weighted multi-mode method (WMMA) uses the exponential power of the decision symbol to form a weighted item, which can adaptively modulate the modulus value and effectively reduce the model error. However, when obtaining the global optimal solution of the non-convex cost function of the method, the gradient is still used. The idea of descending cannot overcome the problem that the method is easy to fall into local extremum, and it is difficult to further improve the equalization effect. Introducing wavelet transform (WT) into WMMA can reduce the signal-to-noise ratio, but it can only improve the equalization effect to a certain extent
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[0099] The following is a further description of a wavelet weighted multi-mode blind equalization method based on mixed monkey group optimization of the present invention with reference to the accompanying drawings and specific embodiments:
[0100] The principle block diagram of the present invention is as figure 1 As shown, figure 1 Where a(k) is the complex signal transmitted by the source; c(k) is the channel impulse response vector of length L, c(k)=[c(k),L,c(k-L+1)] T ; B(k) is the additive white Gaussian noise in the communication process; y(k) is the complex signal sequence of length L transmitted through the channel, y(k)=[y(k+L),L,y (kL)] T , R(k) is the complex signal of y(k) after wavelet transformation; F(k) is the weight vector of the equalizer, F(k)=[F 0 (k),L,F L (k)) T (The superscript T means transpose); z(k) is the output complex signal of the equalizer; the subscripts Re and Im represent the real and imaginary parts of the parameters, respectively.
[0101] Suc...
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The invention discloses a wavelet weighted multi-mode blind equalization method based on mixed monkey group optimization. A climbing step length in a monkey group optimization method is determined by using a Levi flight mode, a simulated annealing optimization method is embedded in the monkey group optimization method to obtain a mixed monkey group optimization method, the new method has very good global optimization ability, an optimal position vector of a monkey group in a search space can be obtained by the method, the vector is used as an initial vector in the weighted multi-mode blind equalization method based on wavelet transform, at this time, a blind equalization system becomes an expected ideal system and has very good equalization ability. Compared with the prior art, the wavelet weighted multi-mode blind equalization method disclosed by the invention has the advantages of having good equalization ability on high-order quadrature amplitude modulation signals, and having a high convergence speed, a small steady state error and certain practical value.
Description
Technical field: [0001] The invention relates to the technical field of data acquisition and signal processing, in particular to a wavelet weighted multi-mode blind equalization method based on mixed monkey group optimization. Background technique: [0002] At present, underwater acoustic communication is a generally accepted method of underwater communication. Factors such as multipath propagation and high background noise in the underwater acoustic channel will cause severe inter-symbol interference (ISI) during signal transmission. , The communication quality cannot be guaranteed. To solve this problem, various equalization techniques have emerged. The weighted multi-mode method (WMMA) uses the exponential power of the decision symbol to form the weighting term, which can adaptively modulate the modulus value and effectively reduce the model error. However, the gradient is still used when obtaining the global optimal solution of the non-convex cost function of the method. Th...
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IPC IPC(8): H04L25/03
CPCH04L25/03006H04L25/0307H04L25/03891H04L2025/03687H04L2025/03707
Inventor 高敏周国良郑亚强李云玲赵敏
Owner HEFEI CAREER TECHNICAL COLLEGE