Particle swarm optimization based orthogonal wavelet blind equalization method

A technology of particle swarm optimization and orthogonal wavelet, applied in baseband system components, shaping network in transmitter/receiver, electrical components, etc., can solve the problem that it is difficult to obtain the global minimum point of the cost function Optimal solution, small amount of computation, etc.

Inactive Publication Date: 2011-07-13
NANJING UNIV OF INFORMATION SCI & TECH
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Problems solved by technology

This method has simple structure, small amount of calculation and stable performance, but it is difficult to obtain the global minimum point of the cost function, and the convergence speed is slow, and the steady-state error after convergence is large.
Literature [2] (Han Yingge, Guo Yecai, Li Baokun, Zhou Qiaoxi. Blind equalization algorithm of orthogonal wavelet transform with the introduction of momentum [J]. Journal of System Simulation, 2008, 20(6): 1559-1562.) shows that the o

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  • Particle swarm optimization based orthogonal wavelet blind equalization method
  • Particle swarm optimization based orthogonal wavelet blind equalization method
  • Particle swarm optimization based orthogonal wavelet blind equalization method

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Embodiment

[0080] In order to test the effectiveness of the method (PSO-WT-CMA) of the present invention, a simulation experiment was carried out with the WT-CMA method as a comparison object.

[0081] [Example 1] The underwater acoustic channel is h=[0.3132-0.1040 0.8908 0.3134]; the transmitted signal is 8PSK, the equalizer weight length is 16, and the signal-to-noise ratio is 20dB; in the WT-CMA method, the 16th tap coefficient is set is 1, and the rest are 0; its step size is μ WT-CMA =2.5×10 -3 ; The step size of the PSO-WT-CMA of the present invention is μ PSO-WT-CMA =1.5×10 -4 . The input signal of the channel is decomposed by DB4 orthogonal wavelet, the decomposition level is 2 layers, the initial value of power is set to 4, and the forgetting factor β=0.99; 1000 times of Monte Carlo simulation results, such as image 3 shown.

[0082] image 3 (a) shows that: on the convergence speed, the PSO-WT-CMA of the present invention is about 5500 steps faster than the WT-CMA. In t...

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Abstract

The invention discloses a particle swarm optimization based orthogonal wavelet blind equalization method. The method comprises the following steps of: allowing a transmitted signal a(k) to pass through a pulse response channel h(k) to acquire a channel output signal x(k); acquiring an orthogonal wavelet transformation (WT) input signal y(k) through channel noise n(k) and x(k); performing WT on the input signal y(k) to acquire an output signal R(k); taking the input signal y(k) as input of a particle swarm optimization (PSO) algorithm and randomly initializing a group of weight vectors, wherein each particle corresponds to each group of weight vectors one to one; determining a fitness function of PSO through a cost function of an orthogonal wavelet transformation-constant module algorithm (WT-CMA) blind equalization method; when a fitness value is the maximum, finding out an optimal position vector in the group and taking the optimal position vector as an initialization weight vector W(k) of the WT-CMA; and acquiring an equalizer output signal z(k) from the output signal R(k) and initialization weight vector W(k). In the method, the optimal equalizer initialization weight vector is sought through PSO, and the autocorrelation of the signal is reduced by WT. Compared with WT-CMA, the method has higher convergence rate and lower steady-state error.

Description

technical field [0001] The invention relates to an orthogonal wavelet blind equalization method based on particle swarm optimization in an underwater acoustic communication system. Background technique [0002] In the underwater communication system, the distortion of the communication channel and the Inter-Symbol Interference (ISI) caused by the limited bandwidth are the main factors affecting the communication quality. In order to eliminate ISI, an equalization technique needs to be introduced at the receiving end. Compared with the traditional adaptive equalization method, the blind equalization technology does not need to transmit periodic training sequences, and only uses the statistical characteristics of the reception itself to equalize the channel changes, saving bandwidth, and is an effective means to overcome inter-symbol interference. In the blind equalization method, the constant module algorithm (Constant Module Algorithm, CMA) (see literature [1] A, Kaya I, ...

Claims

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Application Information

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IPC IPC(8): H04L25/03H04B13/02
Inventor 郭业才胡玲玲
Owner NANJING UNIV OF INFORMATION SCI & TECH
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