Particle swarm optimization based orthogonal wavelet blind equalization method

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, ...

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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 orthogonal The wavelet transform constant modulus blind equalization method (WT-CMA) utilizes the good decorrelation and power normalization technology of the orthogonal wavelet transform, which effectively speeds up the convergence speed; however, WT-CMA still uses the stochastic gradient search method to obtain The weight vector optimal solution, like CMA, still has the defect that it is easy to fall into local convergence and it is difficult to obtain the global optimal solution

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