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基于改进的布谷鸟搜索算法优化的正交小波动态加权多模盲均衡算法

Orthogonal Wavelet Transform Dynamic Weighted Multi-modulus Blind Equalization Algorithm Based on the Improved Cuckoo Search Algorithm

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【作者】 郑亚强

【Author】 ZHENG Ya-qiang;Huainan Union University;

【机构】 淮南联合大学

【摘要】 为了更好地均衡高阶QAM信号,本文提出了基于改进的布谷鸟搜索算法优化的正交小波动态加权多模盲均衡算法(ICS-WT-DWMMA),利用改进了的布谷鸟搜索算法初始化均衡器的权向量,利用小波变换(WT)降低信号自相关性,其中动态加权多模盲均衡算法(DWMMA)利用由判决符号的指数幂构成的加权项来调整代价函数中的模值.水声信道的MATLAB仿真实验结果表明,与小波加权多模盲均衡算法和小波动态加权多模盲均衡算法比较,新算法收敛速度更快,稳态误差更小.

【Abstract】 In order to improve the equalization of high-order QAM signals,the Orthogonal Wavelet Transform Dynamic Weighted Multi-Modulus blind equalization Algorithm based on the Improved Cuckoo Search Algorithm(ICS-WT-DWMMA)was proposed.It took advantage of the weight vector which improved cuckoo search algorithm initialization of equalizer and the wavelet transform(WT)to reduce the signal autocorrelation.The DWMMA(Dynamic Weighted Multi-Modulus blind equalization Algorithm)adjusted the modulus in the cost function by weighted term composed of exponent of decision symbol.The MATLAB simulation results of underwater acoustic channel shew that,compared with Wavelet Weighted Multimodulus blind equalization algorithm and wavelet dynamic weighted Multimodulus blind equalization algorithm,the new algorithm had a faster convergence speed and steady-state error was smaller.

  • 【文献出处】 德州学院学报 ,Journal of Dezhou University , 编辑部邮箱 ,2014年06期
  • 【分类号】TN911.5
  • 【被引频次】1
  • 【下载频次】60
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