基于DNA遗传优化的正交小波常模盲均衡算法

发布时间：2019-06-13 21:06

【摘要】：为克服传统正交小波变换盲均衡算法(Wavelet transform constant modulus blind equalization algorithm,WTCMA)收敛速度慢、均方误差大、易于陷入局部极小值的缺点,提出了一种基于DNA遗传优化的正交小波常模盲均衡算法(Wavelet transform constant modulus blind equalization algorithm based on the optimization of DNA genetic algorithm,DNA-GA-WTCMA)。该算法采用基于DNA核苷酸链的编码方式表示问题的可能解,并且对编码后的DNA链采用新型的交叉操作和变异操作来寻找DNA种群中的最优个体,然后将得到的最优个体进行解码,把解码后得到的权向量作为均衡器的最优权向量,以避免WTCMA出现局部收敛并提高收敛速度。仿真实验表明,与基于遗传优化的正交小波变换常模盲均衡算法(Wavelet transform constant modulus blind equalization algorithm based on the optimization of genetic algorithm,GA-WTCMA)相比,该算法可以获得更快的收敛速度和更低的均方误差。
[Abstract]:in ord to overcome that disadvantage that the traditional orthogonal wavelet transform blind equalization algorithm (WTMA) is slow to converge, the mean square error is large, and the local minimum value is easy to fall into, A method for the blind equalization of orthogonal wavelet (DNA-GA-WTMA) based on DNA genetic optimization is proposed. The method adopts the coding mode of the DNA-based nucleic acid chain to represent the possible solution of the problem, and adopts a novel cross operation and mutation operation on the encoded DNA chain to find the optimal individual in the DNA population, and then decodes the obtained optimal individual, The obtained weight vector is used as the optimal weight vector of the equalizer so as to avoid local convergence of the WTCMA and improve the convergence speed. The simulation experiments show that the algorithm can obtain a faster convergence rate and lower mean square error compared with the orthogonal wavelet transform (GA-WTMA) based on the genetic optimization.
【作者单位】：南京信息工程大学电子与信息工程学院;
【基金】：江苏省高校自然科学研究重大(13KJA510001)资助项目高校科研成果产业化推进工程(JHB2012-9)资助项目江苏省高校信息与通信工程优势学科建设工程资助项目
【分类号】：TN911.5

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