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针对常数模盲均衡算法(CMA)均衡高阶正交振幅调制信号(QAM)存在收敛速度慢、稳态误差大的缺点, 提出了基于量子粒子群优化的正交小波加权多模盲均衡算法(QPSO-WTWMMA). 该算法根据高阶QAM信号星座图分布特点, 将量子粒子群优化算法(QPSO) 和正交小波变换融入于加权多模盲均衡算法(WMMA)中. 因而, 利用QPSO对均衡器权向量进行了优化, 利用正交小波变换降低了输入信号的自相关性, 利用WMMA选择了合适的误差模型匹配QAM星座图. 理论分析及水声信道仿真结果表明, QPSO-WTWMMA算法可以获得更快的收敛速度和更低的稳态误差, 在水声通信中具有重要的参考价值.When constant modulus blind equalization algorithm (CMA) is used to equalize high-order QAM signals, there occur the defects of the slow convergence rate and big steady mean square error. In order to overcome these disadvantages, orthogonal wavelet transform weighted multi-modulus blind equalization algorithm based on the quantum particle swarm optimization (QPSO-WTWMMA) is proposed. In this proposed algorithm, quantum particle swarm optimization algorithm and orthogonal wavelet transform are combined into weighted multi-modulus blind equalization algorithm (WMMA) according to the feature of higher-order QAM signal constellations. Accordingly, the equalizer weight vector can be optimized by QPSO algorithm, the autocorrelation of the input signals can be reduced via using orthogonal wavelet transform, and WMMA is used to choose appropriate error models to match QAM constellations. The theoretical analyses and the computer simulations in underwater acoustic channels indicate that the proposed algorithm can obtain the fastest convergence rate and the smallest steady mean square error in equalizing high-order QAM signals. So, the proposed algorithm has important reference value for the underwater acoustic communications.
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Keywords:
- quantum particle swarm algorithm /
- orthogonal wavelet transform /
- quadrature amplitude modulation /
- weighted multi-modulus blind equalization algorithm
[1] He C B, Huang J G, Han J, Zhang Q F 2009 Acta Phys. Sin. 588379 (in Chinese) [何成兵, 黄建国, 韩晶, 张群飞 2009 物理学报 58 8379]
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[15] Tuo S H 2010 Sys. Simul. Technol. 6 202 (in Chinese) [拓守恒 2010 系统仿真技术 6 202]
[16] Fang W, Sun J, Xie Z P, XuWB 2010 Acta Phys. Sin. 59 3685 (inChinese) [方伟, 孙俊, 谢振平, 须文波 2010 物理学报 59 3685]
[17] Zhang Y B, Zhao J W, Guo Y C, Li J M 2010 Appl. Acoust. 71653
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[1] He C B, Huang J G, Han J, Zhang Q F 2009 Acta Phys. Sin. 588379 (in Chinese) [何成兵, 黄建国, 韩晶, 张群飞 2009 物理学报 58 8379]
[2] Yin J W, Hui J Y, Guo L X 2008 Acta Phys. Sin. 57 1753 (inChinese) [殷敬伟, 惠俊英, 郭龙祥 2008 物理学报 57 1753]
[3] Guo Y C, Gong X L 2011 Inform. Internat. Interdis. J. 14 675
[4] RaoW, Guo Y C,Wang S Q 2011 Acta Elec. Sin. 39 7 (in Chinese) [饶伟, 郭业才, 汪胜前 2011 电子学报 39 7]
[5] Yuan J T, Tsai K D 2005 IEEE Trans. Commun. 53 1427
[6] Dou G Q, Gao J 2008 J. Electron. Information Technol. 30 388 (inChinese) [窦高奇, 高俊 2008 电子与信息学报 30 388]
[7] Yuan J T, Lin T C 2010 IEEE Trans. Signal Process 58 3206
[8] Wu D, Ge L D, Wang B 2010 J. Information Eng. Univ. 11 45 (inChinese) [吴迪, 葛临东, 王彬 2010 信息工程大学学报 11 45]
[9] Xu X D, Dai X C, Xu P X 2007 J. Electron. Information Technol.29 1352 (in Chinese) [许小东, 戴旭初, 徐佩霞 2007 电子与信息学报 29 1352]
[10] Guo Y C, Liu Z X 2010 Acta Armamentarii 31 279 (in Chinese) [郭业才, 刘振兴 2010 兵工学报 31 279]
[11] Ma T P, Hu L Q, Chen K Y 2010 Acta Phys. Sin. 59 7209 (in Chinese) [马天鹏, 胡利群, 陈开云 2010 物理学报 59 7209]
[12] Ren L, Chen X G, Liu C T 2009 Acta Phys. Sin. 58 2035 (inChinese) [任磊, 陈祥光, 刘春涛 2009 物理学报 58 2035]
[13] Liao J, Guo Y C, Liu Z X, Ji J J 2011 Acta Armamentar II 32 268(in Chinese) [廖娟, 郭业才, 刘振兴, 纪娟娟 2011 兵工学报 32 268]
[14] Gao M, Guo Y C, Liu Z X, Zhao X Q 2011 J. Data Acquisit. Proc.26 128 (in Chinese) [高敏, 郭业才, 刘振兴, 赵雪清 2011 数据采集与处理 26 128
[15] Tuo S H 2010 Sys. Simul. Technol. 6 202 (in Chinese) [拓守恒 2010 系统仿真技术 6 202]
[16] Fang W, Sun J, Xie Z P, XuWB 2010 Acta Phys. Sin. 59 3685 (inChinese) [方伟, 孙俊, 谢振平, 须文波 2010 物理学报 59 3685]
[17] Zhang Y B, Zhao J W, Guo Y C, Li J M 2010 Appl. Acoust. 71653
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