适用于高阶QAM信号的分数间隔混合盲均衡算法
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摘要
为了提高高阶QAM信号的盲均衡性能,提出一种分数间隔混合盲均衡算法。该算法将恒模盲均衡算法(CMA)与判决引导算法相结合,并充分利用了分数间隔均衡结构在收敛速度、稳态误差方面的优势。均衡器系数更新首先进行时域解相关,为了消除恒模盲均衡算法的相位不敏感特性,在实现上构造载波同步与盲均衡的大环路。仿真结果表明,对方形星座图的高阶QAM信号,该算法可以提供更快的收敛速度和更小的稳态误差。
For improving the equalization performance of high-order QAM signals,a hybrid blind equalization algorithm based on fractionally spaced sampling is proposed.The algorithm is proposed by joining the Constant Modulus Algorithm( CMA) with the decision directed algorithm.It takes full advantage of the fractional interval structure,providing faster convergence speed and better steady state performance.Decorrelation in time domain is employed for input signals firstly,and then the signals can be used for updating the coefficients of the equalizer. The CMA algorithm has little correlation of phase,so a loop which realizes carrier synchronization and equalization simultaneity is presented. Simulation results demonstrate that the proposed algorithm provides superior performance by increasing the convergence rate and decreasing the steady-state mean square error for square-shape high-order QAM signals of square QAM constellation.
For improving the equalization performance of high-order QAM signals,a hybrid blind equalization algorithm based on fractionally spaced sampling is proposed.The algorithm is proposed by joining the Constant Modulus Algorithm( CMA) with the decision directed algorithm.It takes full advantage of the fractional interval structure,providing faster convergence speed and better steady state performance.Decorrelation in time domain is employed for input signals firstly,and then the signals can be used for updating the coefficients of the equalizer. The CMA algorithm has little correlation of phase,so a loop which realizes carrier synchronization and equalization simultaneity is presented. Simulation results demonstrate that the proposed algorithm provides superior performance by increasing the convergence rate and decreasing the steady-state mean square error for square-shape high-order QAM signals of square QAM constellation.
引文
[1]刁树林,钟剑波.时域自适应均衡技术的分析与应用[J].无线电工程,2009,39(9):44-47.
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[19]李红,雷志勇.基于最大熵谱估计的回波信号检测技术研究[J].半导体光电,2011,32(5):728-732.
[2]张贤达,保铮.通信信号处理[M].北京:国防工业出版社,2002:226-257.
[3]SATO Y.A Method of Self-recovering Equalization for Multilevel Amplitude Modulation Systems[J].IEEE Transactions on Communications,1975,23(6):679-682.
[4]GODARD D.N.Self-recovering Equalization and Carrier Tracking in Two-dimensional Data Communication System[J].IEEE Transactions on Communications,1980,28(11):1867-1875.
[5]张凯,于宏毅,胡赟鹏,等.稀疏信道下基于稀疏贝叶斯学习的精简星座盲均衡算法[J].电子与信息学报,2016,38(9):2255-2260.
[6]YANG J,WERNER J J,DUMONT G A.The Multimodulus Blind Equalization and Its Generalized Algorithms[J].IEEE Journal on Selected.Areas in Communications,2002,20(5):997-1015.
[7]王彬,葛临东,霍亚娟.适用于高阶QAM信号的多模混合盲均衡算法[J].数据采集与处理,2011,26(1):8-14.
[8]戴诚,梁诗晨,肖静薇,等.基于分数间隔的双模式盲均衡算法研究[J].无线电通信技术,2016,42(6):59-62.
[9]张辉,曹丽娜.现代通信原理与技术[M].西安:西安电子科技大学出版社,2006.
[10]孙守宇,郑君里,徐忠勇,等.修正恒模算法分数间隔盲均衡[J].电子学报,2003,31(11):1732-1735.
[11]龙剑友,王梓展,夏舜晖,等.一种解相关变步长归一化LMS自适应算法[J].计算机工程与科学,2006,28(4):60-62.
[12]贺洪江,王春霞.一种新的LMS自适应滤波算法分析仿真研究[J].传感器与微系统,2012,31(3):15-17.
[13]王晓东.一种分数间隔解相关修正判决反馈盲均衡算法研究[J].航天电子对抗,2012,28(4):56-58.
[14]陆光华,彭学愚,张林让,等.随机信号处理[M].西安:西安电子科技大学出版社,2003:50-57.
[15]HE L,AMIN G,REED C,et al.A Hybrid Adaptive Blind Equalization Algorithm for QAM Signal in Wireless Communications[J].IEEE Trans.On Signal Processing,2004,52(7):2058-2069.
[16]许小东,戴旭初,徐佩霞.适合高阶QAM信号的加权多模盲均衡算法[J].电子与信息学报,2007,29(6):1352-1355.
[17]GARDNER F M.A BPSK/QPSK Timing Error Detector for Sampled Receivers[J].IEEE Transactions on Communications,1986,41(5):998-1008.
[18]张华冲,王晓亚.适用于QAM信号的载波同步与均衡实现[J].无线电工程,2010,40(5):27-29.
[19]李红,雷志勇.基于最大熵谱估计的回波信号检测技术研究[J].半导体光电,2011,32(5):728-732.