针对相位噪声的广义软判决辅助相位估计算法  

Generalized soft-decision-aided phase estimation for phase noise

作　　者：吕心浩 李焱 张浩波 周武杰[1] 吴茗蔚[1,3] LYU Xinhao;LI Yan;ZHANG Haobo;ZHOU Wujie;WU Mingwei(School of Information and Electronic Engineering,Zhejiang University of Science and Technology,Hangzhou 310023,Zhejiang,China;Centre of Advanced Microelectronic Devices,National University of Singapore (Suzhou) Research Institute,Suzhou 215123,Jiangsu,China;Zhejiang Provincial Key Laboratory of Information Processing,Communication and Networking,Hangzhou 310027,Zhejiang,China)

机构地区：[1]浙江科技学院信息与电子工程学院,杭州310023 [2]苏州工业园区新国大研究院先进微电子器件中心,江苏苏州215123 [3]浙江省信息处理与通信网络重点实验室,杭州310027

出　　处：《浙江科技学院学报》2019年第5期365-372,共8页Journal of Zhejiang University of Science and Technology

基　　金：国家自然科学基金项目(61302112,61571316);教育部留学回国人员科研启动基金项目(教外司留[2013]1792号);浙江科技学院“科大青年英才”项目(浙科院人[2014]9号);浙江省信息处理与通信网络重点实验室开放课题(IPCAN-1806)

摘　　要：判决辅助最大似然(DA-ML)和软判决辅助最大似然(SDA-ML)载波相位估计器均假定静态分块载波相位,因此在高信噪比下会出现误差下限。通过引入多元高斯分布模型,提出广义SDA-ML相位估计算法,并通过分解信道协方差矩阵来降低计算复杂度。仿真试验结果表明,对于高阶QAM调制,广义SDA-ML可以显著降低DA-ML和传统SDA-ML的误差下限。Both decision-aided maximum likelihood(DA-ML) and soft DA-ML(SDA-ML)carrier phase estimators assume block-wise static carrier phase,therefore an error floor tends to arise at high signal-to-noise ratio(SNR). A generalized SDA-ML phase estimation was proposed by introducing a multi-dimensional Gaussian distribution model,with the computational complexity being reduced by decomposing the channel covariance matrix. Simulation results show that the generalized SDA-ML can significantly reduce the error floor of DA-ML and the conventional SDA-ML,for high-order quadrature amplitude modulation(QAM).

关 键 词：相干光通信 最大似然 相位估计 软判决辅助 

分 类 号：TN929.11[电子电信—通信与信息系统]