粒子滤波盲均衡译码联合算法  

Particle filter algorithm for joint blind equalization and decoding

作　　者：李浩[1] 王润亮[1] 彭华[1] 

机构地区：[1]信息工程大学信息工程学院,河南郑州450002

出　　处：《西安电子科技大学学报》2013年第1期123-128,176,共7页Journal of Xidian University

基　　金：国家自然科学基金资助项目(61072046)

摘　　要：粒子滤波在解决信道盲辨识和盲均衡问题上具有收敛快、抗深衰信道等优势.在粒子滤波盲均衡算法的基础上,依据卷积码的马氏性特点进行建模,提出了一种直接对信息序列做重要性采样的粒子滤波盲均衡和卷积码译码联合算法.同时,提出了噪声功率递推计算的方法,并将其应用于联合算法中噪声功率参数的自适应调整.仿真结果表明,相比分离算法,联合算法的收敛性能和误码率性能都有明显提高,而自适应调整功率参数的算法则降低了运算复杂度.Particle filtering（PF） is particularly useful in dealing with the blind channel identification and blind equalization for its fast convergence and its outstanding performance of resisting multiple-path fading channels.Considering the Markov chain property of convolutional codes,the signal model is modified and a particle filter algorithm for joint blind equalization and decoding of convolutional code is introduced which samples the information sequence directly instead of the coded sequence.An iterative method to approximate the noise power is proposed,which is applied to the joint algorithm to adjust the parameter of noise power adaptively.The proposed algorithm is simulated.The simulation result shows that the convergence of the joint algorithm is faster and the bit error rate（BER） is lower that of the separate algorithm.And the adaptive adjustment algorithm reduces the computational complexity.

关 键 词：粒子滤波 信道盲辨识 盲均衡 联合盲均衡译码 

分 类 号：TN911.5[电子电信—通信与信息系统]