西安电子科技大学学报（自然科学版）2013，Vol.40Issue(1)：123-128,176,7.DOI:10.3969/j.issn.1001-2400.2013.01.022
粒子滤波盲均衡译码联合算法
Particle filter algorithm for joint blind equalization and decoding
摘要
Abstract
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 tre computational complexity.关键词
粒子滤波/信道盲辨识/盲均衡/联合盲均衡译码Key words
particle filtering/ blind channel identification/ blind equalization/ joint blind equalization and decoding分类
信息技术与安全科学引用本文复制引用
李浩,王润亮,彭华..粒子滤波盲均衡译码联合算法[J].西安电子科技大学学报（自然科学版）,2013,40(1):123-128,176,7.基金项目
国家自然科学基金资助项目(61072046) （61072046）
