基于MCMC的CDMA系统联合激活用户识别和信道估计  

Joint Active User Identification and Channel Estimation Using MCMC Methods in CDMA System

作　　者：陈亮辉[1] 胡捍英[1] 

机构地区：[1]解放军信息工程大学通信工程系,郑州450002

出　　处：《数据采集与处理》2009年第4期418-422,共5页Journal of Data Acquisition and Processing

基　　金：国防预研基金(40901010201)资助项目

摘　　要：用户激活参数和信道参数影响了CDMA系统多用户检测算法的性能。根据CDMA接收信号表达式,把接收信号看作以用户激活数和用户路径数为参数的被噪声污染的复合Poisson过程,利用信道脉冲响应疏状特性,把信道脉冲响应建模为Bernoulli-Gaussian过程,然后使用马尔科夫-蒙特卡罗仿真技术求出参数后验概率分布最优化解,实现联合激活用户识别和信道参数估计。由于考虑了匹配滤波后增强的噪声相关性,仿真结果表明,在相同信噪比下基于马尔科夫-蒙特卡罗仿真算法估计误差性能优于期望最大化算法和迭代条件模算法。The performance of multi-user detection （MUD） algorithm in CDMA system is affected by parameters of the active user and the channel. The received signal can be viewed as a noise polluted complex Poisson process with parameters of the active user and their paths. By modeling the channel pulse response as a Bernoulli-Gaussian process based on the character of sparse, the optimization of the posterior distribution by Markov Chain Monte Carlo （MCMC） simulation techniques is derived, and the joint active user identification and the channel estimation are achieved. Considering the enhanced noise correlation after match filtering, simulating results show that under the condition of the same SNR, the performance of MCMC simulation algorithm is better than that of expectation-maximization （EM） and the iterated conditional mode （ICM） algorithms.

关 键 词：复合POISSON过程 激活用户识别 信道估计 MCMC算法 

分 类 号：TN911.72[电子电信—通信与信息系统]