Joint Estimation of Spreading Codes and Information Sequences for Asynchronous Long Code DS-CDMA Signals Based on Sequential Monte Carlo
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摘要: 针对多径信道环境下非同步长码DS-CDMA信号扩频码及信息序列等参数的联合估计问题，该文提出了基于序贯蒙特卡罗(SMC)的盲估计算法。该算法采用混合重要密度函数对联合后验分布模型进行抽样，并迭代计算重要性权值，以完成所需状态参量的估计。同时为了减少算法的计算量，在算法的实现过程中，先估计出各用户的扩频码，再对观测数据进行处理，从而修正原有的迭代步骤，提出一种修正的SMC算法。仿真结果验证了算法对多种情况的适应性，且在时变的多径信道环境下也能获得较好的估计性能。Abstract: To deal with the problem of joint estimation of spreading codes and information sequences for asynchronous long code DS-CDMA signals in multipath channels, an algorithm is introduced based on Sequential Monte Carlo(SMC) for blind estimation. The proposed algorithm emploies hybrid important sampling density to draw the samples from joint posterior distribution iteratively, and computes the importance weight to complete the estimation of the state variable. During the realization of the algorithm, in order to reduce the computational complexity, the modified algorithm estimates the spreading code of each user firstly, then processes the observation data, thereby modifies the original iteration step. Simulation results verify the adaptability of the proposed algorithms for multiple conditions. Moreover, it can obtain good estimation performance in time varying multipath channels.
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