粒子滤波在无线通信中的应用综述

粒子滤波是一种基于贝叶斯原理的序贯Monte-Carlo方法。序贯重要性采样（SIS）算法是粒子滤波的核心算法。粒子滤波算法在处理非线性、非高斯系统的状态估计问题上优于其他滤波方法。本文对粒子滤波算法的基本原理及其在无线通信中的应用进行综述,重点介绍其中的几种典型应用：在盲均衡、衰落信道下的盲检测、多用户检测和衰落信道下的空时解码中的应用,并分别给出了每种应用的状态空间模型、权值更新公式和算法应用过程,并从性能、复杂度和适应性的角度分析了粒子滤波的应用优势。最后展望该算法在无线通信领域应用的发展方向。

Application of Particle Filtering in the Wireless Communication

Particle filtering is based on the concept of sequential importance sampling and the Bayesian theory, it is particularly useful in dealing with nonlinear and non-Gaussian problems. This paper presents the applications of particle filtering in the wireless communication such as blind equalization, blind detection over flat fading channels, multiuser detection and estimation of space-time codes in fading channels. In each case, the system model and the updating of the particle weights are discussed.