基于粒子滤波算法的DS-CDMA多用户检测

粒子滤波算法是一种基于贝叶斯估计的蒙特卡罗方法,尤其适用于处理非线性、非高斯系统的状态估计问题。该算法应用于DS-CDMA系统的多用户检测中,检测器能在检测性能和计算复杂度之间取得很好的平衡。基于粒子滤波算法的多用户检测器在性能上逼近于最优多用户检测器,而计算复杂度远低于最优多用户检测器,与次优多用户检测器相当。利用白化匹配滤波器的输出可以建立同步DS-CDMA系统的状态空间方程,使得粒子滤波算法应用于多用户检测中。仿真实例证明了基于粒子滤波算法的多用户检测器在等功率和远近效应的情况下的性能优势。

DS-CDMA Multiuser Detection Based on Particle Filter

Based on the method of Monte-Carlo and the use of Bayesian theory,particle filtering is particularly useful in dealing with nonlinear and non-Gaussian problems.Applying particle filter to multiuser detection (MUD) can find a balance between the performance of the detector and its computational complexity.The performance of CDMA multiuser detectors with particle filter is close to that of optimum detectors,but with lower computational complexity,which is equal to that of some suboptimum detectors.In this paper,WMF outputs are utilized for the system representation,and then it is shown how particle filter is used for multiuser detection.As a result,a near optimum performance is observed in simulations both in the equal power case and the near-far case.Further studies are mentioned in the conclusion part.