OFDMA上行系统中基于随机集理论的多用户信道估计

摘要

For the uplink OFDMA systems, a random-set theory based multi-user channel estimation algorithm was proposed. In the proposed algorithm, states of the users and the multi-path channels were modeled and described by a finite random set. Then the Bayes filtering was utilized to formulate the problem of multi-user channel estimation. To obtain both the accepted channel estimation performance and low computational complexity, the Rao-Blackwellized particle filtering algorithm was applied to approximately solve this Bayes filtering problem with small number of particles. Simulation results show the effectiveness of the proposed algorithm.%针对正交频分多址(OFDMA)上行系统,提出一种基于随机集理论的导频辅助多用户信道估计算法.该算法利用有限随机集合来建模和表示OFDMA上行系统中的用户状态、各用户对应的多径信道状态以及信道冲激响应等未知量,采用贝叶斯滤波理论来描述多用户信道估计问题,通过使用Rao-Blackwellized粒子滤波算法,实现了活动用户数和信道多径数动态变化情况下的多用户时变信道估计.计算机仿真结果证明了该算法的有效性.