(Annual Symposium)Time-varying Multi-user Detection Based on Rao-Blackwellised Particle Filtering

Abstract : Traditional multi-user detection methods often assume that the number of active users which is usually considered to be the maximum number of users that the system can contain, is known at the receiver. Under this assumption, conventional methods for multi-user detection can achieve good performance. However, the number of active users as well as their parameters are always unknown and time-varying in practical multi-access communication systems. In this case, the performance of traditional methods is deteriorated. In accordance with this problem, in our paper, a dynamic model of multi-user is established by using random set theory (RST) , after that we can decompose the channel into two parts, one is the discrete part and the other is the continuous part. Through analysing the relationship between the two parts, we can get the state transition probability. And then a time-varying multi-user detector based on Rao-Blackwellised particle filtering (RBPF) algorithm is proposed. Our scheme can sufficiently trace the number of active users and estimate the users' transmitted datas. The simulation results in anti-noise, near-far resistance and system capacity of this algorithm are presented at the end of this paper. Simulating results show that the performance of proposed method is better than that of conventional methods.