Abstract:
The typical pilot-aided and blind estimation method for MIMO-OFDM channel can achieve good performance when the number of multi-path components is constant. However, in the practical wireless environment, the number of channel taps and amplitude are all unknown and time-varying in whole process, thus typical estimation methods are not suitable. In this paper, the channel-taps varying condition and a new channel model are established by using RST theory. Based on this model, the re-sample method by Concentrating particle Resample Space (CRS) is proposed. By abandoning low probability samples and reserving high probability samples, more accurate approximation is obtained at each iteration. And then the channel estimation method using Rao-Blackwellised Particle Filtering with CRS (RBPFC) is proposed. Simulation results show that the performance of RBPFC is the best, the performance of Rao-Blackwellised particle filtering scheme follows but is better than that of the basic particle filtering scheme, and the performance of Kalman filter-based scheme is the worst.