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Research on Channel Estimation and OFDM Signals Detection in Rapidly Time-Variant Channels

It is well known that iterative channel estimation and OFDM signals detection can significantly improve the performance of communication system. However, its performance is poor due to the modelling error of basis expansion model (BEM) being large enough and can not being ignored in rapidly time-variant channels. In this paper, channel estimation and OFDM signals detection are integrated into a real non-linear least squares (NLS) problem. Then the modified Broyden-Fletcher-Goldfarb-Shanno (MBFGS) algorithm is adopted to search the optimal solution. In addition, Cramer-Rao Bound (CRB) for our proposed approach is derived. Simulation results are presented to illustrate the superiority of the proposed approach.