Abstract: This paper addresses the problem of frequency offsets and channel gains estimation for a multi-input multi-output (MIMO) system in flat-fading channels. The general case where frequency offsets are possibly different for each transmit antenna is considered. The maximum-likelihood(ML) estimation of the joint frequency offsets and channel gains is investigated, assuming that a training sequence is available. The exact solution to this estimation problem turns out to be too complex as it involves a search over a multi-dimensional domain. To solve this complex estimation problem, a novel joint estimation algorithm for frequency offsets and channel gains is proposed. The new algorithm involves two steps. Frequency offsets are first estimated by the particle swarm optimization(PSO) theory. Then channel gains are estimated by the ML estimator. Simulation results show that the proposed algorithm has a larger frequency offset estimation range than the correlation-based estimation algorithm and asymptotically achieves the Cramer-Rao lower bound (CRLB).

Key words: particle swarm optimization, MIMO, frequency offsets estimation, channel estimation, maximum-likelihood estimation