Sequence estimation with transmit diversity for wireless communications

Abstract

In this paper, an optimum sequence estimation algorithm for wireless systems with Alamouti's two transmitter diversity in the presence of multipath fading is proposed. The algorithm is based on a jointly iterative channel and sequence estimation according to the maximum likelihood (ML) criterion, using the Expectation-Maximization (EM) algorithm employing an M-level phase-shift keying (M-PSK) modulation scheme with additive Gaussian noise. The discrete multipath channel is represented in terms of the channel gains from each transmit antenna to the receive antenna. EM algorithm estimates jointly the complex channel parameters of each channel and the data sequence transmitted, iteratively, which converges to the true ML solution. The channel estimation is achieved in a simple way through the iterative equations by decoupling of the signals transmitted from different antennas. The algorithm is applied to the trellis coded modulation systems and the efficiency of the algorithm proposed has been shown with computer simulations. The simulation results show that the EM algorithm converges quickly for fast fading channels. The performance of the EM-based decoder approaches that of the ML receiver which has perfect knowledge of the channel.