Space-time coded MIMO-OFDM systems for wireless communications: Signal detection and channel estimation

Abstract

In this thesis, signal detection and adaptive channel estimation methods are investigated for a space-time block coded (STBC) MIMO-OFDM scheme. At the receiver, signals from different co-channel users are detected using minimum mean squared error (MMSE) interference cancellation (IC) followed by maximum likelihood (ML) decoding. It is shown that the signal detection scheme could be used to increase the system capacity (in terms of number of users or data rate) while improving the error rate performance for each user with some additional decoding complexity. Simulation results are compared with theoretical error bounds. Performance of the joint interference cancellation and decoding scheme is also investigated on an OFDM based WLAN system. An adaptive channel estimation method based on recursive least square (RLS) algorithm is proposed for MIMO-OFDM scheme. It is shown that the proposed channel estimation method is efficient in terms of complexity and bandwidth requirement. The complexity is reduced by adaptively estimating the time domain channel parameter matrix without using any matrix inversion. The adaptive channel estimator is shown to perform quite close to the system where ideal channel state information is available.