Spatial interference cancellation and channel estimation for multiple-input multiple-output wireless communication systems

Abstract

A multiple-input multiple-output (MIMO) wireless communication system is one of prominent systems for realizing high data-rate transmission services highly demanded in the future wireless communications. It can provide a significant performance enhancement to the wireless communications, including increased data rates through a multiplexing gain, an enhanced error probability through a diversity gain, and cancellation of multiple access interference through smart antennas. However, for such system employing coherent receivers, an accurate channel state information is crucially needed. These performance advantages and challenge, respectively, are the motivations of this dissertation. In the first part of this dissertation, a novel smart antenna system for interference canceling receivers in direct-sequence code-division multiple access (DS-CDMA) systems is proposed. This proposed scheme only exploits the spreading codes of users as the information forits weight adjustment for controlling its beam. This proposed scheme is also robust to the in-beam interference, especially in the near-far effect situation. Convergence and error probability performance analysis is also carried out. Theoretical and simulation results indicate that the proposed scheme outperforms the existing works. In the second part of this dissertation, novel channel estimators for space-time (ST) coded MIMO systems and for space-frequency coded MIMO-orthogonal frequency-division multiplexing (OFDM) systems are proposed, respectively. For the first systems, the novel pilot-embedding approach for joint channel estimation and data detection is first proposed. The unconstrained maximum likelihood (ML) and linear minimum mean square error (LMMSE) channel estimators are then proposed. Mean square error (MSE) of the channel estimation, Cramer-Rao lower bound, and Chernoff's bound of bit error rate for ST codes are analyzed for examining the proposed scheme's performances. The optimum power allocation is also investigated. Theoretical and simulation results show that a code-multiplexing based structure for the data-bearer and pilot matrices is the best among all other structures for nonquasi-static channels. For the second systems, a generalization of the proposed pilot-embedding scheme as well as the corresponding least square (LS) channel estimation and ML data detection are first proposed. Then, LS and adaptive LS FFT-based channel estimators are proposed to improve the performance of such channel estimator. The effect of model mismatch error for non-integer multipath delay profiles and MSE of these channel estimators are analyzed. The optimum number of taps for the adaptive LS FFT-based channel estimator is also determined. Theoretical and simulation results indicate that the adaptive LS FFT-based channel estimator is the best among all other channel estimators