Abstract
Systems that employ multiple antennas in both the transmitter and the receiver of a wireless system have been shown to promise extraordinary spectral efficiency. Research challenges in this area include the development of efficient coding schemes to increase signal diversity and system robustness, advanced signal processing techniques to improve the modulation/equalization efficiency, and better resource assignment algorithms to share limited spectrum among users requiring different data throughputs. On the other hand, researchers in this field have been eagerly trying to characterize the multiple input multiple output (MIMO) wireless channels in more realistic scenarios hoping to bring the sophisticated MIMO techniques into practical applications in the near future. This thesis present the progress we have made towards designing sophistic space-time signal processing techniques and determining the capacity benefits of multiple antennas under realistic channel scenarios. The thesis contains five results. First, we develop an efficient architecture with blind adaptive coding schemes in a time division duplexing (TDD) system with slow Rayleigh fading frequency-selective MIMO channels. With this method, neither a training sequence nor feedback of channel information is required in the proposed blind approach. Besides, the computational complexity of the proposed scheme is significantly lower than that of the coding scheme described by Raleigh and Cioffi. Second, we point out that blindly using optimal approaches, such as the discrete matrix multi-tone (DMMT) coding scheme proposed by Raleigh and Cioffi, is not necessarily efficient in practice. With this perspective, we develop a low complexity space-time coding scheme, DMMT angle-frequency coding scheme (DMMT-AFCS), for wireless communication systems with clustered multipath channels. Making use of a Fourier precoder to identify and process only the dominant clustered spatial channel structure, we construct the DMMT-AFCS and analyze its performance loss, trade-off of its low complexity. Experimental examples show that, with little sacrifice in system capacity, the computational complexity of the proposed coding scheme is significantly lower than that of the original DMMT coding scheme in realistic wireless channel environments. Third, we extend the notion of the DMMT-AFCS to multiuser wireless scenarios. Instead of employing interference-cancellation-like dirty paper coding (DPC) strategies, we work toward an interference mitigation coding scheme by exploiting only partial channel information. Fourth, we derive the mutual information and the achievable data rate of various MIMO systems with correlated spatial channels. We consider scenarios where the MIMO channel state information is known at the receiver, but only partially known at the transmitter. In a unified approach, we investigate the asymptotic performance, or equivalently the large-system properties, of various point-to-point systems with antenna-array-based MIMO channels having spatial correlations at both the transmitter and the receiver. Fifth, we use the replica method originally developed in statistical physics to investigate the asymptotic sum-rate of a Gaussian antenna-array-based MIMO multiple-access wireless channel having spatial correlations at both the transmitters and the receiver. Furthermore, with the asymptotic solution, we provide an efficient iterative water-filling algorithm to determine the optimum transmit signal covariance matrices when only the slow-varying channel spatial covariance information is available.