Asymptotic techniques for space and multi-user diversity analysis in wireless communications

To establish reliable wireless communication links it is critical to devise schemes to mitigate the effects of the fading channel. In this regard, this dissertation analyzes two types of systems: point-to-point, and multiuser systems. For point-to-point systems with multiple antennas, switch and stay diversity combining offers a substantial complexity reduction for a modest loss in performance as compared to systems that implement selection diversity. For the first time, the design and performance of space-time coded multiple antenna systems that employ switch and stay combining at the receiver is considered. Novel switching algorithms are proposed and upper bounds on the pairwise error probability are derived for different assumptions on channel availability at the receiver. It is proved that full spatial diversity is achieved when the optimal switching threshold is used. Power distribution between training and data codewords is optimized to minimize the loss suffered due to channel estimation error. Further, code design criteria are developed for differential systems. Also, for the special case of two transmit antennas, new codes are designed for the differential scheme. These proposed codes are shown to perform significantly better than existing codes. For multiuser systems, unlike the models analyzed in literature, multiuser diversity is studied when the number of users in the system is random. The error rate is proved to be a completely monotone function of the number of users, while the throughput is shown to have a completely monotone derivative. Using this it is shown that randomization of the number of users always leads to deterioration of performance. Further, using Laplace transform ordering of random variables, a method for comparison of system performance for different user distributions is provided. For Poisson users, the error rates of the fixed and random number of users are shown to asymptotically approach each other for large average number of users. In contrast, for a finite average number of users and high SNR, it is found that randomization of the number of users deteriorates performance significantly.