The problem of information-theoretic optimal resource allocation for the synchronous single-cell CDMA Gaussian multiple access channel is investigated. Several different cases are analyzed including: optimal sequence allocation without power control, optimal sequence allocation with optimal power control and optimal sequence allocation without power control with equal single user capacities. In order to simplify the mathematical description of the multiple access capacity region, a Cholesky decomposition characterization is introduced and utilized to find the optimal sequence allocation for equal single user capacities. The case of randomly chosen spreading sequences in a large system model, i.e. when number of users and processing gain increase without bounds while maintaining their ratio fixed, is also analyzed. Using this model, the performance of a conventional decision feedback receiver in flat fading channels is analyzed. A sequence allocation scheme that uses two sets of orthogonal users that can be decoded with a very simple decision feedback receiver is analyzed. It is shown that the spectral efficiency of this scheme is very close to the maximal possible. Finally, the issue of imperfect channel state information available at the receiver is discussed and the spectral efficiency loss compared to the perfect channel state information case is evaluated for the optimal multiuser receiver. / Graduate

Parallel interference cancellation for DS-CDMA has been shown to suffer from biased amplitude estimates if a matched-filter estimator is used. The bias magnitude is proportional to the number of interfering users. For heavy system loads, the bias has been shown to adversely effect the accuracy of the interference cancellation process, thereby impairing BER after cancellation. Empirical simulation work has demonstrated that weighting down interference estimates can improve BER performance. This thesis substantiates these BER improvements by modelling and analyzing a soft interference cancellation technique which mitigates the effects of the bias by minimizing BER after cancellation in a bit-synchronous parallel interference cancellation CDMA receiver. We analyze system decision metrics with down-scaled interference estimates and determine both the mean and variance of the biased decision statistics. From these two metric moments, system BER is evaluated, and the optimal interference scaling function which minimizes BER is derived. We demonstrate BER performance enhancements by simulating this soft interference cancellation technique in systems under perfect power control and in the near-far situation. We further discuss the applicability of the results to asynchronous systems. / Master of Science