The proliferation of services involving the transmission of high rate data traffic over wireless channels makes it essential to overcome the detrimental effects of the wireless medium, such as fading and multiuser interference. This thesis is devoted to obtaining optimal resource allocation policies which exploit the transmitters' and receiver's knowledge about the fading to the network's advantage, to attain information theoretic capacity limits of fading wireless channels.

The major focus of the thesis is on capacity results for fading code division multiple access (CDMA) channels, which have proved to be a robust way of combatting the multiuser interference in practical wireless networks. For these channels, we obtain the capacity region achievable with power control, as well as the power control policies that achieve the desired rate points on the capacity region. We provide practical one-user-at-a-time iterative algorithms to compute the optimal power distributions as functions of the fading. For the special case of sum capacity, some properties of the optimal policy, such as the number of simultaneously transmitting users, are obtained. We also investigate the effects of limited feedback on the capacity, and demonstrate that very coarse channel state information (CSI) is sufficient to benefit from power control as a means of increasing the capacity.

The selection of the signature sequences also plays an important role in determining the capacity of CDMA systems. This thesis addresses the problem of jointly optimizing the signature sequences and power levels to maximize the sum capacity. The resulting policies are shown to be simple, consisting of orthogonal transmissions in time or signal space, and requiring only local CSI. We also provide an iterative way of updating the joint resource allocation policy, and extend our results to asynchronous, and multi-antenna CDMA systems.

Rather than treating the received signal at the transmitters as interference, it is possible to treat it as free side information and use it for cooperation. The final part of the thesis provides power allocation policies for a fading Gaussian multiple access channel with user cooperation, which maximize the rates achievable by block Markov superposition coding, and also simplify the coding strategy.