In this thesis we study the subject of resource allocation for uplink communication systems.
When users have target rate constraints and interference cancelation is used at the base station we provide the optimal decoding order and power allocation in order to minimize the power consumption. In addition, conditions are derived under which the allocation can be done in a distributed way, with only some knowledge of the statistics of the system.
We then proceed to consider multiple-input multiple-output (MIMO) systems, and obtain the optimal precoding matrices such that each user maximizes its own ergodic transmission rate from the sole knowledge of the overall channel statistics. The benefits of using a coordination signal and successive decoding are analyzed.
Next, a scenario in which mobile terminals can be simultaneously connected to several base stations, using non-overlapping frequency bands is investigated. The optimal power allocation in terms of sum rate is derived for different receiver types and an iterative algorithm proposed to achieve the optimal allocation.
Finally, we consider decentralized medium-access control in which many pairwise interactions, where users compete for a medium access opportunity, occur between randomly selected users that belong to a large population. The choice of power level is done by each user, and both team and noncooperative scenarios are analyzed.