In this thesis we investigate different algorithms for dynamic resource allocation in wireless networks. We introduce a general framework for modeling systems whichis applicable to many scenarios. We also analyze a specific scenario with adaptivebeamforming and show how it fits into the proposed framework. We then studytwo different resource allocation problems: Quality-of-Service (QoS) constraineduser scheduling and sum-rate maximization. For user scheduling, we select some“good” set of users that is allowed to use a specific resource. We investigatedifferent algorithms with varying complexities. For the sum-rate maximizationwe find the global optimum through an algorithm that takes advantage of thestructure of the problem by reformulating it as a D.C. program, i.e., a minimizationover a difference of convex functions. We validate this approach by showing that itis more efficient than an exhaustive search at exploring the space of solutions. Thealgorithm provides a good benchmark for more suboptimal algorithms to comparewith. The framework in which we construct the algorithm, apart from being verygeneral, is also very flexible and can be used to implement other low complexitybut suboptimal algorithms.