The objective of this thesis is to implement and evaluate dynamic resource allocation algorithms that adjust the fairness of an OFDMA network. We consider the category of Rate Adaptive algorithms where the Base Station is assumed to transmit at full power and under this condition we try either to maximize the throughput of the system or to maximize the minimum rate of the users. The novelty within the implemented algorithms lies in the adaptive adjustment of the system fairness, an index that shows how fair the throughput of the system is split to the users. The adjustment is performed in general by reallocations of channels and power. Two approaches of adjusting the system fairness were implemented: The Fairness based Sum Rate Maximization with Proportionalities (FSRM-P) and the Fairness Based Max-Min Rate (FMMR). For each approach we initially formulate the optimization problem and then we evaluate three solutions. Because of the non-convex nature of the problems, the proposed novel solutions are iterative, heuristic and in general suboptimal. The evaluation is performed by considering the downlink of a single OFDMA cell serving a set of users which have different rate requirements. The algorithms whether an increase or decrease of the fairness is required, are able to meet the target. However this always comes at the cost of an opposite effect on throughput. Simulations results showed that for the same value of system fairness, the FSRM-P performs better in terms of throughput while the FMMR is able to be fairer with the users. Moreover, in most cases the FMMR achieves higher user satisfaction, however when the rate requirements of the users are increased the satisfaction drops to lower levels than the FSRM-P.