This thesis aims to study the performance of adaptive resource allocation in the downlink of multiuse OFDM systems with fixed or varialbe rate requirements (with fairness consideration) as well as low complexity algorithms for real-time implementations in practical systems.
We first verify the simplifying assumption of flat transmit power over the entire bandwidth. Two different optimal and suboptimal power allocation schemes are applied in a single-user system and the decrease in the total throughput due to the presence of the power mask on subcarriers is measured. Based on the comparison of the achieved data rates, a flat transmit power is then assumed in the proposed suboptimal multiuser resource allocation algorithms. Two suboptimal resource allocation algorithms are then proposed using this simplifying assumption. The objective of the first algorithm is to maximize the total throughput while maintaining rate proportionality among the users. The proposed suboptimal algorithm prioritizes the user with the highest sensitivity to the subcarrier allocation and the variance over the subchannel gains is sued to define the sensitivity of each user. The second algorithm concerns rate adaptive resource allocation in multiuser OFDM systems with fixed rate constraints for each user. We propose a suboptimal joint subchannel and power allocation algorithm which attempts to maximize the total throughput wihile supporting the users with their minimum rate requirments. The main feature of this algorithm is its low complexity while achieving close to optimum capacity.
Particle Swarm Optimization for Adaptive Resource Allocation in Communication Networks
