Fairness adaptive resource allocation in OFDMA networks

Abstract

This thesis work reviews contributions regarding dynamic resource allocation problems in Orthogonal Frequency Division Multiplexing (OFDM) systems, where various system metrics can be improved by periodically reassigning sub-carriers and transmit power to terminals depending on their current channel state. The following three classical problems have been reviewed: a) the sum rate maximization problem, b) the max min rate problem, and c) the sum rate maximization with rate proportionalities. System capacity is maximized in (a), by providing optimal spectral efficiency, but also poor system fairness index. In (b) and (c), fairness is very high but the capacity and spectral efficiency have been limited due to the fair policy; so the system capacity versus fairness trade off has been highlighted. The novel contribution of this thesis work is the formulation of a new problem which includes a system fairness target constraint enabling operators the ability to adjust fairness level. Operators, according to their needs, can get the most of spectral efficiency while providing a certain level of fairness among users. Several novel results regarding the new problem of system capacity maximization with a system fairness target constraint and various comparisons of different sub-optimal fairness-adaptive algorithm families are presented in this work. From the simulation results, including metrics such as system capacity, user fairness, user satisfaction and computational demand, it was possible to conclude about the most efficient fairness-adaptive approach from the perspective of both the user and the operator.