Modeling fairness in resource allocation for secondary users in a competitive cognitive radio network

Abstract

We consider a multi-channel cognitive radio network (CRN) where multiple secondary users share a single channel and multiple channels are simultaneously used by a single secondary user (SU) to satisfy their rate requirements. In this competitive CRN, our interest is in determining optimal power and rate distribution choices for each SU while maintaining fairness in “quality of experience” across all SUs. Unlike prior approaches that focus on resource allocation based on instantaneous quality of service (QoS), our approach to fairness encompasses both current and prior history of user experience with respect to QoS. Specifically, we quantify user experience over time by introducing dynamic fairness weights for each SU in the resource allocation framework. The dynamics of the weights are governed by the Homo Egualis (HE) society model. We consider Jain system level fairness index [1] as a measure of fairness in resource allocation. Simulation results show that the weighted resource allocation scheme provide a better system level fairness index relative to the unweighted allocation scheme.