Distributed energy-efficient resource allocation with fairness in wireless multicell OFDMA networks

Abstract

High-data-rate applications operating wirelessly can greatly increase energy consumption of wireless networks. Therefore, energy-efficient (EE) resource allocation in wireless networks is an emerging research topic. Fairness is largely ignored in existing work on EE resource allocation in multicell OFDMA networks. We propose a distributed EE resource allocation scheme, taking user fairness and priority into consideration. Moreover, unlike existing resource allocation work that often only considers instantaneous data rates, we consider average data rates, which are more appropriate from the users' perspective. We transform the EE resource allocation with fairness optimization problem from fractional to equivalent subtractive form, which is subsequently modeled as a non-cooperative game. Interference pricing functions are used to drive the Nash equilibrium (NE) to Pareto optimal. Simulation results show the effectiveness of the proposed scheme on energy efficiency and user fairness.