Balancing Spectral Efficiency, Energy Consumption, and Fairness in Future Heterogeneous Wireless Systems with Reconfigurable Devices

Abstract

In this paper, we present an approach to managing resources in a large-scale heterogeneous wireless network that supports reconfigurable devices. The system under study embodies internetworking concepts requiring independent wireless networks to cooperate in order to provide a unified network to users. We propose a multi-attribute scheduling algorithm implemented by a central Global Resource Controller (GRC) that manages the resources of several different autonomous wireless systems. The attributes considered by the multi-attribute optimization function consist of system spectral efficiency, battery lifetime of each user (or overall energy consumption), and instantaneous and long-term fairness for each user in the system. To compute the relative importance of each attribute, we use the Analytical Hierarchy Process (AHP) that takes interview responses from wireless network providers as input and generates weight assignments for each attribute in our optimization problem. Through Matlab/CPLEX based simulations, we show an increase in a multi-attribute system utility measure of up to 57% for our algorithm compared to other widely studied resource allocation algorithms including Max-Sum Rate, Proportional Fair, Max-Min Fair and Min Power.