Energy-efficient subcarrier optimization scheme based on particle swarm for green radio wireless networks

Abstract

The growing awareness towards energy efficient cellular networks has paved way for new technologies to enable design towards green cellular networks. According to technical analysts, the base stations are the most energy intensive element in a typical cellular network. Saving power in base stations is therefore the primary focus in green cellular networks. The main goal of designing green base stations is for saving energy and reducing power consumption while guaranteeing service and coverage for users and ensuring the capability of base station for evolution. One cannot ignore the amount of energy that is wasted due to the lack of efficient utilization of resources. This was the main motivation behind this study. This paper aims to exploit the dynamic traffic load conditions to improve the downlink energy consumption by achieving optimal balancing between the number of subcarriers and dynamic traffic load conditions. Particle Swarm Optimization (PSO) has been adopted to optimize the subcarriers under the condition of maximum traffic load while guaranteeing the QOS under the constraint of minimal power per subcarrier. Simulation results show that the annual energy savings that achieved by this approach only for one base station up to 130 kWh. Hence, in a large area with thousands of base stations or even more, the aggregate energy savings could be substantial as well as the annual OPEX saving.