Energy-Efficient Base Station Control Framework for 5G Cellular Networks Based on Markov Decision Process

Abstract

We study the problem of base station (BS) dynamic switching for energy efficient design of fifth-generation (5G) cellular networks and beyond. We formulate this problem as a Markov decision process (MDP) and use an approximation method known as policy rollout to solve it. This method employs Monte Carlo sampling to approximate the Q-value. In this paper, we introduce a novel approach to design an energy-efficient BS control algorithm. We design an MDP-based algorithm to control the on/off switching of BSs in real time; we exploit user mobility and location information in the selection of the optimal control actions. We start our formulation with the simple case of one-user one-ON. We then gradually and systematically extend this formulation to the multi-user multi-ON scenario. Simulation results show the potential of our novel approach of exploiting user mobility information within the MDP framework to achieve significant energy savings while providing quality-of-service guarantees.