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

Fateh Elsherif, Edwin K.P. Chong, Jeong Ho Kim

Research output: Contribution to journalArticlepeer-review

22 Scopus citations


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.

Original languageEnglish
Article number8777099
Pages (from-to)9267-9279
Number of pages13
JournalIEEE Transactions on Vehicular Technology
Issue number9
StatePublished - Sep 2019

Bibliographical note

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  • 5G
  • Green communication
  • MDP
  • energy saving
  • network optimization
  • real-time control
  • user mobility


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