Energy-efficient game-theoretical random access for M2M communications in overlapped cellular networks

Zhenyu Zhou, Junhao Feng, Yunjian Jia*, Shahid Mumtaz, Jonathan Rodriguez, Di Zhang, Kazi Mohammed Saidul Huq

*Corresponding author for this work

Research output: Contribution to journalArticlepeer-review


The unprecedented growth of machine-to-machine (M2M) devices has brought a heavy burden to traditional cellular networks. In this paper, we focus on the overload problem caused by massive connections of M2M devices in overlapped cellular networks. We formulate the joint base station (BS) selection and power allocation optimization problem for each M2M device as a noncooperative access game. The utility function of each M2M device is described as the success probability of random access weighted by the energy efficiency (EE). We propose an iterative energy-efficient game-theoretical random access algorithm, in which each M2M device searches its optimal strategies in turn until no M2M device is able to improve its individual utility with a unilateral deviation. Numerical results demonstrate that significant performance enhancements on both the delay and energy consumption can be achieved simultaneously.

Original languageEnglish
Article numberS1389128617302633
Pages (from-to)1339-1351
Number of pages13
JournalComputer Networks
Issue numberPart 2
Publication statusPublished - 24 Dec 2017


  • Energy efficiency
  • M2M communications
  • Multi-cellular networks
  • Noncooperative game theory
  • Random access


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