Energy-efficient scheduling of small cells in 5G: A meta-heuristic approach

Md Shahin Alom Shuvo, Md Azad Rahaman Munna, Sujan Sarker, Tamal Adhikary, Md Abdur Razzaque, Mohammad Mehedi Hassan, Gianluca Aloi, Giancarlo Fortino

Research output: Contribution to journalJournal articlepeer-review

4 Scopus citations

Abstract

Scheduling of small cells in Fifth-Generation (5G) mobile network is highly important for achieving energy-efficiency and providing Quality of Service (QoS) to the applications users. Minimization of energy consumption hampers QoS. This problem has been further complicated due to exponential increase of mobile application users demanding high data rate. The performances of energy-saving approaches in the literature are limited by the fact that they exploit mere historical data-driven two state operation modes of small cells. This paper formulates the problem of scheduling small cells as a non-linear optimization problem. It then offers a meta-heuristic evolutionary algorithm to solve the problem in polynomial time. The proposed algorithm takes into account four operation states of small cells to minimize the energy consumption while satisfying the users’ QoS. The results of our performance analysis depict that the proposed algorithm outperforms the state-of-the-art works in terms of energy-saving, switching delay, etc.

Original languageEnglish
Article number102986
JournalJournal of Network and Computer Applications
Volume178
DOIs
StatePublished - 15 Mar 2021

Keywords

  • Energy-efficiency
  • Genetic algorithm
  • HetNet
  • Minimize energy
  • Scheduling
  • Small cell
  • State switching delay

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