Vol.35, No.1, 2023, pp.811-826, doi:10.32604/iasc.2023.026523
Base Station Energy Management in 5G Networks Using Wide Range Control Optimization
  • J. Premalatha*, A. SahayaAnselin Nisha
Department of Electronics and Communication Engineering, Sathyabama Institue of Science and Technology, Chennai, 600119, India
* Corresponding Author: J. Premalatha. Email:
Received 29 December 2021; Accepted 13 March 2022; Issue published 06 June 2022
The traffic activity of fifth generation (5G) networks demand for new energy management techniques that is dynamic deep and longer duration of sleep as compared to the fourth generation (4G) network technologies that demand always for varied control and data signalling based on control base station (CBS) and data base station (DBS). Hence, this paper discusses the energy management in wireless cellular networks using wide range of control for twice the reduction in energy conservation in non-standalone deployment of 5G network. As the new radio (NR) based 5G network is configured to transmit signal blocks for every 20 ms, the proposed algorithm implements withstanding capacity of on or off based energy switching, which in-turn operates in wide range control by carrying out reduced computational complexity. The proposed Wide range of control for base station in green cellular network using sleep mode for switch (WGCNS) algorithm toon and off the base station will work in heavy load with neighbouring base station. For reducing the overhead duration in air, heuristic versions of the algorithm are proposed at the base station. The algorithm operates based on the specification with suggested protocol-level to give best amount of energy savings. The proposed algorithm reduces 40% to 83% of residual energy based on the traffic pattern of the urban scenario.
5G base station; energy management; energy saving; traffic pattern; sleep mode
Cite This Article
J. Premalatha and A. SahayaAnselin Nisha, "Base station energy management in 5g networks using wide range control optimization," Intelligent Automation & Soft Computing, vol. 35, no.1, pp. 811–826, 2023.
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