Original scientific paper
https://doi.org/10.32985/ijeces.15.5.6
Performance Measurement of Small Cell Power Management Mechanism in 5G Cellular Networks using Firefly Algorithm
J. Premalatha
; Department of Electronics and Communication Engineering, Sathyabama Institute of Science and Technology, Chennai 600 119.
*
A. Sahaya Anselin Nisha
; Department of Electronics and Communication Engineering, Sathyabama Institute of Science and Technology, Chennai 600 119.
Sanjaikanth E Vadakkethil Somanathan Pillai
; School of Electrical Engineering and Computer Science, University of North Dakota, Grand Forks, North Dakota, USA.
A. Bhuvanesh
; Department of Electrical and Electronics Engineering, PSN College of Engineering and Technology, Tirunelveli 627 152.
* Corresponding author.
Abstract
In cellular networks, with the increase in demand, designing a base station (BS) with less energy consumption remains a challenge for researchers. Also, in a heterogeneous network that is dense in nature, the distribution of numerous small BS has become a challenging issue in terms of expanding the cost of energy. In this paper, we investigate an optimized nature-based cluster sleep technique for reducing the power consumption in the BS as well as the interference in the network. The small BS are grouped along with the interference, which is assumed to be the cluster, which is quite large, where the fire fly (FF) algorithm is applied to frame the sleep technique for the small BS. These FF algorithms, which are based on fire fly attractiveness behavior, improve connectivity among the base stations in an energy-efficient way. The outcomes reveal that the projected sleep technique with the FF algorithm reduces the power consumed by the BS and also gives satisfactory performance for mobile users. The results were compared with the other techniques, such as BS conventional sleep mode and BS sleep mode with LEACH. The proposed method outperformed the other techniques.
Keywords
Firefly algorithm; Base station; sleeps technique; power consumption; heterogeneous network;
Hrčak ID:
316788
URI
Publication date:
13.5.2024.
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