2024
doi: 10.12720/jait.15.5.672-681
Smart 5G Small Cell Mobile Networking with Sleep Strategy Using Novel Swarm Optimization
Narasimha Rao Yamarthi1,*
,
Padma Yenuga2 ,
Srikanth Meda3 ,
Lakshmi Tulasi R3 ,
Venkata Anusha Kolluru4 ,
Satish Kumar Patnala5 ,
Bujji Babu Dasari6 ,
Lakshmi Naga Jayaparada G7 ,
Om Prakash Samantray8 ,
Narasimha Reddy K V9 ,
Kunda Suresh Babu9 ,
Lalitha Kumari Pappala1
- 1School of Computer Science and Engineering, VIT-AP University, Amaravati, India
- 2Department of Information Technology, Prasad V. Potluri Siddhartha Institute of Technology, Vijayawada, India
- 3Department of Computer Science and Engineering, RVR&JC College of Engineering, Guntur, India
- 4Department of Computer Science and Engineering (AI&ML), RVR&JC College of Engineering, Guntur, India
- 5Department of IT, Anil Neerukonda Institute of Technology and Sciences, Visakhapatnam, India
- 6Department of Computer Science and Engineering, QIS College of Engineering and Technology, Ongole, India
- 7Department of CSE, Malla Reddy College of Engineering and Technology, Secunderabad, Telangana, India
- 8Department of Computer Science and Engineering, Raghu Engineering College, Visakhapatnam, India
- 9Department of Computer Science and Engineering, Narasaraopet Engineering College, Narasaraopet, India
- Manuscript receivedOctober 23, 2023
- revisedDecember 25, 2023
- acceptedJanuary 9, 2024
- publishedMay 28, 2024
Abstract
Due to its major contribution to the overall energy consumption in Information and Communication Technologies (ICT), lowering the energy consumption of mobile communication networks has attracted a lot of attention. This study presents the implementation of a 5G network model based on heterogeneity, employing macro cells and small cells, in conjunction with diverse users and control techniques. In this work, the analysis is performed between the consumption of energy and the performance of users in the cellular networks. The objective is to address the identified problem which is related to energy conservation and proposed a solution utilizing the Modified Particle Swarm Optimization (MPSO) algorithm, which is then compared with the existing Iterative Optimization Algorithm (IOA). The sleep strategy involved in this work helps to save energy by overlapping the cells. The evaluation of the implemented solution focuses on various parameters, including contract rate, power, earnings, and energy efficiency. Comparing the outcomes achieved through the two optimization algorithms, the MPSO-based evaluation demonstrates superior performance over the iterative optimization algorithm in terms of energy efficiency and power consumption. Before applying sleep strategy, the energy efficiency is 2.6%, after applying sleep strategy with IOA having 4% and with suggested approach efficiency is obtained is 6%. The evaluation is conducted using the Matlab software tool.
Keywords
- 5G technology
- base station
- sleep strategy
- Modified Particle Swarm Optimization (MPSO)
How to Cite
Narasimha Rao Yamarthi, Padma Yenuga, Srikanth Meda, Lakshmi Tulasi R, Venkata Anusha Kolluru, Satish Kumar Patnala, Bujji Babu Dasari, Lakshmi Naga Jayaparada G, Om Prakash Samantray, Narasimha Reddy K V, Kunda Suresh Babu, and Lalitha Kumari Pappala, "Smart 5G Small Cell Mobile Networking with Sleep Strategy Using Novel Swarm Optimization," Journal of Advances in Information Technology, vol. 15, no. 5, pp. 672-681, 2024. https://doi.org/10.12720/jait.15.5.672-681
Copyright & License
Copyright © 2024 by the authors. This is an open access article distributed under the Creative Commons Attribution License which permits unrestricted use, distribution, and reproduction in any medium, provided the original work is properly cited (CC BY 4.0).
