Modified hybrid fruit fly-based salp swarm optimization strategy for energy efficient optimization in MIMO Wireless Powered Communication Networks

Article type: Research Article

Authors: Kumar, G. Harish^{; *} | Rao, P. Trinatha

Affiliations: Department of ECE, GITAM (Deemed to be University), Hyderabad, India

Correspondence: [*] Corresponding author. E-mail: 221960404003@gitam.in.

Abstract: A potential way to handle the future requirements of wireless data traffic is the Massive Multiple Input Multiple Output (MIMO) antenna systems. The most effective method to satisfy the demand for wireless data traffic is to enhance the Spectral Efficiency of the existing spectrum since the wireless spectrum is a limited resource. In the MIMO network, cell-free, energy-efficient, and user-centric are considered as most important parameters to achieve effective communication. Therefore, a new energy efficiency optimization scheme is developed in a massive MIMO system to improve the system’s capacity and spectral efficiency. The multi-channel optimization problem is effectively rectified with the help of this newly designed energy efficiency optimization scheme. Here, the “Singular Value Decomposition (SVD)” method is utilized for the implementation of a sub-channel grouping scheme, where the sub-channels are arranged in descending order based on the results attained from SVD. After arranging the sub-channels, the sub-channel grouping is carried out, and then the energy efficiency optimization is provided with the help of Integrated Fruit Fly with Salp Swarm Optimization (IFFSSO). This energy-efficient algorithm improves the system capacity and spectral efficiency. The experimental outcome is revealed through various conventional models to ensure the energy efficiency of the recommended model.

Keywords: Massive Multiple Input Multiple Output, Wireless Powered Communication Networks, multi-channel optimization problem, Integrated Fruit Fly with Salp Swarm Optimization

DOI: 10.3233/JHS-230173

Journal: Journal of High Speed Networks, vol. 30, no. 4, pp. 535-555, 2024