Title: An advanced fractal optimisation method for network energy and power based on cellular massive MIMO based on photovoltaic technology

Authors: Ying Huang; Haibin Wan; Gengqiang Huang; Hailu Wan

Addresses: School of Computer, Electronics and Information, Guangxi University, Nanning 530004, Guangxi, China; Intelligence and Information Engineering College, Guangxi Economic and Trade Vocational Institute, Nanning 530021, Guangxi, China ' Guangxi Key Laboratory of Multimedia Communications and Network Technology, Guangxi University, Nanning 530004, Guangxi, China ' Faculty of Green Building and Low Carbon Technology, Guangxi Technological College of Machinery and Electricity, Nanning 530007, Guangxi, China ' Faculty of Industrial Design, Guangxi Technological College of Machinery and Electricity, Nanning 530007, Guangxi, China

Abstract: User communication needs drive the wide application of cell-free massive MIMO systems. Network energy consumption significantly affects communication quality and efficiency. Photovoltaic systems provide real-time electricity, dynamically adjusting MIMO parameters based on output changes to ensure stable operation. This article aims to enhance user experience and optimise energy distribution in communication systems. It constructs a basic system model, defines network signal power optimisation, applies photovoltaic technology for sustainable energy supply, and solves the optimisation problem using PSO. Simulations compare pre- and post-optimisation effects, revealing a 20.24% energy efficiency improvement in photovoltaic-based communication systems with 100 access points. The proposed method enhances communication efficiency and optimises energy distribution in networks.

Keywords: network signal power optimisation; cell-free massive multiple-input multiple-output; photovoltaic technology; network energy; communication systems.

DOI: 10.1504/IJDSDE.2025.146965

International Journal of Dynamical Systems and Differential Equations, 2025 Vol.14 No.1/2, pp.100 - 122

Received: 14 May 2024
Accepted: 02 Dec 2024
Published online: 27 Jun 2025 *

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