Work

Optimizing performance of WPCN based on whale optimization algorithm

Year: 2025
Type: article
Abstract: This paper investigates the optimization issues of wireless powered communication (WPC) networks and proposes a technique that is grounded in the whale optimization algorithm (WOA) to address key optimization problems such as node deployment, energy allocation, power control, and multi-user access within the network. WPC technology is capable of providing energy to terminal devices while transmitting information, which is crucial for the operation of low-power devices in the Internet of Things. However, the design and optimization of WPC networks face numerous challenges, including signal coverage and data transmission under limited energy budgets, ensuring communication quality, and the efficient management and scheduling of network resources. The WOA, a cutting-edge metaheuristic optimization technique, emulates the hunting tactics of humpback whales, showcasing robust global search prowess and responsive search tactics. This paper first proposes an optimization framework for WPC networks based on WOA, then analyzes the applicability and advantages of WOA in WPC networks in detail, and adjusts WOA according to the characteristics of WPC networks. Through simulation experiments, the efficacy of the proposed approach has been confirmed through validation, and it has been compared with current algorithms. The findings from the experiments demonstrate that the WOA offers substantial benefits in terms of enhancing network performance and energy conservation, especially when dealing with complex, dynamically changing WPC network optimization problems, demonstrating its unique strengths. This study provides new perspectives and solutions for the optimization of WPC networks and further promotes the development of WPC technology. Future research will focus on further improving WOA and applying it to optimization problems in a broader range of wireless communication scenarios.
Authors: Lina Yuan, Huajun Chen, Tinghong Chang, Ging Gong
Language: English
Open Access status: gold
Estimated APC paid: $2,690
OpenAlex ID: W4410726467
FWCI: 0.693
Cites: 23
Cited by: 3
Related to: 10