Year: 2025
Type: article
Abstract: This paper studies the optimization of energy efficiency in coexisting wireless body area networks (WBANs). A solution based on combining a naive Bayesian classifier with the Hungarian algorithm is proposed to improve link transmission energy efficiency. The solution is implemented in the following three steps: Firstly, the interference from surrounding WBANs is identified based on a naive Bayesian classifier considering the distance among WBANs, the residual energy of the sensor nodes, and the transmission power of the sensor nodes. Secondly, the signal‐to‐interference plus noise ratio is determined according to the results of the naive Bayesian classifier. Thirdly, the time slots are allocated adaptively by using the Hungarian algorithm to maximize the overall energy efficiency. The simulation results show that the scheme can improve the overall energy efficiency of the WBAN significantly while ensuring quality of service. In comparison with the iterative algorithm and the PONF algorithm, the proposed scheme has obvious advantages in improving energy efficiency.
Source: IET Communications
DOI: 10.1049/cmu2.12712
Authors: Yuting Qian, Kunqi Guo
Institution: Jiangsu University
Language: English
Topic: Wireless Body Area Networks
Subfield: Biomedical Engineering
Field: Engineering
Domain: Physical Sciences
Open Access status: gold
Estimated APC paid: $2,540
OpenAlex ID: W4409529954