期刊
COMPUTERS & ELECTRICAL ENGINEERING
卷 105, 期 -, 页码 -出版社
PERGAMON-ELSEVIER SCIENCE LTD
DOI: 10.1016/j.compeleceng.2022.108493
关键词
Machine learning; Energy consumption; Wireless networks; Wireless body area networks; Effective spectrum sensing; 5G Networks
Wireless Body Area Network (WBAN) is a wireless network that supports continuous monitoring of physiological signals of the human body. It optimizes wireless connections using cognitive radio technology and dynamically indicates effective data transmission paths through machine learning, thus extending the network's lifespan. Reducing energy consumption has become a significant concern in mobile communication networks.
Wireless Body Area Network (WBAN) is one of the wireless networks vertical purviews, which supports for constant physiological signal monitoring of human body and attracts both academic and industry in the field of research. In this wireless communication incorporating cognitive radio supports for providing opportunistic wireless link to user optimally by sensing spectral envi-ronment. Since the sensors used are battery dependent, increasing the lifetime of network is an essential task, implementing machine learning approach dynamically indicate path for effective data transmission between network intermediate and server. Consequently, energy harvesting and standard deviation of utilised energy estimation also need to be concentrated in this work while number sensors are incorporated in WBAN. Proposed scheme is validated with effectiveness of numerical results and proposes modified algorithm with low computational complexity. Reducing energy consumption of mobile communication networks has gained significant atten-tions since it takes a major part of the total energy consumption of information and communi-cation technology (ICT).
作者
我是这篇论文的作者
点击您的名字以认领此论文并将其添加到您的个人资料中。
推荐
暂无数据