Effective spectrum sensing using cognitive radios in 5G and wireless body area networks

Abstract

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 environment. 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 attentions since it takes a major part of the total energy consumption of information and communication technology (ICT).