A bonded channel in cognitive wireless body area network based on IEEE 802.15.6 and internet of things

Abstract

Despite the recent developments in communication technologies for wireless body area networks (WBAN), the reliability of packet transmission, especially for emergency and critical data transfer remains a significant challenge. This may be that most of the existing techniques in WBAN use single-channel for data transmission with no intelligence. The cognitive bonded channel which provides high data rate for emergency and the demanding situation. Existing techniques in WBAN rely on the use of the single-channel for data transmission and do not exploit the use of the bonded channel, which can improve the WBAN capacity of off-body communication. In our research, we propose a traffic load aware bonded channel algorithm (TLA-BCA), which exploits channel bonding to improve the performance of off-body communication between the WBAN sink nodes and gateway. Our proposed algorithm, i.e., TLA-BCA utilizes high-quality channels for channel bonding to maximize the capacity of off-body communication in WBANs. TLA-BCA demonstrates significant performance improvement over Traffic Priority Based Channel Assignment Technique (TP-CAT) and Static Channel Assignment (SCA) in terms of average throughput, average end-to-end delay with comparable energy performance.