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Demonstrates improved network performance in WBANs, indicating efficient healthcare monitoring benefits.
A wireless body area network (WBAN) is a specialized network designed for continuous monitoring of the human body and real‐time data transmission, particularly in medical healthcare applications. The integration of the internet of things (IoT) with WBAN enables efficient patient condition monitoring. This study proposes an innovative energy‐efficient, multi‐phase media access control (MAC) protocol designed to support scalable transmission and incorporate energy harvesting (EH) techniques. The protocol operates in five distinct phases: contention notification interval (CNI), contention access period (CAP), timeslot announcement interval (TAI), contention‐free period (CFP), and an inactive phase. During the CNI, the start of CAP is announced, while TAI indicates the transition from CFP to the inactive phase. In CAP, the carrier sense multiple access/collision avoidance (CSMA/CA) protocol is utilized for both data transfer and global telecommunication system (GTS) request message transmission. CSMA/CA optimizes channel access by avoiding collisions during data transmission to grant access to all nodes. The CFP is then invoked by dividing the time period into different GTS using the time division multiple access (TDMA) protocol. It ensures more controlled channel access during low contention periods. The proposed approach with CSMA/CA and TDMA ensures better channel utilization with less collision and high energy efficiency. Moreover, the resource limitation of WBAN can be handled with the EH technique that improves the lifetime of sensor nodes (SN) in healthcare applications. The proposed approach is simulated in MATLAB, and the throughput rate is improved by 50% for 20 SNs. Moreover, the proposed approach has achieved a residual energy of 32.91 mJ, a packet delay of 32.50 ms, a high packet delivery ratio of 98%, a power consumption of 58.41 mJ, and a network lifetime of 492116.16 s with a transmission probability of 0.001.
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Sachin Kumar (2026) studied this question.
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