Integrating IoT in WBANs: An energy-efficient and QoS-aware approach for rapid model-driven transmission power control and link adaptation

Abstract

Wireless Body Area Networks (WBAN) are integral to the application framework of the Internet of Things (IoT) domain, especially in applications demanding efficient connectivity and availability. Our study introduces a rapid, model-based, and sensor-centric approach in WBANs, significantly enhancing energy and time efficiency, crucial for IoT devices constrained by limited power supply and the need for extended operational duration. Our scheme maintains a transmit power threshold table, ensuring objective Quality of Service (QoS) while reducing power consumption in sensor nodes. We achieve this through a novel approach that contrasts the target bit error rate (BER) with the received instantaneous BER, refining path loss and channel models to accurately determine receiver sensitivity. The proposed scheme sets a in receiver sensitivity model, establishing the minimum transmit power needed for desired QoS. This is particularly relevant for IoT applications where maintaining consistent communication quality is paramount. Our performance evaluations show that this approach outperforms existing link adaptation and transmit power control methods in sensor overhead, time efficiency, and energy efficiency, marking a significant advancement in IoT connectivity solutions. By addressing the challenges of radio frequency signal vulnerability to body shadowing and path loss in dynamic conditions, our study not only enhances WBAN performance but also contributes to the stability and adaptability of IoT networks. This aligns with the evolving needs of the IoT domain, where efficient, reliable, and adaptive network solutions are increasingly in demand for a wide range of applications.