Wi-Fi Energy Harvesting for IoT Implants in Body Area Networks

Wireless body area network (WBAN) plays a crucial role in the internet-of-things (IoT) aided E-health sector. It has revolutionized the healthcare industry by connecting wearable devices/implants for biomedical signal monitoring. However, high power consumption and unexpectedly less battery life of implants installed in the patient’s body are key challenges calling for the need for sustainable IoT-assisted BAN. Interestingly, among all the scattered RF energy harvesting sources, Wi-Fi is the most prominent and widely available resource for harvesting unutilized energy. In this work, first, we provide a comprehensive study of the power consumption of various implants, along with the power densities of a few energy harvesters. Then we propose a more practical and sustainable indoor BAN channel model powered by the available ambient Wi-Fi signals as compared to the existing models. In particular, we have defined a unique indoor path loss model specific to four rooms with different channel conditions, thereby incorporating the effects of numerous indoor parameters like the number of floors, types of walls, and small-scale fading. Results are numerically validated and compared with two existing benchmark models, in addition to providing the scenario-specific outage probability-based sustainability analysis of implants.