PERFORMANCE ANALYSIS OF HYBRID ENERGY HARVESTING TECHNIQUES FOR WBAN APPLICATIONS

Abstract

Wireless Body Area Networks (WBANs) are widely used in healthcare and wearable monitoring applications, where continuous power supply is a major challenge due to limited battery life. Conventional Radio Frequency (RF) energy harvesting methods provide low and unstable energy, especially at longer distances. To overcome this limitation, this paper proposes a hybrid energy harvesting system that combines RF, motion, and thermal energy sources for long-term WBAN operation. The proposed system improves power availability and reliability by utilizing body movement and body heat along with RF signals. MATLAB simulation is used to analyze the performance of both the existing RF-only method and the proposed hybrid method. The results show that the hybrid system provides better energy efficiency, stable power generation, and improved operational lifetime compared to the conventional approach. The proposed method is suitable for low-power wearable healthcare devices and sustainable WBAN applications.