Smart Energy Solutions for Wireless Medical Sensor Networks: Modulation Optimization in IoMT for Medical Applications

Abstract

Background: Wireless Medical Sensor Networks (WMSNs) are crucial for monitoring patients' health in Wireless Body Area Networks (WBANs). However, the energy consumption of medical sensors (MSs) presents a significant challenge, impacting the efficiency and longevity of these networks. Optimizing energy consumption while maintaining spectral efficiency is essential for enhancing the performance of WMSNs. Objective: This study aims to optimize energy consumption in WMSNs by exploring the balance between energy conservation and spectral efficiency. The focus is on selecting optimal modulation schemes that minimize total energy consumption while considering various distances and the Additive White Gaussian Noise (AWGN) channel. Methods: The research investigates energy and constellation optimization using different modulation types, particularly in the context of the Internet of Medical Things (IoMT). A coefficient is introduced to vary circuit consumption independently of power emitted. Additionally, the study derives a performance-optimized energy efficiency measure for circuits and provides a closed-form transmission efficiency measure for M-ray quadrature amplitude modulation (M-QAM), validated numerically. Results: The findings reveal the optimal modulation schemes for various conditions, demonstrating significant energy savings while maintaining adequate spectral efficiency. The introduced coefficient effectively decouples circuit consumption from emitted power, optimizing energy use in WMSNs. Conclusion: This research offers a comprehensive approach to energy consumption optimization in WMSNs, contributing to more efficient WBANs. The proposed methods and findings support the development of energy-efficient, remote medical care systems, enhancing the reliability and longevity of IoMT-based healthcare solutions.