OPTIMIZED SMART FRAMEWORK FOR ENERGY-EFFICIENT DEVICE-TO-DEVICE CONNECTIVITY IN 5G-DRIVEN HEALTHCARE IOT SYSTEMS

Abstract

 The paradigm shift of continuous and real-time health monitoring is emerging with the creation of the Fifth Generation (5G) networks as one of the foundations of the Internet of Medical Things (IoMT). However, the energy needs of battery-operated wearable and implantable devices are a highly central bottleneck particularly in the light of meeting the Ultra-Reliable Low-Latency Communication (URLLC) requirements of life-critical applications. The current paper is an offer of an Optimized SMART Framework which must be applied to optimize the extent of energy efficiency and deliver tight Quality of Service (Quality of Service) in a medical facility. The framework applies the principle that the transmission load can be transferred between the cellular uplink and proximal edge nodes by applying the 5G Device-to-Device (D2D) Sidelink to reduce the propagation loss by a large margin.    This cross-layer optimization strategy has been characterised by five synergistic pillars, the first being Secure which utilises lightweight cryptography (Speck/LECC) to reduce power needs of encryption by approximately 30 percent compared with AES; Multi-tier, which employs hierarchical edge computing to minimise latency; Adaptive, which uses Deep Reinforcement Learning (DRL) algorithms (DRL-LVT) to dynamically optimise resource block and transmission power consumption based on the real-time channel state information; Reliable, which uses Non-Orthog.