MEC-enabled load balancing framework for DFA-IRS aided wearable healthcare networks
摘要
The underlying challenges in the wearable electronic market are the limited power and processing capability often resulting in failure to handle complex computations. In order to balance the computational demands with resource constraints, the potential of intelligent reflecting surfaces (IRSs) are exploited in this paper. The paper presents a wearable electronics network in which the wearable nodes communicate with the assistance of double faced active (DFA) IRSs. By simultaneously controlling reflection and transmission links with active amplification, DFA-IRS enables reliable mobile edge computing (MEC)-based task offloading from wearable devices to nearby processing nodes. A resource utilization (RU) algorithm is proposed that associates the devices with DFA-IRSs. The optimal phase shifts of DFA-IRSs are obtained. Further, the impact of transmit power