An Intelligent Clustering-Based Routing Protocol (CRP-GR) for 5G-Based Smart Healthcare Using Game Theory and Reinforcement Learning

With advantages such as short and long transmission ranges, D2D communication, low latency, high node density, the 5G communication standard is a strong contender for smart healthcare. Smart healthcare networks based on are expected to have heterogeneous energy mobility, requiring them adapt connected environment. As result, in 5G-based healthcare, building routing protocol that optimizes consumption, reduces delay, extends network lifetime remains challenge. This paper presents clustering-based improve Quality of services (QoS) optimization QoS achieved by selecting an energy-efficient clustering head (CH) with help game theory (GT) best multipath route selection reinforcement learning (RL). The cluster modeled mixed strategy considering various attributes find equilibrium conditions. parameters distance between nodes, nodes base station, remaining speed mobility were used probability. An (RL) having (Q-learning) proposed. simulation result shows our proposed approach improves compared existing approaches. average performances schemes CRP-GR CRP-G 78% 71%, respectively, while schemes, FBCFP, TEEN LEACH 63%, 48% 35% accordingly.