Quality of Service Protection in 5G Mobile Ad Hoc Networks with Behavior Learning-Enhanced CNN-AODV Routing

MANETs that make use of 5G technology have been receiving a significant amount of attention as of late. It is distinguished by the fact that nodes are subjected to an unrelenting onslaught of traffic while simultaneously being expected to maintain a high level of service. It has become clear that the limits of previously used routing protocols are exposed by 5G-based MANETs. In this study, we propose an innovative modification to the CNN-AODV protocol that can be used for 5G MA-NETs. Each node makes use of reinforcement learning in order to monitor the state of the other nodes that are between it and the destination it seeks. The QoS-assured pathway information is utilized by the route optimization approach in order to locate the most advantageous paths. According to the results of the simulations, our approach offers excellent levels of throughput of 20% high, 0% end-to-end delay, and very low signal-to-noise ratio.