Reinforcement Learning for Optimal Resource Allocation in UAV-Assisted Integrated Access and Backhaul Cellular Networks

According to many studies, a layer-based UAV installation provides for improved object interaction. Besides these solutions, research connecting UAVs to multiple layers (U2X) is limited. In particular, no one discussed the issue of resource allocation. This project will help you resolve resource allocation issues and determine the total number of transfers between UAVs. It saves a lot of energy while increasing the likelihood of service delivery. UAVs provide ground users with communications services in a variety of situations, including transportation systems, emergencies, surveillance, and disaster situation. UAV technology's long-term coverage of a particular area in a flexible environment is challenging. Due to finite power resources, low coverage, flight laws, and regulations. As a result, a decentralized solution is required to address these issues. This research described a new distribution strategy that involves several unmanned aerial vehicles (UAVs) in an area to enhance coverage points while consuming less power and ensuring accuracy. In this project, our basic requirement is Algorithms and Simulations using Matlab or python. In this we want output using Reinforcement learning in terms of minimization of energy consumption. i.e as compared to existing researches based on this it should be more less and efficient energy consumption. Anybody who is interested in this project, kindly contact me.