Adaptive AI Algorithms for Dynamic Network Resource Allocation and QoS Optimization in 5G Telecommunications

This research explores the application of adaptive AI algorithms to dynamically allocate network resources and optimize Quality of Service (QoS) in 5G telecommunications networks. With 5G's rapid deployment, efficient resource allocation for ultra-low latency, enhanced data speeds, and high device density has become essential. This paper introduces a reinforcement learning-based adaptive AI framework for real-time dynamic resource management in 5G environments, showing significant improvements in QoS metrics compared to traditional allocation methods.