The Role of Edge Computing in Enhancing 5G Networks

The article discusses how 5G and future networks are optimized using AI and machine learning technologies to improve performance metrics such as spectral efficiency and minimize latency. Realistic AI/ML deployments like smart network management software and dynamic spectrum sharing technologies already have encouraging gains in real deployment. This paper is centered on AI-based methods, with a particular emphasis on deep and reinforcement learning. The paper also discusses the computational cost, energy overhead, and security threats these technologies cause. In the future, the paper discusses how AI-driven 6G systems, smart network management, and cooperative learning can optimize resource management and improve security in future wireless networks. The study considers the natural complexity, energy consumption and privacy concerns of the deployment of AI / ML in wireless networks.