Empowering Optimizing Resource Management in 5G Telecommunication Networks: The Power of Machine Learning

The emergence of 5G telecommunication technology has changed communication, promising high-speed data transfer, low latency, and extensive device connectivity. A key challenge lies in optimizing the performance and resource management of 5G networks, with supervised learning algorithms presenting a viable solution. These algorithms, supplemented by labeled training data, can accurately predict, and improve network behaviors, such as spectrum allocation, energy efficiency, quality of service (QoS) provisioning, and network optimization. This paper reviews these algorithms, delving into their applications and various strengths and limitations. It also discusses the challenges and future research directions in applying these algorithms to 5G networks, emphasizing the need to balance accuracy with complexity and ensuring fairness and security.