5G Resource Allocation for Efficient Usage of Bandwidth using Machine Learning

Abstract

Abstract: The rapid evolution of telecommunications technology has ushered in the era of 5G networks, offering unparalleled speed, minimal latency, and enhanced connectivity. This study comprehensively analyzes the performance of 5G networks, focusing on critical Quality of Service (QoS) metrics and innovative resource allocation strategies. Through meticulous examination and real-world simulations, our research reveals that 5G networks typically achieve a tenfold increase in data transfer rates compared to their 4G counterparts. Moreover, our findings demonstrate a substantial 30% reduction in latency, underscoring the efficiency and responsiveness of 5G technology. Additionally, our investigation delves into advanced resource allocation strategies, introducing a novel approach that optimizes network resources and leads to a 15% enhancement in overall network efficiency. These conclusions are substantiated by empirical data obtained from extensive field tests and simulations, providing compelling evidence of the project's impact on 5G network performance. As global adoption of 5G accelerates, the insights gleaned from this study are poised to shape the future of telecommunications, offering valuable guidance to network operators, policymakers, and industry stakeholders as they navigate towards a more efficient and reliable 5G ecosystem..