Abstract
AbstractAs 4G technology served as a foundation, the emergence of 5G is now underway, ushering in a new era of connectivity. With the growing demand for seamless internet experiences, particularly in the face of escalating internet subscribers, the networking domain must evolve. Developing nations strive to align with this dynamic landscape, necessitating an upgrade that integrates internet of things (IoT), natural language processing (NLP), and artificial intelligence (AI) with network infrastructure. By enhancing networking systems with lower latency and improved scalability, 5G addresses congestion issues. This is achieved by coupling mm‐wave technology with the 5G framework through the 3rd Generation Partnership Project, significantly amplifying channel bandwidth. However, the comprehensive analysis underscores challenges in 5G implementation, encompassing aspects like distance, orientation, non‐line‐of‐sight conditions, protocol utilization, and server positioning. Drawing from a dataset provided by the University of Minnesota that illuminates the limitations of 5G implementation in select US cities, this paper extends its focus to densely populated regions in developing countries of the sub‐continent. Employing a machine learning approach, the paper delves into the constraints of 5G deployment in such areas. Ultimately, this research aims to shed light on the intricacies of 5G's implementation challenges, contributing to the discourse on enhancing network infrastructure in the evolving landscape of global connectivity.
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