Unveiling the Potential of Artificial Intelligence and Machine Learning in the 5G Network Landscape: A Comprehensive Review

Author:

Rizvi Samreen

Abstract

Exploring successful case studies, scholars and industry experts concur that artificial intelligence (AI) and 5G technology, as holistic solutions, exhibit remarkable efficiency. The integration of AI has notably resolved wireless communication dilemmas that defy traditional modeling approaches, substantially diminishing technological uncertainties. Furthermore, 5G technology is poised to amalgamate communication, computation, sensing, and control across diverse industries. However, the convergence of these capabilities also introduces complexity, a challenge that can be effectively addressed through the application of artificial intelligence and machine learning functionalities. These cutting-edge technologies not only ensure data security but also satisfy stringent latency requirements while minimizing the burden on both communication and computation resources. In this context, a thorough examination of machine learning and artificial intelligence applications geared towards optimizing communication, computation, and resource allocation within the realm of 5G technology holds paramount significance. In pursuit of this objective, the study endeavors to offer a comprehensive outlook on the current landscape of artificial intelligence research within the 5G domain. By scrutinizing recent studies, we aim to encapsulate the contributions and prevailing trends associated with these technologies. Ultimately, our aim is to empower researchers and industry practitioners with insights that will facilitate informed decision-making when selecting the most suitable machine learning and artificial intelligence approaches for their endeavors.

Publisher

Sciencedomain International

Subject

General Agricultural and Biological Sciences

Cited by 1 articles. 订阅此论文施引文献 订阅此论文施引文献,注册后可以免费订阅5篇论文的施引文献,订阅后可以查看论文全部施引文献

1. Analysis and forecasting of modern telecommunication systems traffic based on artificial intelligence methods;Vestnik of Astrakhan State Technical University. Series: Management, computer science and informatics;2024-02-09

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