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Next Generation Wireless Communication: Facilitated by Machine Learning

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Recent Innovations in Computing

Part of the book series: Lecture Notes in Electrical Engineering ((LNEE,volume 855))

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Abstract

Currently, the fifth generation (5G) Wireless Communication Networks (WCN) with enhanced capabilities are in the process of deployment all over the world. With ever increasing mobile traffic, they are likely to offer better coverage, security and spectrum efficacy in addition to more cost-effective infrastructural network. Emergence of Artificial Intelligence (AI), e-health, cognitive techniques, automation of industries and many other Machine Learning (ML) applications are likely to flourish with next generation WCN. This paper deals with a significant aspect of next generation WCN and how it will be facilitated by the ML [2–4]. Initially, the overview of both the WCN and ML has been given by bringing out the fundamentals of both the concepts in this paper which is followed by the brief outline about the noteworthy parameters facilitating the next generation mobile communication data networks. Further, it provides a brief account on the promising prospects in relation to future WCN applications. An added technological paradigm associated with these prospects even beyond 5G networks shall enable such applications that the limitations between the cyber and the physical domains are likely to be wiped out. A recommendation on deployment parameters of future generation WCN applications supported by ML has also been provided to evaluate the impact of this promising technology [21]. Lastly, this paper explores the future research possibilities wherein the ML can contribute in surmounting the limitations of such widespread mobile network deployments.

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Author information

Authors and Affiliations

  1. Department of Computer Application, Shri Ramswaroop Memorial University, Lucknow-Deva Road, Barabanki, India

    Praveen Kumar Singh

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  1. Praveen Kumar Singh
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Editor information

Editors and Affiliations

  1. KIET Group of Institutions, Ghaziabad, India

    Pradeep Kumar Singh

  2. Department of CSE, Central University of Jammu, Jammu and Kashmir, India

    Yashwant Singh

  3. Department of Computer Engineering, NIT Kurukshetra, Kurukshetra, India

    Jitender Kumar Chhabra

  4. Faculty of Informatics, Eötvös Loránd University (ELTE), Budapest, Hungary

    Zoltán Illés

  5. Faculty of Informatics, Eötvös Loránd University (ELTE), Budapest, Hungary

    Chaman Verma

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Singh, P.K. (2022). Next Generation Wireless Communication: Facilitated by Machine Learning. In: Singh, P.K., Singh, Y., Chhabra, J.K., Illés, Z., Verma, C. (eds) Recent Innovations in Computing. Lecture Notes in Electrical Engineering, vol 855. Springer, Singapore. https://doi.org/10.1007/978-981-16-8892-8_59

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