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Machine Learning in Terahertz Communication

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Antenna Technology for Terahertz Wireless Communication

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Abstract

This chapter discusses the potential role of machine learning (ML)/deep learning (DL)/artificial intelligence (AI) for 6G wireless communication systems. Developing an efficacious 6G communication network at THz frequency is more complicated than those at lower frequency systems because channels at the THz band are noted to be further insecure than those of lower frequencies. Therefore, 6G wireless networks will own the intelligence and capacity to encourage the most appropriate communications tactics based on channel activities sensing and signal quality estimation feedback using ML/DL/AI technologies. In addition, to increase the bandwidth and boost the data rate to new dimensions, we need to use THz communication to induce 6G wireless applications such as holographic communication and digital twinning. Moreover, the THz frequencies supply access to broader bandwidth, which allows interaction with communication devices to be changed by improving aspects like gesture recognition to assist XR-based applications, for example, the Metaverse.

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Authors and Affiliations

  1. University of Johannesburg, Johannesburg, South Africa

    Uri Nissanov & Ghanshyam Singh

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  1. Uri Nissanov
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  2. Ghanshyam Singh
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Nissanov, U., Singh, G. (2023). Machine Learning in Terahertz Communication. In: Antenna Technology for Terahertz Wireless Communication. Springer, Cham. https://doi.org/10.1007/978-3-031-35900-2_10

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  • DOI: https://doi.org/10.1007/978-3-031-35900-2_10

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  • Publisher Name: Springer, Cham

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  • Online ISBN: 978-3-031-35900-2

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