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Application of AI & ML in 5G Communication

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Paradigms of Smart and Intelligent Communication, 5G and Beyond

Part of the book series: Transactions on Computer Systems and Networks ((TCSN))

Abstract

The world is on the cusp of a new era of communication. Current networks are struggling to keep up with the demand. It is predicted that 5G will be one of the most impactful technologies in the world in the next decade. It will connect a billion people to the internet in the same way that 4G has done today, but with even faster speeds. The application of AI and machine learning in 5G communication will enable the generation of higher speeds, lower latency, and improved reliability. This will enable the next generation of internet services and greater connectivity for users. The next generation of communication networks will require a shift towards artificial intelligence and machine learning to improve the experience for users. This advancement in technology will better understand how to best utilize the limited spectrum and provide a better experience for users. The application of AI and machine learning in 5G communication will enable the generation of higher speeds, lower latency, and improved reliability. This will enable the next generation of internet services and greater connectivity for users.

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Abbreviations

eMBB:

Extreme mobile broadband

eMTC:

Massive machine type communication

URLLC:

Ultra-reliable low latency communication

QoS:

Quality of service

V2V:

Vehicle to Vehicle

RAN:

Radio access network

FDMA:

Frequency-Division Multiple Access

AMPS:

Advanced Mobile Phone System

MIMO:

Massive multiple-input multiple-output

mmWave:

Millimeter wave

SDN:

Software defined network

NFV:

Network functions visualization

NG-RAN:

Next Generation—Radio Access Network

SBA:

Service-Based Architecture

SNR:

Signal-to-noise

DCNN:

Deep convolutional neural network

GSM:

Global System for Mobile communication

CDMA:

Code-Division Multiple Access

TDMA:

Time-Division Multiple Access

VR:

Virtual Reality

AR:

Augmented Reality

MAE:

Multi-access Edge Computing

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Authors and Affiliations

  1. Amity University, Greater Noida, UP, India

    Lipsa Das, Ajay Rana, Khushi Dadhich, Smita Sharma & Suman Avdhesh Yadav

  2. Manipal University Jaipur, Jaipur, India

    Biswa Mohan Sahoo

Authors
  1. Lipsa Das
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  2. Biswa Mohan Sahoo
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  3. Ajay Rana
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  4. Khushi Dadhich
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  5. Smita Sharma
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  6. Suman Avdhesh Yadav
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Corresponding author

Correspondence to Lipsa Das .

Editor information

Editors and Affiliations

  1. G L Bajaj Institute of Technology and Management, Greater Noida, Uttar Pradesh, India

    Amrita Rai

  2. G L Bajaj Institute of Technology and Management, Greater Noida, Uttar Pradesh, India

    Dinesh Kumar Singh

  3. Electrical Electronics and Communication Engineering (EECE), Sharda University, Greater Noida, Uttar Pradesh, India

    Amit Sehgal

  4. Electrical and Electronics Engineering Department, Trakya University Faculty of Engineering, Trakya, Türkiye

    Korhan Cengiz

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© 2023 The Author(s), under exclusive license to Springer Nature Singapore Pte Ltd.

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Das, L., Sahoo, B.M., Rana, A., Dadhich, K., Sharma, S., Yadav, S.A. (2023). Application of AI & ML in 5G Communication. In: Rai, A., Kumar Singh, D., Sehgal, A., Cengiz, K. (eds) Paradigms of Smart and Intelligent Communication, 5G and Beyond. Transactions on Computer Systems and Networks. Springer, Singapore. https://doi.org/10.1007/978-981-99-0109-8_9

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  • DOI: https://doi.org/10.1007/978-981-99-0109-8_9

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  • Publisher Name: Springer, Singapore

  • Print ISBN: 978-981-99-0108-1

  • Online ISBN: 978-981-99-0109-8

  • eBook Packages: Computer ScienceComputer Science (R0)

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