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Multi-objective Optimization in NOMA-IoT Networks

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Artificial Intelligence and Data Science Based R&D Interventions (NERC 2022)

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Abstract

In recent years Internet of Things (IoT) attracts a significant attention in fifth generation (5G) networks. 5G network is considered for its high speed and large number of user equipments (UEs). Non-orthogonal multiple access (NOMA), an information theoretic approach, has been considered in 5G to support large UEs as well as with many other benefits. As a result, different objectives such as energy efficiency (EE), spectral efficiency (SE), and user fairness (UF) have to be taken care of. In this paper, we aim to focus on improving SE and EE while maintaining UF. This paper presents multi-objective optimization (MOO) using genetic algorithm (GA) with the help of reinforcement learning (RL) algorithm. This work focuses on improving the sum rate as well as energy efficiency assuming perfect channel state information (CSI). Most of the work focuses on gradient-based algorithm, namely, backpropagation while Evolution strategies can rival gradient-based algorithm. In this work, we omit the use of backpropagation and replace it with genetic algorithm. It is a challenging task when considering long-term reward maximization in the network. Reinforcement learning with Markov decision process (MDP) help in this direction.

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Authors and Affiliations

  1. Indian Institute of Technology Guwahati, Guwahati, Assam, India

    Sumita Majhi & Pinaki Mitra

Authors
  1. Sumita Majhi
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  2. Pinaki Mitra
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Correspondence to Sumita Majhi .

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Editors and Affiliations

  1. Department of Electronics and Electrical Engineering and Head Mehta Family School of Data Science and Artificial Intelligence, Indian Institute of Technology Guwahati, Guwahati, Assam, India

    Ratnajit Bhattacharjee

  2. Mehta Family School of Data Science and Artificial Intelligence, Indian Institute of Technology Guwahati, Guwahati, India

    Debanga Raj Neog

  3. Mehta Family School of Data Science and Artificial Intelligence, Indian Institute of Technology Guwahati, Guwahati, India

    Konda Reddy Mopuri

  4. Mehta Family School of Data Science and Artificial Intelligence, Indian Institute of Technology Guwahati, Guwahati, India

    Santosh Kumar Vipparthi

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Majhi, S., Mitra, P. (2023). Multi-objective Optimization in NOMA-IoT Networks. In: Bhattacharjee, R., Neog, D.R., Mopuri, K.R., Vipparthi, S.K. (eds) Artificial Intelligence and Data Science Based R&D Interventions. NERC 2022. Springer, Singapore. https://doi.org/10.1007/978-981-99-2609-1_6

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  • DOI: https://doi.org/10.1007/978-981-99-2609-1_6

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  • Publisher Name: Springer, Singapore

  • Print ISBN: 978-981-99-2608-4

  • Online ISBN: 978-981-99-2609-1

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