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Energy Efficient Channel Coding Technique for Narrowband Internet of Things

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Intelligent Computing (SAI 2020)

Part of the book series: Advances in Intelligent Systems and Computing ((AISC,volume 1229))

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Abstract

Most of the existing Narrowband Internet of Things (NB-IoT) channel coding techniques are based on repeating transmission data and control signals as a way to enhance the network’s reliability and therefore, enable long distance transmissions. However, most of these efforts are made to the expense of reducing the energy consumption of the NB-IoT network and do not always consider the channel conditions. Therefore, this work proposes a novel NB-IoT Energy Efficient Adaptive Channel Coding (EEACC) scheme. The EEACC approach is a two-dimensional (2D) approach which not only, selects an appropriate channel coding scheme based on the estimated channel conditions; but also minimizes the transmission repetition number under a pre-assessed probability of successful transmission. It is aimed at enhancing the energy efficiency of the network by dynamically selecting the appropriate Modulation Coding Scheme (MCS) number and efficiently minimizing the transmission repetition number. Link-level simulations are performed under different channel conditions (good, medium or bad) considerations in order to assess the performance of the proposed up-link adaptation technique for NB-IoT. The obtained results demonstrate that the proposed technique outperforms the existing Narrowband Link Adaptation (NBLA) as well as the traditional repetition schemes, in terms of the achieved energy efficiency as well as reliability, latency and network scalability.

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Acknowledgment

This work is supported in part by the National Research Foundation of South Africa (Grant Number: 90604). Opinions, findings and conclusions or recommendations expressed in any publication generated by the NRF supported research are those of the author(s) alone, and the NRF accepts no liability whatsoever in this regard. The authors would like to also thank the Telkom Centre of Excellence (CoE) for their support.

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Authors and Affiliations

  1. Tshwane University of Technology (TUT), Staatsartillerie Road, Pretoria, 0001, South Africa

    Emmanuel Migabo, Karim Djouani & Anish Kurien

  2. Université de Paris-Est Cretéil, Laboratoire Images, Signaux et Systèmes Intelligents (LISSI), Vitry sur Seine, 94400, Paris, France

    Emmanuel Migabo & Karim Djouani

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  1. Emmanuel Migabo
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Correspondence to Emmanuel Migabo .

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Editors and Affiliations

  1. Faculty of Science and Engineering, Saga University, Saga, Japan

    Kohei Arai

  2. The Science and Information (SAI) Organization, Bradford, West Yorkshire, UK

    Supriya Kapoor

  3. The Science and Information (SAI) Organization, Bradford, West Yorkshire, UK

    Rahul Bhatia

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Migabo, E., Djouani, K., Kurien, A. (2020). Energy Efficient Channel Coding Technique for Narrowband Internet of Things. In: Arai, K., Kapoor, S., Bhatia, R. (eds) Intelligent Computing. SAI 2020. Advances in Intelligent Systems and Computing, vol 1229. Springer, Cham. https://doi.org/10.1007/978-3-030-52246-9_33

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