Reliability optimization in narrowband device-to-device communication for 5G and beyond-5G networks

Nauman, A., Jamshed, M. A., Qadri, Y. A., Ali, R. and Kim, S. W. (2021) Reliability optimization in narrowband device-to-device communication for 5G and beyond-5G networks. IEEE Access, 9, pp. 157584-157596. (doi: 10.1109/ACCESS.2021.3129896)

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The 5G and beyond-5G (B5G) is expected to be a key enabler for Internet-of-Everything (IoE). The narrowband Internet of Things (NB-IoT) is a low-power wide-area enabling technology introduced by the 3rd Generation Partnership in 5G. The objective of the NB-IoT is to enhance the mobile coverage area by increasing the number of repetitions of control and data packets between user equipment (UE) and the base station/evolved NodeB (BS/eNB). While these repetitions improve data delivery for delay-sensitive applications, they degrade the efficiency of the already resource-constrained IoT system by increasing the system overhead and energy consumption. Moreover, NB-IoT devices in the edge region of the cellular coverage area require more repetitions, which augment energy consumption. In this study, we investigate device-to-device (D2D) communication for NB-IoT delay-sensitive applications, such as healthcare-IoT services, to use two-hop communication instead of using a direct uplink. An optimization problem is formulated to achieve an optimal end-to-end delivery ratio (EDR). In addition, this study incorporates Q-Learning-based reinforcement learning (RL) for the selection of an optimal cellular relay, which assists NB-IoT UE in uploading sensitive data to BS/eNB. The proposed RL-intelligent-D2D (RL-ID2D) communication methodology selects the optimum relay with a maximum EDR, which ultimately augments energy efficiency.

Item Type:Articles
Additional Information:This research was supported by Basic Science Research Program through the National Research Foundation of Korea (NRF) funded by the Ministry of Education (NRF-2021R1A6A1A03039493).
Glasgow Author(s) Enlighten ID:Jamshed, Dr Muhammad Ali
Authors: Nauman, A., Jamshed, M. A., Qadri, Y. A., Ali, R., and Kim, S. W.
College/School:College of Science and Engineering > School of Engineering > Autonomous Systems and Connectivity
Journal Name:IEEE Access
ISSN (Online):2169-3536
Published Online:22 November 2021
Copyright Holders:Copyright © 2021 The Authors
First Published:First published in IEEE Access 9: 157584-157596
Publisher Policy:Reproduced under a Creative Commons License

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