Intelligent Energy Efficient Resource Allocation for URLLC Services in IoV Networks

Sohaib, R. M., Onireti, O. , Sambo, Y. , Swash, R. and Imran, M. (2022) Intelligent Energy Efficient Resource Allocation for URLLC Services in IoV Networks. In: 2022 IEEE 33rd Annual International Symposium on Personal, Indoor and Mobile Radio Communications (PIMRC), 13-16 Sep 2022, ISBN 9781665480536 (doi: 10.1109/PIMRC54779.2022.9978038)

Abstract

Internet of vehicles (IoV) has been developed as a promising technology to improve road safety. However, resource management can be challenging in a congested traffic environment, which can affect the energy efficiency (EE) and spectrum efficiency (SE) in IoV networks. In this paper, we present a novel intelligent resource allocation approach based on deep reinforcement learning to maximize the weighted composite efficiency that incorporates the EE and SE metric subject to latency and reliability constraints of vehicle-to-vehicle (V2V) users. We employ Thompson sampling with double deep Q network to transform the objective function. Moreover, we present a probability-based learning approach to meet the quality of service requirements and to increase the learning ability of the proposed model. The simulation results indicate that the proposed approach maximizes the composite efficiency while satisfying the latency and reliability constraints of V2V users.

• Item Type: Conference Proceedings
• Status: Published
• Refereed: Yes
• Glasgow Author(s) Enlighten ID: Sambo, Dr Yusuf and Imran, Professor Muhammad and Swash, Professor Rafiq and Onireti, Oluwakayode and Sohaib, Rana
• Authors: Sohaib, R. M., Onireti, O., Sambo, Y., Swash, R., and Imran, M.
• College/School: College of Science and Engineering > School of Engineering; College of Science and Engineering > School of Engineering > Autonomous Systems and Connectivity
• ISSN: 2166-9589
• ISBN: 9781665480536
• Copyright Holders: Copyright © 2022 IEEE
• Publisher Policy: Reproduced in accordance with the copyright policy of the publisher

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