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HAP-Assisted RSMA-Enabled Vehicular Edge Computing: A DRL-Based Optimization Framework

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  • Tri-Hai Nguyen

    (Department of Computer Science and Engineering, Seoul National University of Science and Technology, Seoul 01811, Republic of Korea)

  • Laihyuk Park

    (Department of Computer Science and Engineering, Seoul National University of Science and Technology, Seoul 01811, Republic of Korea)

Abstract

In recent years, the demand for vehicular edge computing (VEC) has grown rapidly due to the increasing need for low-latency and high-throughput applications such as autonomous driving and smart transportation systems. Nevertheless, offering VEC services in rural locations remains a difficulty owing to a lack of network facilities. We tackle this issue by taking advantage of high-altitude platforms (HAPs) and rate-splitting multiple access (RSMA) techniques to propose an HAP-assisted RSMA-enabled VEC system, which can enhance connectivity and provide computational capacity in rural locations. We also introduce a deep deterministic policy gradient (DDPG)-based framework that optimizes the allocation of resources and task offloading by jointly considering the offloading rate, splitting rate, transmission power, and decoding order parameters. Via results from extensive simulations, the proposed framework shows superior performance in comparison with conventional schemes regarding task success rate and energy consumption.

Suggested Citation

  • Tri-Hai Nguyen & Laihyuk Park, 2023. "HAP-Assisted RSMA-Enabled Vehicular Edge Computing: A DRL-Based Optimization Framework," Mathematics, MDPI, vol. 11(10), pages 1-23, May.
  • Handle: RePEc:gam:jmathe:v:11:y:2023:i:10:p:2376-:d:1151421
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    References listed on IDEAS

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    1. Volodymyr Mnih & Koray Kavukcuoglu & David Silver & Andrei A. Rusu & Joel Veness & Marc G. Bellemare & Alex Graves & Martin Riedmiller & Andreas K. Fidjeland & Georg Ostrovski & Stig Petersen & Charle, 2015. "Human-level control through deep reinforcement learning," Nature, Nature, vol. 518(7540), pages 529-533, February.
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