Zhu, S; Li, D; Meng, K; (2024) Multi-Domain Orthogonal V2X Communication for Diverse Platoon Transmissions. In: Valenti, M and Reed, D and Torres, M, (eds.) 2024 IEEE International Conference on Communications Workshops, ICC Workshops 2024. (pp. pp. 75-81). IEEE: Denver, CO, USA.

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Text 11.1-Multi-Domain Orthogonal V2X Communication for Diverse Platoon Transmissions - Copy.pdf - Accepted Version Download (895kB) | Preview

Abstract

Driven by vehicle-to-vehicle (V2V) and vehicle-to-infrastructure (V2I) communication techniques, platoons can not only improve road safety and throughput but also centralize the resources of composed vehicles to enhance sensing and computation capabilities, thus contributing to the deployment of vehicular edge computing (VEC). Nevertheless, achieving reliable V2I and V2V communications is challenging due to the rapidly varying channel states caused by high-speed platoons and the potential severe inter-vehicle interferences. To tackle this issue, utilizing the resources in both delay-Doppler (DD) and time-frequency (TF) domains is a promising solution to provide reliable platoon communications and enhance data transmission efficiency, but accompanied by symbol spreading and interferences. This paper proposes a multi-domain orthogonal vehicle-to-everything (V2X) communication scheme, where the orthogonality and multi-periodicity of resource blocks between DD and TF domains are proven and then exploited in platoon communications. Specifically, an orthogonal time frequency space (OTFS)-based resource allocation model is proposed that connects the orthogonal DD-domain resource allocation for V2I links with the orthogonal TF resource blocks for V2V links under different cycles. With DD and TF resource blocks allocated separately at coarse- and fine-granularity under power control, vehicle users' transmission efficiency is maximized, which is a non-convex problem with closely coupled variables in multi-domain. To tackle this issue, the optimal V2V transmit power is firstly derived in closed form, and then a two-layer resource allocation algorithm is proposed to solve the primal problem. Numerical results validate that our proposed scheme can significantly improve efficiency, reliability, and adaptability over benchmark schemes.

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