Abstract
Unmanned aerial vehicle mounted base stations (UAV-BSs) are expected to become an integral component of future intelligent transportation systems, which can provide seamless coverage for vehicles on highways with poor cellular infrastructures. Motivated by the above, this paper proposes an aerial-ground integrated vehicular networking architecture, based on which a UAV-vehicle collaboration perspective is proposed. Specifically, an emerging vehicle-to-UAV (V2U) and vehicle-to-vehicle (V2V) collaboration framework is first presented to facilitate diverse vehicular applications. Next, we investigate the coverage radius maximization problem by optimizing the UAV-BS altitude. Meanwhile, by taking the channel state information (CSI) feedback delay into account, we formulate a V2U communication sum rate maximization problem by optimizing the power control and spectrum allocation, which is constrained by the capacity and reliability requirements. Then, we derive the closed-form expression of optimal UAV-BS altitude. Afterwards, we decouple the formulated sum rate maximization problem, and devise an efficient algorithm with polynomial complexity, where the optimal power control and spectrum sharing are solved. Finally, simulation results demonstrate that the maximum coverage radius and optimal UAV-BS altitude can be achieved by our proposed scheme in different urban environments. In addition, our designed scheme can effectively improve the V2U communication sum rate in comparison with the current works.
| Original language | English |
|---|---|
| Pages (from-to) | 5154-5169 |
| Number of pages | 16 |
| Journal | IEEE Transactions on Intelligent Transportation Systems |
| Volume | 25 |
| Issue number | 6 |
| DOIs | |
| State | Published - 1 Jun 2024 |
UN SDGs
This output contributes to the following UN Sustainable Development Goals (SDGs)
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SDG 11 Sustainable Cities and Communities
Keywords
- Aerial-ground integrated vehicular networking architecture
- UAV
- V2U and V2V collaboration
- coverage radius maximization
- sum rate maximization
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