A Thorough Analysis of Radio Resource Assignment for UAV-Enhanced Vehicular Sidelink Communications
<|reference_start|>A Thorough Analysis of Radio Resource Assignment for UAV-Enhanced Vehicular Sidelink Communications: The rapid expansion of connected and autonomous vehicles (CAVs) and the shift towards millimiter-wave (mmWave) frequencies offer unprecedented opportunities to enhance road safety and traffic efficiency. Sidelink communication, enabling direct Vehicle-to-Vehicle (V2V) communications, play a pivotal role in this transformation. As communication technologies transit to higher frequencies, the associated increase in bandwidth comes at the cost of a severe path and penetration loss. In response to these challenges, we investigate a network configuration that deploys beamforming-capable Unmanned Aerial Vehicles (UAVs) as relay nodes. In this work, we present a comprehensive analytical framework with a groundbreaking performance metric, i.e. average access probability, that quantifies user satisfaction, considering factors across different protocol stack layers. Additionally, we introduce two Radio Resources Assignment (RRA) methods tailored for UAVs. These methods consider parameters such as resource availability, vehicle distribution, and latency requirements. Through our analytical approach, we optimize the average access probability by controlling UAV altitude based on traffic density. Our numerical findings validate the proposed model and strategy, which ensures that Quality of Service (QoS) standards are met in the domain of Vehicle-to-Anything (V2X) sidelink communications.<|reference_end|>
@article{conserva2024a,
    title={A Thorough Analysis of Radio Resource Assignment for UAV-Enhanced
  Vehicular Sidelink Communications},
    author={Francesca Conserva, Francesco Linsalata, Marouan Mizmizi, Maurizio
  Magarini, Umberto Spagnolini, Roberto Verdone and Chiara Buratti},
    journal={arXiv preprint arXiv:2403.12059},
    year={2024},
    archivePrefix={arXiv},
    eprint={2403.12059},
    primaryClass={cs.NI eess.SP}
}