Performance Analysis of Cellular-V2X with Adaptive and Selective Power Control
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Abstract (arXiv)
LTE based Cellular Vehicle-To-Everything (C-V2X) allows vehicles to communicate with each other directly without the need for infrastructure and is expected to be a critical enabler for connected and autonomous vehicles. V2X communication based safety applications are built on periodic broadcast of basic safety messages with vehicle state information. Vehicles use this information to identify collision threats and take appropriate countermeasures. As the vehicle density increases, these broadcasts can congest the communication channel resulting in increased packet loss; fundamentally impacting the ability to identify threats in a timely manner. To address this issue, it is important to incorporate a congestion control mechanism. Congestion management scheme based on rate and power control has proved to be effective for DSRC. In this paper, we investigate the suitability of similar congestion control to C-V2X with particular focus on transmit power control. In our evaluation, we include periodic basic safety messages and high priority event messages that are generated when an event such as hard braking occurs. Our study reveals that while power control does not improve packet delivery performance of basic safety messages, it is beneficial to high priority event message delivery. In this paper, we investigate the reasons for this behavior using simulations and analysis.
Key facts. Cited by 4 papers in the map (data through 7 Oct 2026). First posted on arXiv 8 Aug 2020.
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Citing papers per year: 2021: 3; 2022: 1.
4 papers.
- 2021Social Coordination and Altruism in Autonomous Drivingcited by 28
- 2022Robustness and Adaptability of Reinforcement Learning based Cooperative Autonomous Driving in Mixed-autonomy Trafficcited by 15
- 2021Altruistic Maneuver Planning for Cooperative Autonomous Vehicles Using Multi-agent Advantage Actor-Criticcited by 11
- 2021Towards Learning Generalizable Driving Policies from Restricted Latent Representationscited by 4
- 2022Robustness and Adaptability of Reinforcement Learning based Cooperative Autonomous Driving in Mixed-autonomy Traffic2 Feb 2022
- 2021Towards Learning Generalizable Driving Policies from Restricted Latent Representations5 Nov 2021
- 2021Altruistic Maneuver Planning for Cooperative Autonomous Vehicles Using Multi-agent Advantage Actor-Critic12 Jul 2021
- 2021Social Coordination and Altruism in Autonomous Driving1 Jul 2021