Distributed Learning for Vehicular Dynamic Spectrum Access in Autonomous Driving
Open accessAbstract
Reliable wireless communication between the autonomously driving cars is one of the fundamental needs for guaranteeing passenger safety and comfort. However, when the number of communicating cars increases, the transmission quality may be significantly degraded due to too high occupancy radio of the used frequency band. In this paper, we concentrate on the autonomous vehicle-platooning use-case, where intra-platoon communication is done in the dynamically selected frequency band, other than nominally devoted for such purposes. The carrier selection is done in a flexible manner with the support of the context database located at the roadside unit (edge of wireless communication infrastructure). However, as the database delivers only context information to the platoons’ leaders, the final decision is made separately by the individual platoons, following the suggestions made by the artificial intelligence algorithms. In this work, we concentrate on a lightweight Q-learning solution, that could be successfully implemented in each car for dynamic channel selection.
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Dynamic Spectrum Access (DSA) is an emerging technology that enables efficient spectrum utilization in V2X communication systems.
“Dynamic Spectrum Access (DSA) [103], [104], [105] is another emerging technology that enables efficient spectrum utilization in V2X communication systems.”
From Towards 6G V2X Sidelink: Survey of Resource Allocation—Mathematical Formulations, Challenges, and Proposed Solutions (2024) · cites this paper as [104]
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Annu, & Rajalakshmi, P. (2024) · IEEE Open Journal of Vehicular Technology · doi:10.1109/ojvt.2024.3368240 · Cited by 73 · see citing works
Enhancing V2X Communications with UAV-mounted Reconfigurable Intelligent Surfaces
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- Authors
- Sroka, P., & Kliks, A.
- Affiliations
- Poznan University of Technology,Institute of Radiocommunications,Poznań,Poland
- Poznań University of Technology (PL)
- ORCID
- Kliks, Adrian
- Venue
- 2022 IEEE International Conference on Pervasive Computing and Communications Workshops and other Affiliated Events (PerCom Workshops)
- Publisher
- IEEE
- Published
- 2022-03-21
- Pages
- 605-610
- OpenAlex
- W4229038700
- Cited by
- 4
- References
- 18
- Citations by year
- 2025: 1 · 2024: 2 · 2023: 1
- FWCI
- 1.62
- Type
- conference paper
- Language
- en
- Open access
- green
- arxiv.org
- Locations
- IEEE International Conference on Pervasive Computing and Communications Workshops (PerCom Workshops) (publishedVersion)
- arXiv (Cornell University) (submittedVersion)
- arXiv (Cornell University)
- Topics
- Physical Sciences › Engineering › Electrical and Electronic Engineering › Vehicular Ad Hoc Networks (VANETs)
- Physical Sciences › Computer Science › Computer Networks and Communications › Cognitive Radio Networks and Spectrum Sensing
- Physical Sciences › Computer Science › Computer Networks and Communications › Wireless Networks and Protocols
- Keywords
- autonomous driving, vehicle platooning, distributed learning, Q-learning, dynamic channel selection, edge computing, roadside units
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