Goal-Oriented Source Coding and Filtering for Vehicular Communications

Vehicle-to-everything (V2X) networks will constitute a prominent application in future generations of cellular networks, definitely transforming our conception of transportation systems. A major challenge in V2X networks is the vast amount of data generated by the large number of sensors in the vehi...

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Bibliographic Details
Published in:IEEE internet of things journal 2024-06, Vol.11 (11), p.19804-19822
Main Authors: Gimenez-Guzman, Jose Manuel, Leyva-Mayorga, Israel, Popovski, Petar
Format: Article
Language:English
Subjects:
6G mobile communication
Bloom filter (BF)
Cellular communication
Codes
Coding
Delays
discontinuous reception (DRX)
Energy consumption
Filtration
goal-oriented (GO) communications
intelligent transportation systems (ITSs)
Internet of Things
Semantics
Sensors
Source coding
Traffic delay
Transportation networks
Transportation systems
Vehicle-to-everything
vehicle-to-everything (V2X)
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Summary:Vehicle-to-everything (V2X) networks will constitute a prominent application in future generations of cellular networks, definitely transforming our conception of transportation systems. A major challenge in V2X networks is the vast amount of data generated by the large number of sensors in the vehicles, which saturates the wireless links. As it is not possible to meet the throughput, timing, and reliability requirements for the total bulk of generated data, one needs to filter out data based on the actual communication goal. In this article, we present an architecture and diverse options to implement filtering and source coding for goal-oriented (GO) vehicular communications. We illustrate how filtering and source coding contribute to meeting the strict delay requirements while maintaining energy-efficient operation. Our results show that GO communications, performed as the combination of Bloom filtering and GO source coding, can greatly contribute not only to reduce the energy consumption by up to \mathbf {30} % but also to decrease delay, which in turn increases the supported amount of delay-sensitive traffic by up to 819.2%.
ISSN:2327-4662
2327-4662
DOI:10.1109/JIOT.2024.3367438