Traffic-Aware Sensing-Based Semi-Persistent Scheduling for High Efficacy of C-V2X Networks

Chourasia, Anshika and Tamma, Bheemarjuna Reddy and Franklin, Antony (2021) Traffic-Aware Sensing-Based Semi-Persistent Scheduling for High Efficacy of C-V2X Networks. In: 94th IEEE Vehicular Technology Conference, VTC 2021-Fall, 27 September 2021 through 30 September 2021, Virtual, Online.

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3GPP has introduced C-V2X technology in the Rel. 14 for improving road safety. There are two modes of vehicular communication in C-V2X viz., Mode 3 and Mode 4. Since Mode 4 allows vehicles to communicate with each other even outside the cellular coverage, it is acknowledged as the baseline mode. In Mode 4, vehicles select the best available least interfered radio resource by utilising Semi-Persistent Scheduling (SPS) in a distributed fashion. Medium Access Control (MAC) parameters like pKeep (probability of keeping a radio resource) and Resource Counter (RC) affect the duration of radio resource collision, so these need to be configured carefully for efficient C-V2X communication. This paper explicates the impact of pKeep and RC on the overall performance of C-V2X system. A new algorithm called Traffic-Aware SPS (TA-SPS) is then proposed, which optimally configures these parameters according to the current density of road traffic by estimating it from periodic Cooperative Awareness Messages (CAMs) broadcasted by the vehicles. By reducing the number of resource collisions, TA-SPS increases transmission reliability of the C-V2X system. Through extensive simulation studies, we show how TA-SPS outperforms the traditional SPS in mixed road traffic scenarios. © 2021 IEEE.

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IITH Creators:
IITH CreatorsORCiD
Tamma, Bheemarjuna Reddy
Franklin, AntonyUNSPECIFIED
Item Type: Conference or Workshop Item (Paper)
Uncontrolled Keywords: Cellular coverage; Control parameters; Extensive simulations; Performance; Radio resources; Road safety; Road traffic; Traffic aware; Transmission reliability; Vehicular communications
Subjects: Computer science
Divisions: Department of Computer Science & Engineering
Depositing User: . LibTrainee 2021
Date Deposited: 06 Oct 2022 11:53
Last Modified: 06 Oct 2022 11:53
Publisher URL:
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