As newer generations of use cases are added for vehicle-to-everything (V2X) communication, wireless channel congestion is expected in the Intelligent Transport Systems (ITS) band because the band allocation is limited to 20 to 40 MHz in most countries. Since V2X Day1, Day2, and Day3 all adopt periodic broadcast for their most fundamental messages, it is necessary to develop methods for minimizing the amount of periodic broadcast traffic as far as it does not impair the purpose of V2X communication. For this reason, there has been a recent effort to reduce packetization and channel access overhead in the Dedicated Short Range Communication (DSRC) environment. However, no solution has been explored yet in the cellular V2X environment where packetization and channel access methods are different. In this paper, we explore the traffic reduction effect when using intelligent packetization method in addition to packet transmission timing prediction and allocation proposed in our previous work. Simulation results show that the number of wasted resources and packet collisions can be greatly reduced compared to using standard SPS. Consequently, the packet reception ratio (PRR) is increased and the target PRR for safety applications can be achieved at much longer distances.
|Title of host publication
|2023 IEEE 97th Vehicular Technology Conference, VTC 2023-Spring - Proceedings
|Institute of Electrical and Electronics Engineers Inc.
|Published - 2023
|97th IEEE Vehicular Technology Conference, VTC 2023-Spring - Florence, Italy
Duration: 2023 Jun 20 → 2023 Jun 23
|IEEE Vehicular Technology Conference
|97th IEEE Vehicular Technology Conference, VTC 2023-Spring
|23/6/20 → 23/6/23
Bibliographical noteFunding Information:
ACKNOWLEDGMENTS This work was supported by the National Research Foundation of Korea(NRF) grant funded by the Korea government(MSIT) (No. 2020R1A2C3011888).
© 2023 IEEE.
- CPM generation rule
- Cellular V2X
- collective perception
- deep learning
- packet reception ratio (PRR)
ASJC Scopus subject areas
- Computer Science Applications
- Electrical and Electronic Engineering
- Applied Mathematics