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Enhancing Groupcasting Reliability in the Multi-Platoon Environment Through a Multi-Relay-Vehicle Adjustment Mechanism

Research output: Chapter in Book/Report/Conference proceeding › Conference contribution

Abstract

In 5G platoon communications, the Platoon Leader (PL) can adopt groupcasting to transmit messages to all Platoon Member (PM) vehicles. However, due to the limited range of transmission, a PM vehicle must act as the Platoon Relay (PR) vehicle to retransmit messages to other PM vehicles that are outside PL's groupcasting range. This work introduces a 2-Step relay vehicle selection method called Platoon Relay Vehicle Selection Achieving the Maximum Groupcasting Reliability (PRVS-MGR). The first Step of PRVS-MGR formulates a tripartite matching problem among the allocated subchannel, the PL or PR vehicle, and the individual entity to ensure efficient resource allocation for groupcasting. In the second Step, PRVSMGR proposes a scheme for selecting PR vehicles to enhance groupcasting reliability. The simulation results show that the proposed method has the better performance in terms of spectral efficiency, transmission latency and overall reliability of platoon groupcasting.

Original languageEnglish
Title of host publicationProceedings - 2025 European Conference on Communication Systems, ECCS 2025
PublisherInstitute of Electrical and Electronics Engineers Inc.
Pages20-27
Number of pages8
ISBN (Electronic)9798331514228
DOIs
Publication statusPublished - 2025
Event5th European Conference on Communication Systems, ECCS 2025 - Vienna, Austria
Duration: 2025 May 21 → 2025 May 23

Publication series

NameProceedings - 2025 European Conference on Communication Systems, ECCS 2025

Conference

Conference5th European Conference on Communication Systems, ECCS 2025
Country/TerritoryAustria
CityVienna
Period25-05-21 → 25-05-23

All Science Journal Classification (ASJC) codes

  • Artificial Intelligence
  • Computer Networks and Communications
  • Computer Science Applications
  • Statistics, Probability and Uncertainty
  • Control and Optimization

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