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Cooperative Resource Status Exchange for Reliable Vehicular Sidelink Broadcasts
| DC Field | Value | Language |
|---|---|---|
| dc.contributor.author | Elsharief, Mahmoud | - |
| dc.contributor.author | Rahman Sabuj, Saifur | - |
| dc.contributor.author | Kwon, Sean | - |
| dc.contributor.author | Jo, Han-Shin | - |
| dc.date.accessioned | 2026-06-24T02:00:15Z | - |
| dc.date.available | 2026-06-24T02:00:15Z | - |
| dc.date.issued | 2026-03 | - |
| dc.identifier.issn | 2687-7813 | - |
| dc.identifier.issn | 2687-7813 | - |
| dc.identifier.uri | https://scholarworks.bwise.kr/hanyang/handle/2021.sw.hanyang/214927 | - |
| dc.description.abstract | Vehicular sidelink communications are essential to autonomous driving, yet broadcast reliability under distributed operation remains constrained by collisions and inefficient resource use. The third-generation partnership project (3GPP) has defined a new radio (NR) for vehicle-to-everything (V2X) Mode 2 for autonomous resource reservation and selection. An important challenge in the design of NR-V2X systems is the efficient allocation of resources. Resource allocation facilitates reliable communication between user equipment (UEs) and other network elements. A cooperative approach among UEs is required to ensure reliable resource allocation and communication in such networks. This paper presents cooperative resource status exchange (CRSE), a cooperative scheme that augments autonomous sidelink broadcasts by disseminating a compact resource status map in each packet. It significantly maximizes the packet reception ratio (PRR) and resource utilization. In addition, CRSE integrates game theory to provide a sophisticated method for analyzing and optimizing resource selection strategies among UEs. The analytical model and simulation results show that CRSE performs better than new radio NR-V2X Mode 2, UE-scheduling, and short-term sensing-based resource selection (STS-RS) in terms of PRR and successful transmission rate. The results show that CRSE improves the PRR by approximately 24.6%, 15.2%, and 12.3% over NR-V2X, UE-scheduling, and STS-RS, respectively. Furthermore, the results demonstrate the possibility of realizing the maximum value of PRR and a successful transmission rate. | - |
| dc.format.extent | 16 | - |
| dc.language | 영어 | - |
| dc.language.iso | ENG | - |
| dc.publisher | IEEE-INST ELECTRICAL ELECTRONICS ENGINEERS INC | - |
| dc.title | Cooperative Resource Status Exchange for Reliable Vehicular Sidelink Broadcasts | - |
| dc.type | Article | - |
| dc.publisher.location | 미국 | - |
| dc.identifier.doi | 10.1109/OJITS.2026.3671296 | - |
| dc.identifier.scopusid | 2-s2.0-105032120102 | - |
| dc.identifier.wosid | 001714467300001 | - |
| dc.identifier.bibliographicCitation | IEEE OPEN JOURNAL OF INTELLIGENT TRANSPORTATION SYSTEMS, v.7, pp 771 - 786 | - |
| dc.citation.title | IEEE OPEN JOURNAL OF INTELLIGENT TRANSPORTATION SYSTEMS | - |
| dc.citation.volume | 7 | - |
| dc.citation.startPage | 771 | - |
| dc.citation.endPage | 786 | - |
| dc.type.docType | Article | - |
| dc.description.isOpenAccess | N | - |
| dc.description.journalRegisteredClass | scopus | - |
| dc.description.journalRegisteredClass | esci | - |
| dc.relation.journalResearchArea | Computer Science | - |
| dc.relation.journalResearchArea | Engineering | - |
| dc.relation.journalResearchArea | Transportation | - |
| dc.relation.journalWebOfScienceCategory | Computer Science, Artificial Intelligence | - |
| dc.relation.journalWebOfScienceCategory | Engineering, Electrical & Electronic | - |
| dc.relation.journalWebOfScienceCategory | Transportation Science & Technology | - |
| dc.subject.keywordPlus | CELLULAR V2X | - |
| dc.subject.keywordPlus | ALLOCATION | - |
| dc.subject.keywordPlus | DESIGN | - |
| dc.subject.keywordPlus | MAC | - |
| dc.subject.keywordAuthor | Resource management | - |
| dc.subject.keywordAuthor | Sidelink | - |
| dc.subject.keywordAuthor | Reliability | - |
| dc.subject.keywordAuthor | Vehicle-to-everything | - |
| dc.subject.keywordAuthor | Sensors | - |
| dc.subject.keywordAuthor | Intelligent transportation systems | - |
| dc.subject.keywordAuthor | Games | - |
| dc.subject.keywordAuthor | Safety | - |
| dc.subject.keywordAuthor | Rail to rail inputs | - |
| dc.subject.keywordAuthor | 3GPP | - |
| dc.subject.keywordAuthor | autonomous resource allocation | - |
| dc.subject.keywordAuthor | NR-V2X | - |
| dc.subject.keywordAuthor | sidelink | - |
| dc.subject.keywordAuthor | vehicle-to-everything | - |
| dc.subject.keywordAuthor | connected and automated vehicles | - |
| dc.subject.keywordAuthor | resource status exchange | - |
| dc.subject.keywordAuthor | PRR | - |
| dc.subject.keywordAuthor | game theory | - |
| dc.identifier.url | https://ieeexplore.ieee.org/document/11422953 | - |
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