Evaluating the Performance of Proposed Switched Beam Antenna Systems in Dynamic V2V Communication Networks.
5G
V2V
intelligent transportation system
vehicular safety
Journal
Sensors (Basel, Switzerland)
ISSN: 1424-8220
Titre abrégé: Sensors (Basel)
Pays: Switzerland
ID NLM: 101204366
Informations de publication
Date de publication:
29 Jul 2023
29 Jul 2023
Historique:
received:
05
07
2023
revised:
17
07
2023
accepted:
20
07
2023
medline:
12
8
2023
pubmed:
12
8
2023
entrez:
12
8
2023
Statut:
epublish
Résumé
This paper develops a novel approach for reliable vehicle-to-vehicle (V2V) communication in various environments. A switched beam antenna is deployed at the transmitting and receiving points, with a beam management system that concentrates the power in each beam using a low-computation algorithm and a potential mathematical model. The algorithm is designed to be flexible for various environments faced by vehicles. Additionally, an anti-failure system is proposed in case the intelligent transportation system (ITS) system fails to retrieve real-time Packet Delivery Ratio (PDR) values related to traffic density. Performance metrics include the time to collision in seconds, the bit error rate (BER), the packet error rate (PER), the average throughput (Mbps), the beam selection probability, and computational complexity factors. The proposed system is compared with traditional systems. Extensive experiments, simulations, and comparisons show that the proposed approach is excellent and reliable for vehicular systems. The proposed study demonstrates an average throughput of 1.7 Mbps, surpassing conventional methods' typical throughput of 1.35 Mbps. Moreover, the bit error rate (BER) of the proposed study is reduced by a factor of 0.1. Additionally, the proposed framework achieves a beam power efficiency of touching to 100% at computational factor of 34. These metrics indicate that the proposed method is both efficient and sufficiently robust.
Identifiants
pubmed: 37571565
pii: s23156782
doi: 10.3390/s23156782
pmc: PMC10422314
pii:
doi:
Types de publication
Journal Article
Langues
eng
Sous-ensembles de citation
IM
Subventions
Organisme : FRGS
ID : MMUE/210058 (FRGS/1/2021/TK02/MMU/02/1) and MMUE/190229 (FRGS/1/2020/TK02/MMU/03/1).