Skip to main page content
U.S. flag

An official website of the United States government

Dot gov

The .gov means it’s official.
Federal government websites often end in .gov or .mil. Before sharing sensitive information, make sure you’re on a federal government site.

Https

The site is secure.
The https:// ensures that you are connecting to the official website and that any information you provide is encrypted and transmitted securely.

Access keys NCBI Homepage MyNCBI Homepage Main Content Main Navigation
. 2023 Jul 29;23(15):6782.
doi: 10.3390/s23156782.

Evaluating the Performance of Proposed Switched Beam Antenna Systems in Dynamic V2V Communication Networks

Affiliations

Evaluating the Performance of Proposed Switched Beam Antenna Systems in Dynamic V2V Communication Networks

Tahir H Ahmed et al. Sensors (Basel). .

Abstract

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.

Keywords: 5G; V2V; intelligent transportation system; vehicular safety.

PubMed Disclaimer

Conflict of interest statement

The authors declare no conflict of interest.

Figures

Figure 1
Figure 1
Comparative structural analysis of existing and proposed architectures.
Figure 2
Figure 2
Structural explanation of HPBW and FNBW lobes.
Figure 3
Figure 3
Proposed beam-to-beam power connection.
Figure 4
Figure 4
Concept of the proposed algorithm in case of real-time PDR failure.
Figure 5
Figure 5
Experimental and working structure of the algorithm.
Figure 6
Figure 6
Time to collision in seconds with respect to vehicular speed.
Figure 7
Figure 7
BER calculation with respect to distance in meters.
Figure 8
Figure 8
PER calculation with respect to distance in meters.
Figure 9
Figure 9
Calculation of average throughput in Mbps.
Figure 10
Figure 10
Beam switching and selection probability liaise with DSRC range.
Figure 11
Figure 11
Calculation of computational complexity in various environments.
Figure 12
Figure 12
Estimation of the computational complexity factor with respect to beam power efficiency.
Figure 13
Figure 13
Estimation of the computational complexity factor with respect to vehicular density.
Figure 14
Figure 14
Communication range between vehicles at different time intervals.
Figure 15
Figure 15
Effect of computational complexity on V2V link quality.
Figure 16
Figure 16
Algorithm execution time with respect to vehicular density.
Figure 17
Figure 17
Algorithm execution time in an antifailure algorithmic system.
Figure 18
Figure 18
ns3 vehicular node visualization with message communication data rate.

References

    1. Liu X., Liu Y., Chen Y., Hanzo L. Enhancing the fuel-economy of V2I-assisted autonomous driving: A reinforcement learning approach. IEEE Trans. Veh. Technol. 2020;69:8329–8342. doi: 10.1109/TVT.2020.2996187. - DOI
    1. Gündoğan C., Kietzmann P., Lenders M.S., Petersen H., Frey M., Schmidt T.C., Shzu-Juraschek F., Wählisch M. The impact of networking protocols on massive M2M communication in the industrial IoT. IEEE Trans. Netw. Serv. Manag. 2021;18:4814–4828. doi: 10.1109/TNSM.2021.3089549. - DOI
    1. Zhou S., Wei C., Song C., Pan X., Chang W., Yang L. Short-term traffic flow prediction of the smart city using 5G internet of vehicles based on edge computing. IEEE Trans. Intell. Transp. Syst. 2022;24:2229–2238. doi: 10.1109/TITS.2022.3147845. - DOI
    1. Ahmad S.A., Hajisami A., Krishnan H., Ahmed-Zaid F., Moradi-Pari E. V2V system congestion control validation and performance. IEEE Trans. Veh. Technol. 2019;68:2102–2110. doi: 10.1109/TVT.2019.2893042. - DOI
    1. Gupta M., Benson J., Patwa F., Sandhu R. Secure V2V and V2I communication in intelligent transportation using cloudlets. IEEE Trans. Serv. Comput. 2020;15:1912–1925. doi: 10.1109/TSC.2020.3025993. - DOI

LinkOut - more resources