Please use this identifier to cite or link to this item: http://dspace.iitrpr.ac.in:8080/xmlui/handle/123456789/4283
Title: Connectivity improvement of hybrid millimeter wave and microwave vehicular networks
Authors: Saluja, D.
Singh, R.
Saluja, N.
Kumar, S.
Keywords: Vehicular network
Mobility
MmWave RAT
Microwave RAT
Connectivity analysis
Hybrid networks
Issue Date: 9-Dec-2022
Abstract: The network connectivity while traveling in a vehicle is an important issue, which needs to be addressed by mobile vehicular networks. This paper proposes a novel scheme to improve the connectivity of mobile vehicular networks. In particular, the paper proposes a medium access control (MAC) layer hybrid mmWave and microwave scheme for vehicular networks, and leverage their capabilities to improve the vehicle’s connectivity. The novel computational model is derived to evaluate the connectivity for the proposed scheme. The model is used for performance analysis of vehicles moving on a multi-lane highway road and getting connectivity with road-side-units (RSUs) deployed along the roads. Our analysis considers that reference VN has perfect channel state information. It is assumed that the RSU radiates ubiquitously on the road surface using microwave radio access technology (RAT), while it radiates directionally towards reference VN using mmWave RAT. For mathematical analysis, the directionality in mmWave RAT is well approximated by a sectored antenna model. The analysis for the proposed scheme is compared with the existing mmWave network and packet data convergence protocol (PDCP) layer hybrid scheme. The analysis claims that the proposed hybrid scheme significantly improves the connectivity performance in mobile vehicular networks over the existing schemes. The computation results are validated with the simulation results. Also, the paper offers parametric analysis for connectivity probability with vehicle speed and slot duration to enable its practical implementation in 5G/6G technologies.
URI: http://localhost:8080/xmlui/handle/123456789/4283
Appears in Collections:Year-2022

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