Multi-Hop Connectivity Probability in Infrastructure-Based Vehicular Networks

Abstract

Abstract-Infrastructure-based vehicular networks (consisting of a group of Base Stations (BSs) along the road) will be widely deployed to support Wireless Access in Vehicular Environment (WAVE) and a series of safety and non-safety related applications and services for vehicles on the road. As an important measure of user satisfaction level, uplink connectivity probability is defined as the probability that messages from vehicles can be received by the infrastructure (i.e., BSs) through multi-hop paths. While on the system side, downlink connectivity probability is defined as the probability that messages can be broadcasted from BSs to all vehicles through multi-hop paths, which indicates service coverage performance of a vehicular network. This paper proposes an analytical model to predict both uplink and downlink connectivity probabilities. Our analytical results, validated by simulations and experiments, reveal the trade-off between these two key performance metrics and the important system parameters, such as BS and vehicle densities, radio coverage (or transmission power), and maximum number of hops. This insightful knowledge enables vehicular network engineers and operators to effectively achieve high user satisfaction and good service coverage, with necessary deployment of BSs along the road according to traffic density, user requirements and service types.Index Terms-Vehicular ad-hoc Network (VANET), Wireless Access in Vehicular Environment (WAVE), IEEE 802.11p, IEEE 1609, Connectivity Probability

A Survey on Platoon-Based Vehicular Cyber-Physical Systems

“…Based on the analysis, the required minimum number of RSUs for a straight road is derived under the constraint of the transmission delay. A complementary work was conducted in [123], in which Zhang et al concerned the uplink and downlink connectivity performance between vehicle and RSUs in multi-hop scenarios. Some trade-offs between the key performance metrics and the important system parameters were fully investigated, such as the inter-RSUs distance and the traffic density, the radio coverage and the maximum number of hops.…”

A Survey on Infrastructure-Based Vehicular Networks

“…(i) Broadcast [20] (ii) Channel allocation [21] (iii) Caching [22] (iv) Content download [23,24] (v) Data dissemination [25] (vi) Data aggregation [26] (vii) Data scheduling [27] (viii) Gaming & streaming [28,29] (ix) Gateway [11,22,30] (x) Hand-off [31][32][33] (xi) Vehicles localization [34,35] (xii) QoS [36][37][38][39] (xiii) Real-time support [40][41][42] (xiv) Routing [14,43,44] (xv) Security [45][46][47][48] (xvi) Multihop comm [49].…”

“…In terms of architecture, we notice analytic models for the selection of communicating devices [88,93], proposals for light-weight infrastructures employing relay nodes [13], virtual infrastructures using the publish-subscribe paradigm [52], biologically inspired solutions [94], and reputation mechanisms [45]. In terms of communication, we notice works addressing routing [14,44,95], cooperative data dissemination [22], QoS controlled media access [36], multihop communication [49], content download [23], and data traffic [96,97]. Mobility is addressed in [98][99][100].…”

Co-DDTMA: Cooperative Distributed TDMA for Vehicular Networks

“…1).Since wireless transmission range is much larger than the width of the road, the 1-D network model is a good approximation of VANET [1,3]. Nodes are placed on the road according to a Poisson point process [3,16]. With the network densityβ(in nodes per meter), the probability p(i,l) of finding i nodes in the lane of l length is given by: ,... …”

“…3).For communication models, the unit disk is considered in this paper [16]. All vehicles have the same communication capabilities with the same transmission range R. Within the transmission range of a source, a node can receive the transmitted packet successfully with probability p, taking account of the channel quality.…”