Dice the TX Power - Improving Awareness Quality in VANETs by Random Transmit Power Selection

Future safety-related vehicular applications require reliable information exchange provided by cooperative Vehicular Ad-hoc NETworks (VANETs). Although the vehicular WLAN standard IEEE 802.11p has been adapted to the challenging vehicular environment, it has not been adapted to the stringent communication requirements imposed by vehicular applications. In particular, broadcast transmissions are mostly periodic and initiated at common TX powers. This makes potential interferences recurring instead of spurious and lowers the performance of medium access for vehicular applications. In this paper, we propose to leverage recurring interferences by randomly selecting each TX power following a given probability distribution. Such randomization reduces the chances of recurring interferences, and the probability distribution provides control to the applications regarding the required Awareness Quality, in particular by providing a higher Awareness Quality at close range. This concept also reduces congestions by transmitting less at high distances. It is transparent to the applications, and manages to improve the Awareness Quality in a dense highway by a factor 2 to 20, yet at a factor 2 to 3 lower channel load

Connectivity Analysis of Directed Highway VANETs using Graph Theory

Graph theory is a promising approach in handling the problem of estimating the connectivity probability of vehicular ad-hoc networks (VANETs). With a communication network represented as graph, graph connectivity indicators become valid for connectivity analysis of communication networks as well. In this article, we discuss two different graph-based methods for VANETs connectivity analysis showing that they capture the same behavior as estimated using probabilistic models. The study is, then, extended to include the case of directed VANETs, resulting from the utilization of different communication ranges by different vehicles. Overall, the graph-based methods prove a robust performance, as they can be simply diversified into scenarios that are too complex to acquire a rigid probabilistic model for them.Comment: 21 pages, 6 figure

Decentralized Congestion Control Algorithm for Vehicle to Vehicle Networks Using Oscillating Transmission Power

Wireless access in vehicular environments (WAVE) is a vehicle to vehicle (V2V) communications technology which could help prevent up to 82% of non-impaired accidents, according to the US DOT. A 2013 study by the World Health Organization estimated 2,227 road fatalities in 2009 alone. Currently the channel that is responsible for a vehicle’s awareness of others suffers from congestion at moderate loads. In this paper we propose a novel method for adjusting the transmission power in a pattern which alternates between high and low powered transmissions. We modify one commonly used decentralized congestion control (DCC) algorithm, LIMERIC, and compare the power adaptation model against two controls. WAVE supports a 300 meter transmission radius, however, less than 200 vehicles can communicate at the target rate of 10 transmissions per second. We demonstrate that our algorithm reduces the number of packets received by distant vehicles, while maintaining a higher packet rate to the closer vehicles, for which a higher rate is more important