2,114 research outputs found
Two-Hop Connectivity to the Roadside in a VANET Under the Random Connection Model
We compute the expected number of cars that have at least one two-hop path to
a fixed roadside unit in a one-dimensional vehicular ad hoc network in which
other cars can be used as relays to reach a roadside unit when they do not have
a reliable direct link. The pairwise channels between cars experience Rayleigh
fading in the random connection model, and so exist, with probability function
of the mutual distance between the cars, or between the cars and the roadside
unit. We derive exact equivalents for this expected number of cars when the car
density tends to zero and to infinity, and determine its behaviour using
an infinite oscillating power series in , which is accurate for all
regimes. We also corroborate those findings to a realistic situation, using
snapshots of actual traffic data. Finally, a normal approximation is discussed
for the probability mass function of the number of cars with a two-hop
connection to the origin. The probability mass function appears to be well
fitted by a Gaussian approximation with mean equal to the expected number of
cars with two hops to the origin.Comment: 21 pages, 7 figure
Fine-Grained vs. Average Reliability for V2V Communications around Intersections
Intersections are critical areas of the transportation infrastructure
associated with 47% of all road accidents. Vehicle-to-vehicle (V2V)
communication has the potential of preventing up to 35% of such serious road
collisions. In fact, under the 5G/LTE Rel.15+ standardization, V2V is a
critical use-case not only for the purpose of enhancing road safety, but also
for enabling traffic efficiency in modern smart cities. Under this anticipated
5G definition, high reliability of 0.99999 is expected for semi-autonomous
vehicles (i.e., driver-in-the-loop). As a consequence, there is a need to
assess the reliability, especially for accident-prone areas, such as
intersections. We unpack traditional average V2V reliability in order to
quantify its related fine-grained V2V reliability. Contrary to existing work on
infinitely large roads, when we consider finite road segments of significance
to practical real-world deployment, fine-grained reliability exhibits bimodal
behavior. Performance for a certain vehicular traffic scenario is either very
reliable or extremely unreliable, but nowhere in relative proximity to the
average performance.Comment: 5 pages, 4 figures. arXiv admin note: substantial text overlap with
arXiv:1706.1001
Simple Approximations of the SIR Meta Distribution in General Cellular Networks
Compared to the standard success (coverage) probability, the meta
distribution of the signal-to-interference ratio (SIR) provides much more
fine-grained information about the network performance. We consider general
heterogeneous cellular networks (HCNs) with base station tiers modeled by
arbitrary stationary and ergodic non-Poisson point processes. The exact
analysis of non-Poisson network models is notoriously difficult, even in terms
of the standard success probability, let alone the meta distribution. Hence we
propose a simple approach to approximate the SIR meta distribution for
non-Poisson networks based on the ASAPPP ("approximate SIR analysis based on
the Poisson point process") method. We prove that the asymptotic horizontal gap
between its standard success probability and that for the Poisson point
process exactly characterizes the gap between the th moment of the
conditional success probability, as the SIR threshold goes to . The gap
allows two simple approximations of the meta distribution for general
HCNs: 1) the per-tier approximation by applying the shift to each tier
and 2) the effective gain approximation by directly shifting the meta
distribution for the homogeneous independent Poisson network. Given the
generality of the model considered and the fine-grained nature of the meta
distribution, these approximations work surprisingly well.Comment: This paper has been accepted in the IEEE Transactions on
Communications. 14 pages, 13 figure
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