49 research outputs found
Fine-Grained Reliability for V2V Communications around Suburban and Urban Intersections
Safe transportation is a key use-case of the 5G/LTE Rel.15+ communications,
where an end-to-end reliability of 0.99999 is expected for a vehicle-to-vehicle
(V2V) transmission distance of 100-200 m. Since communications reliability is
related to road-safety, it is crucial to verify the fulfillment of the
performance, especially for accident-prone areas such as intersections. We
derive closed-form expressions for the V2V transmission reliability near
suburban corners and urban intersections over finite interference regions. The
analysis is based on plausible street configurations, traffic scenarios, and
empirically-supported channel propagation. We show the means by which the
performance metric can serve as a preliminary design tool to meet a target
reliability. We then apply meta distribution concepts to provide a careful
dissection of V2V communications reliability. Contrary to existing work on
infinite roads, when we consider finite road segments for practical deployment,
fine-grained reliability per realization exhibits bimodal behavior. Either
performance for a certain vehicular traffic scenario is very reliable or
extremely unreliable, but nowhere in relatively proximity to the average
performance. In other words, standard SINR-based average performance metrics
are analytically accurate but can be insufficient from a practical viewpoint.
Investigating other safety-critical point process networks at the meta
distribution-level may reveal similar discrepancies.Comment: 27 pages, 6 figures, submitted to IEEE Transactions on Wireless
Communication
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
pH-Impedance testing in gastro-oesophageal reflux
Gastro-Oesophageal Reflux Diseases
(GORD) are one of the most common
reasons for physician consultation. Out
of 2,056 individuals randomly surveyed
in the United States and Canada, up
to 35% had more than one upper
gastrointestinal symptom occurring
at least once per week with at least
moderate intensity.
Investigation of GORD has evolved
over the years.peer-reviewe
On the Fundamentals of Stochastic Spatial Modeling and Analysis of Wireless Networks and its Impact to Channel Losses
With the rapid evolution of wireless networking, it becomes vital to ensure transmission reliability, enhanced connectivity, and efficient resource utilization. One possible pathway for gaining insight into these critical requirements would be to explore the spatial geometry of the network. However, tractably characterizing the actual position of nodes for large wireless networks (LWNs) is technically unfeasible. Thus, stochastical spatial modeling is commonly considered for emulating the random pattern of mobile users. As a result, the concept of random geometry is gaining attention in the field of cellular systems in order to analytically extract hidden features and properties useful for assessing the performance of networks. Meanwhile, the large-scale fading between interacting nodes is the most fundamental element in radio communications, responsible for weakening the propagation, and thus worsening the service quality. Given the importance of channel losses in general, and the inevitability of random networks in real-life situations, it was then natural to merge these two paradigms together in order to obtain an improved stochastical model for the large-scale fading. Therefore, in exact closed-form notation, we generically derived the large-scale fading distributions between a reference base-station and an arbitrary node for uni-cellular (UCN), multi-cellular (MCN), and Gaussian random network models. In fact, we for the first time provided explicit formulations that considered at once: the lattice profile, the users’ random geometry, the spatial intensity, the effect of the far-field phenomenon, the path-loss behavior, and the stochastic impact of channel scatters. Overall, the results can be useful for analyzing and designing LWNs through the evaluation of performance indicators. Moreover, we conceptualized a straightforward and flexible approach for random spatial inhomogeneity by proposing the area-specific deployment (ASD) principle, which takes into account the clustering tendency of users. In fact, the ASD method has the advantage of achieving a more realistic deployment based on limited planning inputs, while still preserving the stochastic character of users’ position. We then applied this inhomogeneous technique to different circumstances, and thus developed three spatial-level network simulator algorithms for: controlled/uncontrolled UCN, and MCN deployments