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Open AccessJournal ArticleDOI

Connectivity of soft random geometric graphs

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TLDR
In this paper, it was shown that the probability of full connectivity is governed by having no isolated vertices, itself governed by a Poisson approximation for the number of isolated nodes.
Abstract
Consider a graph on $n$ uniform random points in the unit square, each pair being connected by an edge with probability $p$ if the inter-point distance is at most $r$. We show that as $n\to\infty$ the probability of full connectivity is governed by that of having no isolated vertices, itself governed by a Poisson approximation for the number of isolated vertices, uniformly over all choices of $p,r$. We determine the asymptotic probability of connectivity for all $(p_n,r_n)$ subject to $r_n=O(n^{-\varepsilon})$, some $\varepsilon >0$. We generalize the first result to higher dimensions and to a larger class of connection probability functions.

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Proceedings ArticleDOI

Random graphs

TL;DR: Some of the major results in random graphs and some of the more challenging open problems are reviewed, including those related to the WWW.
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Continuum percolation: References

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Clustering Implies Geometry in Networks.

TL;DR: It is shown that random graphs in which expected degree and clustering of every node are fixed to some constants are equivalent to random geometric graphs on the real line, if clustering is sufficiently strong.
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Random geometric graphs with general connection functions.

TL;DR: Here the connection probability of a dense network in a convex domain in two or three dimensions is expressed in terms of contributions from boundary components for a very general class of connection functions.
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Hyperbolic graph generator

TL;DR: This paper presents a computer program to generate random graphs from other well-known graph ensembles, such as the soft configuration model, random geometric graphs on a circle, or Erdős–Renyi random graphs.
References
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Journal ArticleDOI

The capacity of wireless networks

TL;DR: When n identical randomly located nodes, each capable of transmitting at W bits per second and using a fixed range, form a wireless network, the throughput /spl lambda/(n) obtainable by each node for a randomly chosen destination is /spl Theta/(W//spl radic/(nlogn)) bits persecond under a noninterference protocol.
Book

Fundamentals of Wireless Communication

TL;DR: In this paper, the authors propose a multiuser communication architecture for point-to-point wireless networks with additive Gaussian noise detection and estimation in the context of MIMO networks.
Proceedings ArticleDOI

Random graphs

TL;DR: Some of the major results in random graphs and some of the more challenging open problems are reviewed, including those related to the WWW.
Book

Random Geometric Graphs

TL;DR: This chapter discusses probabilistic ingredients, the largest component for a binomial process, and connectedivity and the number of components in a graph-like model.
Book ChapterDOI

Critical Power for Asymptotic Connectivity in Wireless Networks

Piyush Gupta, +1 more
TL;DR: It is shown that if n nodes are placed in a disc of unit area in !
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