5 research outputs found
Information-theoretic Capacity of Clustered Random Networks
We analyze the capacity scaling laws of clustered ad hoc networks in which
nodes are distributed according to a doubly stochastic shot-noise Cox process.
We identify five different operational regimes, and for each regime we devise a
communication strategy that allows to achieve a throughput to within a
poly-logarithmic factor (in the number of nodes) of the maximum theoretical
capacity.Comment: 6 pages, in Proceedings of ISIT 201
Laplace Functional Ordering of Point Processes in Large-scale Wireless Networks
Stochastic orders on point processes are partial orders which capture notions
like being larger or more variable. Laplace functional ordering of point
processes is a useful stochastic order for comparing spatial deployments of
wireless networks. It is shown that the ordering of point processes is
preserved under independent operations such as marking, thinning, clustering,
superposition, and random translation. Laplace functional ordering can be used
to establish comparisons of several performance metrics such as coverage
probability, achievable rate, and resource allocation even when closed form
expressions of such metrics are unavailable. Applications in several network
scenarios are also provided where tradeoffs between coverage and interference
as well as fairness and peakyness are studied. Monte-Carlo simulations are used
to supplement our analytical results.Comment: 30 pages, 5 figures, Submitted to Hindawi Wireless Communications and
Mobile Computin