This paper investigates the throughput capacity of a flow crossing a multi-hop wireless network, whose geometry is characterized by general randomness laws including Uniform, Poisson, Heavy-Tailed distributions for both the nodes' densities and the number of hops. The key contribution is to demonstrate \textit{how} the \textit{per-flow throughput} depends on the distribution of 1) the number of nodes Nj inside hops' interference sets, 2) the number of hops K, and 3) the degree of spatial correlations. The randomness in both Nj's and K is advantageous, i.e., it can yield larger scalings (as large as Θ(n)) than in non-random settings. An interesting consequence is that the per-flow capacity can exhibit the opposite behavior to the network capacity, which was shown to suffer from a logarithmic decrease in the presence of randomness. In turn, spatial correlations along the end-to-end path are detrimental by a logarithmic term.
@article{arxiv.1307.7271,
title = {On the Catalyzing Effect of Randomness on the Per-Flow Throughput in Wireless Networks},
author = {Florin Ciucu and Jens Schmitt},
journal= {arXiv preprint arXiv:1307.7271},
year = {2013}
}