General Capacity for Deterministic Dissemination in Wireless Ad Hoc Networks

TL;DR

This paper investigates the capacity scaling laws of deterministic dissemination in general homogeneous random wireless networks under the physical model, unifying various scenarios and closing gaps between known bounds.

Contribution

It provides a unified analysis of network capacity for general homogeneous random models, addressing different densities, session types, and session counts, and tightens existing bounds.

Findings

Derived general upper bounds on capacity for arbitrary parameters

Proved bounds are tight using continuum percolation models

Unified capacity analysis for unicast, broadcast, and multicast sessions

Abstract

In this paper, we study capacity scaling laws of the deterministic dissemination (DD) in random wireless networks under the generalized physical model (GphyM). This is truly not a new topic. Our motivation to readdress this issue is two-fold: Firstly, we aim to propose a more general result to unify the network capacity for general homogeneous random models by investigating the impacts of different parameters of the system on the network capacity. Secondly, we target to close the open gaps between the upper and the lower bounds on the network capacity in the literature. The generality of this work lies in three aspects: (1) We study the homogeneous random network of a general node density $\lambda \in [1,n]$, rather than either random dense network (RDN, $\lambda=n$) or random extended network (REN, $\lambda=1$) as in the literature. (2) We address the general deterministic dissemination sessions, \ie, the general multicast sessions, which unify the capacities for unicast and broadcast sessions by setting the number of destinations for each session as a general value $n_d\in[1,n]$. (3) We allow the number of sessions to change in the range $n_s\in(1,n]$, instead of assuming that $n_s=\Theta(n)$ as in the literature. We derive the general upper bounds on the capacity for the arbitrary case of $(\lambda, n_d, n_s)$ by introducing the Poisson Boolean model of continuum percolation, and prove that they are tight according to the existing general lower bounds constructed in the literature.