On Throughput Scaling of Wireless Networks: Effect of Node Density and Propagation Model

TL;DR

This paper establishes lower bounds on per-node throughput in wireless networks considering node density and propagation models, revealing different scaling laws depending on network size and density.

Contribution

It provides a simplified derivation of throughput bounds that extend and refine previous results by Gupta and Kumar, incorporating node density and propagation effects.

Findings

Per-node throughput scales as n^{1-γ} for γ<1/2

Per-node throughput scales as (n ln n)^{-1/2} for γ≥1/2

Derived bounds depend on network size and node distribution

Abstract

This paper derives a lower bound to the per-node throughput achievable by a wireless network when n source-destination pairs are randomly distributed throughout a disk of radius $n^\gamma$, $ \gamma \geq 0$, propagation is modeled by attenuation of the form $1/(1+d)^\alpha$, $\alpha >2$, and successful transmission occurs at a fixed rate W when received signal to noise and interference ratio is greater than some threshold $\beta$, and at rate 0 otherwise. The lower bound has the form $n^{1-\gamma}$ when $\gamma < 1/2$, and $(n \ln n)^{-1/2}$ when $\gamma \geq 1/2$. The methods are similar to, but somewhat simpler than, those in the seminal paper by Gupta and Kumar.