One-Hop Throughput of Wireless Networks with Random Connections

TL;DR

This paper analyzes the throughput capacity of one-hop wireless networks with random, i.i.d. channel connections, proposing a scheme that nearly achieves the theoretical upper bound for large networks.

Contribution

It introduces a new scheme that achieves near-optimal throughput scaling of order n^{1/3- ext{delta}} in random connection models, matching the known upper bound.

Findings

Achieves throughput scaling of order n^{1/3- ext{delta}} for any ext{delta}>0

Establishes the throughput capacity for connection models with finite mean and variance

Provides a scheme approaching the theoretical upper bound

Abstract

We consider one-hop communication in wireless networks with random connections. In the random connection model, the channel powers between different nodes are drawn from a common distribution in an i.i.d. manner. An scheme achieving the throughput scaling of order $n^{1/3-\delta}$, for any $\delta>0$, is proposed, where $n$ is the number of nodes. Such achievable throughput, along with the order $n^{1/3}$ upper bound derived by Cui et al., characterizes the throughput capacity of one-hop schemes for the class of connection models with finite mean and variance.