Random Access Transport Capacity

TL;DR

This paper introduces a new metric called random access transport capacity to measure end-to-end throughput in multihop wireless networks with uncoordinated transmissions, providing analytical bounds and optimal parameters.

Contribution

It develops a closed-form upper bound for the new metric and derives optimal hop count and success probability, confirming the square root scaling law with exact constants.

Findings

Upper bound accurately predicts optimal hop count and success probability

Optimal number of hops follows the square root scaling law

Numerical results validate the analytical bounds

Abstract

We develop a new metric for quantifying end-to-end throughput in multihop wireless networks, which we term random access transport capacity, since the interference model presumes uncoordinated transmissions. The metric quantifies the average maximum rate of successful end-to-end transmissions, multiplied by the communication distance, and normalized by the network area. We show that a simple upper bound on this quantity is computable in closed-form in terms of key network parameters when the number of retransmissions is not restricted and the hops are assumed to be equally spaced on a line between the source and destination. We also derive the optimum number of hops and optimal per hop success probability and show that our result follows the well-known square root scaling law while providing exact expressions for the preconstants as well. Numerical results demonstrate that the upper bound is accurate for the purpose of determining the optimal hop count and success (or outage) probability.