Random linear multihop relaying in a general field of interferers using spatial Aloha

TL;DR

This paper models multihop relaying in a Poisson field of interferers using spatial Aloha, analyzing performance in vehicular and planar networks, and explores how node clustering affects routing efficiency and delay.

Contribution

It provides explicit performance evaluations for multihop relaying in Poisson fields, including the impact of clustering and fixed relays, with applications to vehicular and planar ad-hoc networks.

Findings

Clustering of interferers reduces outage probability.

Clustering increases mean end-to-end delay.

Adding fixed relays improves routing performance.

Abstract

In our basic model, we study a stationary Poisson pattern of nodes on a line embedded in an independent planar Poisson field of interfering nodes. Assuming slotted Aloha and the signal-to-interference-and-noise ratio capture condition, with the usual power-law path loss model and Rayleigh fading, we explicitly evaluate several local and end-to-end performance characteristics related to the nearest-neighbor packet relaying on this line, and study their dependence on the model parameters (the density of relaying and interfering nodes, Aloha tuning and the external noise power). Our model can be applied in two cases: the first use is for vehicular ad-hoc networks, where vehicles are randomly located on a straight road. The second use is to study a typical route traced in a (general) planar ad-hoc network by some routing mechanism. The approach we have chosen allows us to quantify the non-efficiency of long-distance routing in pure ad-hoc networks and evaluate a possible remedy for it in the form of additional fixed relaying nodes, called road-side units in a vehicular network. It also allows us to consider a more general field of interfering nodes and study the impact of the clustering of its nodes the routing performance. As a special case of a field with more clustering than the Poison field, we consider a Poisson-line field of interfering nodes, in which all the nodes are randomly located on random straight lines. The comparison to our basic model reveals a paradox: clustering of interfering nodes decreases the outage probability of a single (typical) transmission on the route, but increases the mean end-to-end delay.