Asymptotic Deployment Gain: A Simple Approach to Characterize the SINR Distribution in General Cellular Networks

TL;DR

This paper introduces the asymptotic deployment gain (ADG), a new metric to compare SINR distributions in general cellular network models, showing that the outage probability slope is universal across motion-invariant processes.

Contribution

It proposes the ADG as a simple, effective way to characterize and compare the high-reliability behavior of various cellular network deployment models.

Findings

The outage probability slope is universal for all motion-invariant models.

The ADG quantifies the horizontal gap in success probabilities between different point processes.

Simulations validate the ADG's effectiveness across various models and fading statistics.

Abstract

In cellular network models, the base stations are usually assumed to form a lattice or a Poisson point process (PPP). In reality, however, they are deployed neither fully regularly nor completely randomly. Accordingly, in this paper, we consider the very general class of motion-invariant models and analyze the behavior of the outage probability (the probability that the signal-to-interference-plus-noise-ratio (SINR) is smaller than a threshold) as the threshold goes to zero. We show that, remarkably, the slope of the outage probability (in dB) as a function of the threshold (also in dB) is the same for essentially all motion-invariant point processes. The slope merely depends on the fading statistics. Using this result, we introduce the notion of the asymptotic deployment gain (ADG), which characterizes the horizontal gap between the success probabilities of the PPP and another point process in the high-reliability regime (where the success probability is near 1). To demonstrate the usefulness of the ADG for the characterization of the SINR distribution, we investigate the outage probabilities and the ADGs for different point processes and fading statistics by simulations.