Accurate Characterization of Dynamic Cell Load in Noise-Limited Random Cellular Networks

TL;DR

This paper develops a realistic analytical framework to characterize the dynamic load of typical cells in noise-limited cellular networks, improving upon the mean cell approach by providing more accurate and tractable load estimations.

Contribution

It introduces a new analytical method to accurately model the load distribution of typical cells in noise-limited networks, surpassing previous mean cell approximations.

Findings

Provides the cumulative density function of the typical cell load.

Offers two approximations for the average load, with one in closed-form.

Demonstrates improved realism and tractability over existing methods.

Abstract

The analyses of cellular network performance based on stochastic geometry generally ignore the traffic dynamics in the network. This restricts the proper evaluation and dimensioning of the network from the perspective of a mobile operator. To address the effect of dynamic traffic, recently, the mean cell approach has been introduced, which approximates the average network load by the zero cell load. However, this is not a realistic characterization of the network load, since a zero cell is statistically larger than a random cell drawn from the population of cells, i.e., a typical cell. In this paper, we analyze the load of a noise-limited network characterized by high signal to noise ratio (SNR). The noise-limited assumption can be applied to a variety of scenarios, e.g., millimeter wave networks with efficient interference management mechanisms. First, we provide an analytical framework to obtain the cumulative density function of the load of the typical cell. Then, we obtain two approximations of the average load of the typical cell. We show that our study provides a more realistic characterization of the average load of the network as compared to the mean cell approach. Moreover, the prescribed closed-form approximation is more tractable than the mean cell approach.