Cellular-Based Statistical Model for Mobile Dispersion

TL;DR

This paper develops an unbiased statistical model for node distribution in hexagonal cellular networks, improving accuracy over traditional circular models, and provides a versatile tool for complex network analysis verified by simulations.

Contribution

It introduces a novel unbiased node density model for hexagonal cells and extends it to sectored cells, enhancing the realism of mobile dispersion modeling.

Findings

The hexagon-based model is unbiased and more accurate than circular models.

The modeling tool supports complex network configurations with various parameters.

Simulations confirm the theoretical accuracy of the proposed models.

Abstract

While analyzing mobile systems we often approximate the actual coverage surface and assume an ideal cell shape. In a multi-cellular network, because of its tessellating nature, a hexagon is more preferred than a circular geometry. Despite this reality, perhaps due to the inherent simplicity, only a model for circular based random spreading is available. However, if used, this results an unfair terminal distribution for non-circular contours. Therefore, in this paper we specifically derived an unbiased node density model for a hexagon. We then extended the principle and established stochastic ways to handle sectored cells. Next, based on these mathematical findings, we created a generic modeling tool that can support a complex network with varying position, capacity, size, user density, and sectoring capability. Last, simulation was used to verify the theoretical analysis.