Emergence of the Traffic Autonomous Zone (TAZ) for Telecommunication Operations from Spatial Heterogeneity in Cellular Networks

TL;DR

This paper introduces the Traffic Autonomous Zone (TAZ) concept, a novel regionalization method for telecommunication networks that identifies spatial clusters to improve management and captures city self-organization.

Contribution

It proposes a new regionalization approach for telecommunication networks that balances multiple metrics and captures urban self-organization, outperforming existing methods like Louvain.

Findings

The TAZ approach effectively identifies spatial clusters in real telecommunication data.

Compared to Louvain, TAZ offers a Pareto-efficient balance among multiple metrics.

The method captures the self-organized structure of cities in telecommunications.

Abstract

In the field of telecommunications, various operations are driven by different physical quantities. Each has its own patterns in time and space, but all show some clustered structures in their spatial distribution. This reflects a unified rule of human mobility, suggesting the consistency among different telecommunication regionalization objectives. With this in mind, regionalization can be used to identify these patterns and can be applied to improve management efficiency in the context of "autonomous networks". This article introduces the "Traffic Autonomous Zone (TAZ)" concept. This approach aims to create a reasonable unified regionalization scheme by identifying spatial clusters. It is not just a practical way to partition cities based on telecommunications needs, but it also captures self-organization structure of cities in essence. We present examples of this regionalization method using real data. Compared to the popular Louvain community detection method, our approach is on the Pareto frontier, allowing for a balance among various metrics in telecommunications.