Understanding Mobile Traffic Patterns of Large Scale Cellular Towers in Urban Environment

TL;DR

This paper presents a novel model that combines temporal, spatial, and spectral data to extract and analyze mobile traffic patterns across thousands of cellular towers in a city, revealing fundamental patterns linked to urban geography and human activity.

Contribution

The paper introduces a powerful multi-dimensional model for traffic pattern extraction and provides empirical insights into urban cellular traffic behaviors.

Findings

Only five basic traffic patterns among 9,600 towers.

Traffic patterns correspond to urban geographical areas.

Traffic spectra can be reconstructed from four primary components.

Abstract

Understanding mobile traffic patterns of large scale cellular towers in urban environment is extremely valuable for Internet service providers, mobile users, and government managers of modern metropolis. This paper aims at extracting and modeling the traffic patterns of large scale towers deployed in a metropolitan city. To achieve this goal, we need to address several challenges, including lack of appropriate tools for processing large scale traffic measurement data, unknown traffic patterns, as well as handling complicated factors of urban ecology and human behaviors that affect traffic patterns. Our core contribution is a powerful model which combines three dimensional information (time, locations of towers, and traffic frequency spectrum) to extract and model the traffic patterns of thousands of cellular towers. Our empirical analysis reveals the following important observations. First, only five basic time-domain traffic patterns exist among the 9,600 cellular towers. Second, each of the extracted traffic pattern maps to one type of geographical locations related to urban ecology, including residential area, business district, transport, entertainment, and comprehensive area. Third, our frequency-domain traffic spectrum analysis suggests that the traffic of any tower among the 9,600 can be constructed using a linear combination of four primary components corresponding to human activity behaviors. We believe that the proposed traffic patterns extraction and modeling methodology, combined with the empirical analysis on the mobile traffic, pave the way toward a deep understanding of the traffic patterns of large scale cellular towers in modern metropolis.