Abstract

This study investigates mobility patterns in microcellular wireless networks, based on measurements from the 802.11-based system that blankets the Carnegie Mellon University campus. We characterize the distribution of dwell time, which is the length of time that a mobile device remains in a cell until the next handoff, and sign-on interarrival time, which is the length of time between successive sign-ons from the same mobile device. Many researchers have assumed that these distributions are exponential, but our results based on empirical analysis show that dwell time and sign-on interarrival time can be accurately described using heavy-tailed arithmetic distributions that have infinite mean and variance. We also show that the number of handoffs per sign-on can be modeled accurately with a heavy-tailed distribution.

Highlights

  • To analyze or simulate micro-cellular wireless networks, as is necessary when determining how much capacity is needed or whether a given protocol is effective, a researcher must make assumptions about mobility patterns

  • We perform an empirical analysis on the data collected from the Wireless Andrew network, the enterprise-wide broadband micro-cellular wireless network that blankets the Carnegie Mellon University (CMU) campus [1,2,3]

  • Sign-on interarrival time is the time between a sign-on and the previous sign-on while dwell time is the time between a handoff and the previous handoff or sign-on

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Summary

INTRODUCTION

To analyze or simulate micro-cellular wireless networks, as is necessary when determining how much capacity is needed or whether a given protocol is effective, a researcher must make assumptions about mobility patterns. Mobile devices in the system we observed generate a sign-on message to establish a connection with the micro-cellular wireless network, and a handoff message when they move from cell to cell. Dwell time is the period that a mobile device maintains a connection with a cell until the handoff. Some researchers have instead sought to derive these distributions using intuitively reasonable assumptions about the speed and direction of device movement, and the geometry of cells. Since few institutions have long experience with vast micro-cellular systems like Wireless Andrew, there has been little measurement-based analysis of mobility of these networks until now.

DESCRIPTION OF WIRELESS ANDREW AND THE DATA
Distribution of Dwell Times
Estimations of the Distribution of Dwell Times
Predictions using the Distribution of Dwell Time
Distribution of Sign-on Interarrival Times
Estimations of Sign-on Interarrival Time Distribution
ANALYSIS OF THE NUMBER OF HANDOFFS PER SIGN-ON
Findings
CONCLUSIONS
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