A Spherical Probability Distribution Model of the User-Induced Mobile Phone Orientation

TL;DR

This paper introduces a spherical probability distribution model for user-induced mobile phone orientations, using accelerometer data to improve realistic handset usage modeling for better wireless device and network design.

Contribution

It presents a novel spherical von Mises-Fisher distribution-based model for different phone usage types, enhancing the accuracy of handset orientation simulations.

Findings

Model accurately captures user-induced orientation randomness

Finite mixture model improves representation of usage variability

Data-driven approach based on accelerometer measurements

Abstract

This paper presents a statistical modeling approach of the real-life user-induced randomness due to mobile phone orientations for different phone usage types. As well-known, the radiated performance of a wireless device depends on its orientation and position relative to the user. Therefore, realistic handset usage models will lead to more accurate Over-The-Air characterization measurements for antennas and wireless devices in general. We introduce a phone usage classification based on the network access modes, e.g., voice (circuit switched) or nonvoice (packet switched) services, and the use of accessories such as wired or Bluetooth handsets, or a speaker-phone during the network access session. The random phone orientation is then modelled by the spherical von Mises-Fisher distribution for each of the identified phone usage types. A finite mixture model based on the individual probability distribution functions and heuristic weights is also presented. The models are based on data collected from built-in accelerometer measurements. Our approach offers a straightforward modeling of the user-induced random orientation for different phone usage types. The models can be used in the design of better handsets and antenna systems as well as for the design and optimization of wireless networks.