Analysis of wireless networks using Hawkes processes

Michael Moore1, Mark Davenport

  • 1Georgia Institute of Technology

Details

Category

Technical Session: Poster

Theme

Signal Processing for Wireless Communications

Sessions

15:15 - 16:45 | Wed 6 Jul | Pentland A | R11

Localization and tracking in Wireless/UWB networks

Abstract

In this paper we consider the problem of characterizing and analyzing a wireless network from limited passive observations of network activity. In particular, we will assume that the only information that we can acquire is knowledge of when each particular transmitter in the network initiates any given transmission. From this data, we wish to be able to solve problems such as learning the network topology, detecting changes to the existing topology, and extracting higher-level summaries of information flow in the network. We show how one can use a multidimensional autoregressive point process known as a Hawkes process to model the observed data and approach these problems.

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