Mobility

Estimating Distances Via Connectivity in Wireless Sensor Networks

Download Now Free registration required

Executive Summary

Distance estimation is vital for localization and many other applications in wireless sensor networks. In this paper, the authors develop a method that employs a Maximum-Likelihood Estimator (MLE) to estimate distances between a pair of neighboring nodes in static wireless sensor networks using their local connectivity information, namely the numbers of their common and non-common one-hop neighbors. They present the distance estimation method under a generic channel model, including the unit disk (communication) model and the more realistic log-normal (shadowing) model as special cases.

  • Format: PDF
  • Size: 364.73 KB