Complete Abstract:

The efficient deployment and robust operation of many sensor network applications depend on deploying relays to ensure wireless coverage. Radio mapping aims to predict network coverage based on a small number of link measurements from sampled locations. Radio mapping is particularly challenging in complex indoor environments where walls significantly affect radio signal propagation. This paper makes the following key contributions to indoor radio mapping. First, our empirical study in an office building identifies a wall-classification model as the most effective model for indoor environments due to its balance between model complexity and accuracy. Second, we propose a practical algorithm to predict the Reception Signal Strength (RSS) of links in an indoor environment based on a small number of measurements at sampled locations. A key novelty of our algorithm lies in its capability to automatically classify walls into a small number of classes with different degrees of signal attenuation. Finally, we present a practical Radio Mapping Tool that can predict the coverage areas of relays based on a small number of link quality measurements in... Read complete abstract on page 2