Deterministic Wireless Propagation Model Assisted Indoor Positioning

In this paper, we explore the application of deterministic wireless propagation models for the generation of radio maps used in fingerprinting-based indoor positioning. Four positioning algorithms, namely, the k-nearest neighbors (kNN), weighted k-nearest neighbors (WkNN), maximum a posterior (MAP), and minimum mean squared error (MMSE), are investigated. Their performance is examined with respect to the density of radio maps as well as the number and location of wireless access points.