This thesis focuses on evaluating an effective type of Position Location (PL) system for cellular phones.
Due to the inadequacy of existing Large-Scale-Fading (LSF) models, a new model is developed. This new LSF model introduces random changes called Splashes-Of-Change (SOC), in the root-mean-square delay spread of channel impulse responses over small regions of a cell. The new LSF model is called the SOC LSF Model (SOCLSFM) and includes propagation delay, path loss, exponentially distributed power delay profiles, and log-normal shadowing.
Strength-Of-Arrival (SOA) PL simulations were used to evaluate the SOCLSFM. SOA PL alone is often not sufficiently accurate because of the multipath. A multilayer Levenberg-Marquardt-trained feed-forward Neural Network (NN) was introduced and successfully improved accuracy compared to SOA PL. Impulse responses from the mobile to the base stations, as well as extracted features of impulse responses, are the inputs to the NN.PDF file, 1.824 MBytes