| 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. |
