Design and Simulation of a Proposed Location Management Model for Cellular Networks

In this model, a 4-layerd (3 hidden layers and 1 output layer) are used Artificial Neural Network (ANN) with three inputs (BS1-BS3) and two outputs (x and y). The three inputs of the ANN represent the signals strength of three different Base Stations (BS1-BS3) which are received by the Mobile Station (MS) and used to determine the location of the MS as a point with 2 coordinates x and y which represent the 2-outputs of the ANN then the position of MS will be send to the MSC to inform it about the exact location of the MS within the specified area. The three hidden layers consist of 3-nodes or neurons, 4 and 8-nodes, respectively and by applying a powerful learning algorithm called the Back Propagation Learning algorithm (BPL) to find the set of network weights that minimizes the network's cumulative error. The mobile unit regularly informs the MSC about its location result in avoiding the paging problem.