Neural Network Prediction of Signal Strength for Irregular Indoor Environments

A neural-network based approach for modelling propagation inside complex indoor environments is presented. Selection of the neural network model, initialization, and training and performance evaluation are studied in details. Furthermore, in order to determine optimal access point arrangement the neural network propagation model is merged with the particle swarm optimization method. In the case of simple indoor environments the developed propagation model is equally accurate as the deterministic methods, while in the case of complex environments the proposed method shows superior properties. Finally, the calculated results were tested in direct comparison with the measurements for both simple and complex indoor environments.