A neural network-based approach for predicting connectivity in wireless networks

This paper proposes a Connectivity Decision Support System based on connectivity maps generated by a neural network approach. The proposed approach creates a coverage map based on the signal strengths from active wireless users. These data are used to train a neural network to predict the signal strengths or coverage for locations for which no active user is reporting. In other words, a neural network fills in gaps in a coverage map for a given network connection point.