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

Authors:
Mahdi Nasereddin;Abdullah Konak;Michael R. Bartolacci
Affiliations:
Penn State Berks, PO Box 7009, Reading, PA 19610-6009, USA.;Penn State Berks, PO Box 7009, Reading, PA 19610-6009, USA.;Penn State Berks, PO Box 7009, Reading, PA 19610-6009, USA
Venue:
International Journal of Mobile Network Design and Innovation
Year:
2005

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Abstract

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.