A neural network-based approach for predicting connectivity in wireless networks. (5th October 2005)

• Record Type: Journal Article
• Authors: Nasereddin, Mahdi; Konak, Abdullah; Bartolacci, Michael R.
• Is Part Of: International journal of mobile network design and innovation. Volume 1:Number 1(2005)
• Page Start: 18
• Page End: 23
• Publication Date: 2005-10-05
• Subjects: wireless networks -- connectivity prediction -- neural networks -- artificial intelligence -- mobile networks -- DSS -- decision support systems -- connectivity maps -- mobile communications -- connectivity modelling -- network design; Mobile communication systems -- Periodicals; Wireless communication systems -- Design and construction -- Periodicals; 384.535
• Languages: English
• ISSNs: 1744-2869

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.