A neural network-based approach for predicting connectivity in wireless networks
International Journal of Mobile Network Design and Innovation
A kriging approach to predicting coverage in wireless networks
International Journal of Mobile Network Design and Innovation
Estimating signal strengths in the design of an indoor wireless network
IEEE Transactions on Wireless Communications
In-building wideband partition loss measurements at 2.5 and 60 GHz
IEEE Transactions on Wireless Communications
Large-scale wireless LAN design
IEEE Communications Magazine
Rollabout: a wireless design tool
IEEE Communications Magazine
Propagation measurements and models for wireless communications channels
IEEE Communications Magazine
Predicting coverage in wireless local area networks with obstacles using kriging and neural networks
International Journal of Mobile Network Design and Innovation
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This paper introduces ordinary kriging as a new tool to predict network coverage in wireless local area networks. The proposed approach aims to reduce the cost of active site surveys by estimating path loss at points where no measurement data is available using samples taken at other points. To take the effect of obstacles on the covariance among points into account, a distance measure is proposed based on an empirical path loss model. The performance of the proposed approach is tested in a simulated wireless local area network. The results show that ordinary kriging is able to estimate path loss with acceptable error levels.