Path-Loss Prediction for UHF/VHF Signal Propagation in Edo State: Neural Network Approach


  • Ogbeide K. O. University of Benin
  • Eko Mwenrenren E. J University of Benin



ANN, Hata-model, Pathloss, back-propagation, neurons


The aim of this paper is to present and evaluate artificial neural network model used for path loss prediction of signal propagation in the VHF/UHF spectrum in Edo state.Measurement data obtained from three television broadcasting stations in Edo state, operating at 189.25MHz, 479.25MHz, and 743.25MHz, is used to train and evaluate the artificial neural network. A two layer neural network with one hidden and one output layer is evaluated regarding prediction accuracy and generalization properties. The path loss prediction results obtained by using the artificial neural network model are evaluated against the Hata and Walfisch-Ikegami empirical path loss models .Result analysis shows that the artificial neural network performs well as regards to prediction accuracy and generalization ability. The ANN performed better across all performance measures in comparison to the Hata and Walfisch-Ikegami and Line of Sight models in estimating path loss in vhf/uhf spectrum in Edo state.


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How to Cite

O., O. K., & E. J, E. M. (2016). Path-Loss Prediction for UHF/VHF Signal Propagation in Edo State: Neural Network Approach. APTIKOM Journal on Computer Science and Information Technologies, 1(2), 77–84.