Int. J. of Wireless and Mobile Computing   »   2014 Vol.7, No.6

 

 

Title: Improved path-loss model for predicting TV coverage for secondary access

 

Authors: Nasir Faruk; Adeseko A. Ayeni; Yinusa A. Adediran; Nazmat T. Surajudeen-Bakinde

 

Addresses:
Department of Telecommunication Science, University of Ilorin, Ilorin, Kwara State, Nigeria
Department of Telecommunication Science, University of Ilorin, Ilorin, Kwara State, Nigeria
Department of Electrical and Electronics Engineering, University of Ilorin, Ilorin, Kwara State, Nigeria
Department of Electrical and Electronics Engineering, University of Ilorin, Ilorin, Kwara State, Nigeria

 

Abstract: Path-loss model is essential for proper planning of emerging technologies in the broadcast frequency band. Characterisation of the radio channel is paramount for accurate prediction of TV coverage, and achievement of peaceful coexistence between the TV (primary users) and other new infrastructures (secondary users). In this paper, field strength measurements are conducted along six routes that spanned through urban, suburban and rural areas of Kwara State, Nigeria. The measurement results are compared with path-loss prediction of eight widely used empirical models. Least squares and linear iterative methods are employed to optimise Hata-Davidson's model, as it showed best fit compared with other models. The predictions of the tuned model are compared with other models in terms of relative error, mean error, skewness, root mean square errors and normalised error probability density function. Results of the simulations indicate that the optimised model gives better values for the metrics considered.

 

Keywords: path loss prediction; Hata's model; Davidson's model; least squares method; linear iterative method; primary users; secondary users; TV white space; digital TV; digital television; TV coverage; Nigeria; simulation; optimisation.

 

DOI: 10.1504/IJWMC.2014.065607

 

Int. J. of Wireless and Mobile Computing, 2014 Vol.7, No.6, pp.565 - 576

 

Submission date: 11 Nov 2013
Date of acceptance: 23 Jul 2014
Available online: 30 Oct 2014

 

 

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