The Impact of Propagation Models on TV White Space Estimation in Southern Nigeria

International Journal of Electronics and Communication Engineering

© 2020 by SSRG - IJECE Journal

Volume 7 Issue 1

Year of Publication : 2020

Authors : Kebiru Abu, Stephen U. Ufoaroh, Obomeghie Mariam A

10.14445/23488549/IJECE-V7I1P102

How to Cite?

Kebiru Abu, Stephen U. Ufoaroh, Obomeghie Mariam A, "The Impact of Propagation Models on TV White Space Estimation in Southern Nigeria," SSRG International Journal of Electronics and Communication Engineering, vol. 7,  no. 1, pp. 5-14, 2020. Crossref, https://doi.org/10.14445/23488549/IJECE-V7I1P102

Abstract:

Geo-location databases are ideal for detecting TV white spaces by white space devices (WSD) in the United States (US). The approach protects spectrum incumbent (primary users) and secondary users from interference adequately by keeping a record of the TV transmitters’ information and relying on propagation models to determine the TV transmitters’ protection area. This paper presents statistical path loss models derived from experimental data collected in Benin city, Edo State in Southern Nigeria from Edo Broadcasting Service (EBS), operating at 745.25MHz. The measurements’ results were used to develop a path loss model for the urban areas of Edo state. The measurement results showed that the Path loss increases by 23.1dB per decade in the urban areas. Variations in path loss between the measured and the predicted values from the Okumura-Hata model were calculated by finding the mean square errors (MSE) to be 1.31dB for the urban terrain. These variations (errors) were used to modify the Okumura-Hata models for the terrain. Comparing the modified Hata model with the measured values showed a better result. The developed statistical Path loss models or the modified Hata models can be used in the urban areas of Southern Nigeria.

Keywords:

Interference, TV whitespace, Radio Spectrum, Radio Propagation, Southern Nigeria.

References:

[1] Hope M, Antoine B, Marco Z., Guy .L. Z (2015). “On the Impact of Propagation Models on TV White Space Measurements in Africa”.International Conference on Emerging Trends in Networks and Computer Communications (ETNCC)pp. 148–154. DOI: 10.1109/etncc.2015.7184825
[2] Alemu, T. B., (2012), “Spectrum Availability Assessment Tool for TV White Space”, MSc. Thesis Master of Science in Technology, School of Electrical Engineering, Aalto University available online:
http://lib.tkk.fi/Dipl/2012/urn100704.pdf Accessed June 5, 2013.
[3] Ofcom, (November 2009). “Implementing geo-location", http://stakeholders.ofcom.org.uk/binaries/consultations/geolocation/summary/geolocation.pdf retrieved April 2, 2018.
[4] Saeed A., Ibrahim M., Youssef M., and HarrasK.A., (2013) “Towards dynamic real-time geo-location databases for TV white spaces.”arXiv preprintarXiv:1303.3962.
[5] Oluwole, F. J., and Olajide, O. Y. (2013). “Radiofrequency propagation mechanisms and empirical models for hilly areas.” International. Journal of Elect. Comput. Eng. (3): pp. 372–376.
[6] Wang, H., Noh, G., Kim, D., Kim, S., and Hong, D. (2010). “Advanced sensing techniques of energy detection in cognitive radios.” Communications and networks, Journal of 12, no. 1. pp. 19-29.
[7] Chebil J, Lawas A.K, and Islam M. D, (2013)."Comparison between measured and predicted path loss for mobile communication in Malaysia.” World Applied Sciences Journal 21: pp. 123-128.
[8] Ubom, E.A., Idigo, V. E., Azubogu, A.C.O., Ohaneme, C.O., and Alumona, T. L. (June, 2015). “Path loss Characterization of Wireless Propagation for South-South Region of Nigeria”. International Journal of Computer Theory and Engineering, Vol. 3, No. 3, pp 360-364.
[9] Nwalozie G. C, Ufoaroh S. U, Ezeagwu C. O, Ejiofor A. C, (February 2014), “Path loss prediction for GSM mobile networks for the urban region of Aba, South-East Nigeria” International Journal of Computer Science and Mobile Computing, Vol.3 Issue.2, pp. 267-281.
[10] Smith, M.S. et al.,(April 2000) “A new methodology for deriving path loss models from cellular drive test data, Proc. AP 2000, conference, Davos, Sivitzerlend.
[11] Obot A, Simeon .O and Afolayan (2011). “Comparative analysis of pathloss prediction models for the urban macrocellular environment” Nigerian Journal of Technology. Vol. 30, No.3. pp. 50-59.
[12] Katulski, R. J. and Kiedrowski, A. (2005). Empirical Formulas for determination of the Propagation Loss in urban radio access links, Proceedings of IEEE 62nd Vehicular Technology Conference, Dallas, USA, pp. 1742-1746.
[13] Saurav Jain , M.V. Raghunadh. "Spectrum Sensing Based on Cyclostationary Detector using USRP", International Journal of Engineering Trends and Technology (IJETT), V11(4),188-191 May 2014. ISSN:2231-5381.