Simple and Effective Electromagnetic Wave Propagation Loss Model in GSM Band for Smart Campus Applications

International Journal of Electrical and Electronics Engineering
© 2024 by SSRG - IJEEE Journal
Volume 11 Issue 11
Year of Publication : 2024
Authors : Oluwole John Famoriji, Thokozani Shongwe
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How to Cite?

Oluwole John Famoriji, Thokozani Shongwe, "Simple and Effective Electromagnetic Wave Propagation Loss Model in GSM Band for Smart Campus Applications," SSRG International Journal of Electrical and Electronics Engineering, vol. 11,  no. 11, pp. 306-311, 2024. Crossref, https://doi.org/10.14445/23488379/IJEEE-V11I11P129

Abstract:

A simple and cost-effective empirical path loss model is crucial for mobile communication systems' link planning, optimization, and budgeting. Although numerous path loss models have been developed in the literature, many are complex and difficult to apply, highlighting the need for a more straightforward and economical solution. This paper presents the mathematical characterization of a Global System for Mobile communications (GSM) path loss dataset obtained from Covenant University in Ota, Nigeria. The developed empirical propagation model employs a step-wise curve fitting to the path loss data. The results show that the mathematical model agrees quite well with the measured data. The mathematical expression is also straightforward, easy to use, and suitable for GSM signal loss calculations, requiring minimal input parameters. In conclusion, the analysis results are promising and suggest that the proposed model is well suited for practical deployment in smart campus interconnectivity designs, optimization, and similar applications.

Keywords:

Electromagnetic wave propagation, Empirical model, GSM, Curve fitting, Propagation loss model.

References:

[1] Segun I. Popoola, Aderemi A. Atayero, and Nasir Faruk, “Received Signal Strength and Local Terrain Profile Data for Radio Network Planning and Optimization at GSM Frequency Bands,” Data in Brief, vol. 16, pp. 972-981, 2018.
[CrossRef] [Google Scholar] [Publisher Link]
[2] D.P. Wright, and E.A. Ball, “IoT Focused VHF and UHF Propagation Study and Comparisons,” IET Microwaves, Antennas & Propagation, vol. 15, no. 8, pp. 871-884, 2021.
[CrossRef] [Google Scholar] [Publisher Link]
[3] Tom Viering, and Marco Loog, “The Shape of Learning Curves: A Review,” IEEE Transactions on Pattern Analysis and Machine Intelligence, vol. 45, no. 6, pp. 7799-7819, 2023.
[CrossRef] [Google Scholar] [Publisher Link]
[4] Igor Fomenko, Mark Durst, and David Balaban, “Robust Regression for High Throughput Drug Screening,” Computer Methods and Programs in Biomedicine, vol. 82, no. 1, pp. 31-37, 2006.
[CrossRef] [Google Scholar] [Publisher Link]
[5] Theodore Rappaport, Wireless Communications: Principles and Practice, vol. 2. Upper Saddle River, NJ, USA: Prentice-Hall, 1996.
[Google Scholar] [Publisher Link]
[6] N. Faruk, A.A. Ayeni, and Y.A. Adediran, “Characterization of Propagation Path Loss at VHF/UHF Bands for Ilorin City, Nigeria,” Nigerian Journal of Technology, vol. 32, no. 2, pp. 253-265, 2013.
[CrossRef] [Google Scholar] [Publisher Link]
[7] Eran Greenberg, and Edmund Klodzh, “Comparison of Deterministic, Empirical and Physical Propagation Models in Urban Environments,” 2015 IEEE International Conference on Microwaves, Communications, Antennas and Electronic Systems (COMCAS), Tel Aviv, Israel, pp. 1-5, 2015.
[CrossRef] [Google Scholar] [Publisher Link]
[8] L.B. Felsen, and L. Sevgi, “Adiabatic and Intrinsic Modes for Wave Propagation in Guiding Environments with Longitudinal and Transverse Variation: Formulation and Canonical Test,” IEEE Transactions on Antennas and Propagation, vol. 39, no. 8, pp. 1130-1136, 1991.
[CrossRef] [Google Scholar] [Publisher Link]
[9] L. Sevgi, F. Akleman, and L.B. Felsen, “Groundwave Propagation Modeling: Problem-Matched Analytical Formulations and Direct Numerical Techniques,” IEEE Antennas and Propagation Magazine, vol. 44, no. 1, pp. 55-75, 2002.
[CrossRef] [Google Scholar] [Publisher Link]
[10] Levent Sevgi, “Groundwave Modeling and Simulation Strategies and Path Loss Prediction Virtual Tools,” IEEE Transactions on Antennas and Propagation, vol. 55, no. 6, pp. 1591-1598, 2007.
[CrossRef] [Google Scholar] [Publisher Link]
[11] M. Hata, “Empirical Formula for Propagation Loss in Land Mobile Radio Services,” IEEE Transactions on Vehicular Technology, vol. 29, no. 3, pp. 317-325, 1980.
[CrossRef] [Google Scholar] [Publisher Link]
[12] V. Erceg et al., “An Empirically Based Path Loss Model for Wireless Channels in Suburban Environments,” IEEE Journal on Selected Areas in Communications, vol. 17, no. 7, pp. 1205-1211, 1999.
[CrossRef] [Google Scholar] [Publisher Link]
[13] Nasir Faruk et al., “Clutter and Terrain Effects on Path Loss in the VHF/UHF Bands,” IET Microwaves, Antennas & Propagation, vol. 12, no. 1, pp. 69-76, 2018.
[CrossRef] [Google Scholar] [Publisher Link]
[14] Johannes Hejselbæk et al., “Empirical Study of Near Ground Propagation in Forest Terrain for Internet-of-Things Type Device-to-Device Communication,” IEEE Access, vol. 6, pp. 54052-54063, 2018.
[CrossRef] [Google Scholar] [Publisher Link]
[15] Hamnah Munir et al., “Resource Optimization in Multi-Tier HetNets Exploiting Multi-Slope Path Loss Model,” IEEE Access, vol. 5, pp. 8714-8726, 2017.
[CrossRef] [Google Scholar] [Publisher Link]