Performance Evaluation of Standard Path Loss Models for Cellular Network Systems

Performance Evaluation of Standard Path Loss Models for Cellular Network Systems

  IJRES-book-cover  International Journal of Recent Engineering Science (IJRES)          
  
© 2024 by IJRES Journal
Volume-11 Issue-5
Year of Publication : 2024
Authors : Ikechi Risi, Arobo R.C. Amakiri, Jiriwari Amonieah
DOI : 10.14445/23497157/IJRES-V11I5P101

How to Cite?

Ikechi Risi, Arobo R.C. Amakiri, Jiriwari Amonieah, "Performance Evaluation of Standard Path Loss Models for Cellular Network Systems," International Journal of Recent Engineering Science, vol. 11, no. 5, pp. 1-6, 2024. Crossref, https://doi.org/10.14445/23497157/IJRES-V11I5P101

Abstract
The quality of signal propagation for any cellular system is based on the terrain where the system is deployed. Also, the distance of the receiving device from the transmitter, the hindrance obstacles at the path of signal propagation, and the frequency are other factors on which the quality of the signal depends. More so, path loss at various distances and frequencies can be related to the environment and can only be evaluated using path loss models with the capacity to predict only the terrain for which it was designed. The existing standard cost231, Okumura, and Free-space models have often been utilized for propagation attenuation estimation during cellular network planning. In this paper, existing standard Okumura-hata, COST231- hata, and Free space models were analyzed and compared with measurement path loss values to ascertain the level of performance between these models at 2600MHz in Port Harcourt, Nigeria. The signal strengths were measured through the drive-test method within six (6) cell sites. It showed that the range of the measured propagation path loss varies from 120-180dB, whereas COST 231-hata, Okumura-hata, and Free space models attained propagation path loss values which vary between 215- 255dB, 210-252dB, and 140-162dB respectively in the sites. The free-space path loss model estimated the closest path loss data with measured path loss data as compared to the Okumura model, cost231 model, and measured path loss data. As such, the Free-space model outperformed the Okumura and COST231 models within the study area. The standard COST231 model estimated the highest path loss values. The free-space model proved to be the best that can be suitable within the environment and, as such, should be adopted for cellular network system planning and optimization within Port-Harcourt, Nigeria.

Keywords
Performance, Evaluation, Path loss, Models, Cellular network.

Reference
[1] Chukwutem Isaac Abiodun, and Joseph Sunday Ojo, “Determination of Probability Distribution Function for Modelling Path Loss for Wireless Channels Applications Over Micro-Cellular Environments of Ondo State, Southwestern Nigeria,” World Scientific News, vol. 118, no. 12, pp. 74-88, 2019.
[Google Scholar] [Publisher Link]
[2] M. A. Alim et al., “Analysis of Large-Scale Propagation Models for Mobile Communications in Urban Area,” International Journal of Computer Science and Information Security, vol. 7, no. 1, pp. 135-139, 2010.
[CrossRef] [Google Scholar] [Publisher Link]
[3] Julia Ofure Eichie et al., “Comparative Analysis of Basic Models and Artificial Neural Network Based Model for Path Loss Prediction,” Progress in Electromagnetics Research, vol. 61, no. 9, pp. 133-146, 2017.
[CrossRef] [Google Scholar] [Publisher Link]
[4] Joseph Isabona, and Divine O. Ojuh “Application of Levenberg-Marguardt Algorithm for Prime Radio Propagation Wave Attenuation Modelling in Typical Urban, Suburban and Rural Terrains,” International Journal of Intelligent Systems and Applications, vol. 13, no. 3, pp. 35-42, 2021.
[CrossRef] [Google Scholar] [Publisher Link]
[5] Manju Kumari et al., “Comparative Study of Path Loss Models in Different Environments,” International Journal of Engineering Science, vol. 3, no. 4, pp. 2945-2949, 2011.
[Google Scholar]
[6] Imhomoh E. Linus "Optimization of Cost 231-Hata Model for Propagation Path Loss Measurements in Lagos,” International Journal of Engineering Science Invention, vol. 10, no. 3, pp. 14-23, 2021.
[Google Scholar] [Publisher Link]
[7] Michael S. Mollel, and Michael Kisangiri, “Comparison of Empirical Propagation Path Loss Models for Mobile Communication,” International Institute for Science, Technology and Education, vol. 5, no. 9, pp. 1-11, 2014.
[Google Scholar] [Publisher Link]
[8] Raphaël Nlend, and Emmanuel Tonye, “Planning and Simulation of LTE Radio Network: Case of the City of Yaoundé,” Journal of Electronics and Communication Engineering, vol. 14, no. 2, pp. 19-29, 2019.
[Google Scholar] [Publisher Link]
[9] E.O. Ogundapo, L.I. Oborkhale, and S.B. Ogunleye, “Comparative Study of Path Loss Models for Wireless Mobile Network Planning," International Journal of Engineering and Mathematical Intelligence, vol. 2, no. 1, pp. 19-25, 2011.
[Google Scholar]
[10] N. Pooja, R. Anitha, and C.S. Hanchinal, “Optimized Path Loss Model for the Effects of Environmental Factors on Mobile Signal Strength,” International Research Journal of Engineering and Technology, vol. 5, no. 4, pp. 4513-4516, 2018.
[Google Scholar] [Publisher Link]
[11] Theodore S. Rappaport, Wireless Communications: Principles and Practice, 2nded., Cambridge University Press, pp. 1-732, 2002.
[Google Scholar] [Publisher Link]
[12] Wali Samuel, Njumoke N. Odu, and Samuel Godwin Ajumo, “Performance Evaluation of Hata-Davidson Pathloss Model Tuning Approaches for A Suburban Area,” American Journal of Software Engineering and Applications, vol. 6, no. 3, pp. 93-98, 2017.
[CrossRef] [Google Scholar] [Publisher Link]
[13] Purnima K. Sharma, and R.K.Singh, “Comparative Analysis of Propagation Path Loss Models with Field Measured Data,” International Journal of Engineering Science and Technology, vol. 2, no. 6, pp. 2008-2013, 2010.
[Google Scholar] [Publisher Link]
[14] Nathaniel S. Tarkaa, Victor A. Agbo, and Samuel O. Oglegba, “Radio Propagation Path-Loss Analysis for An Operative Gsm Network,” The International Journal of Engineering and Science, vol. 6, no. 9, pp. 53-67, 2017.
[Google Scholar] [Publisher Link]
[15] Aymen Zreikat, and Milan Dordevic, “Performance Analysis of Path Loss Prediction Models in Wireless Mobile Performance Analysis of Path Loss Prediction Models in Wireless Mobile Networks in Different Propagation Environments," In Proceedings of the 3rd World Congress on Electrical Engineering, Computer Systems and Science, vol. 103, no. 6, pp. 1-11, 2017.
[CrossRef] [Google Scholar] [Publisher Link]
[16] Mukesh Kumar, Vijay Kumar, and Suchika Malik, “Performance and Analysis of Propagation Models for Predicting RSS for Efficient Handoff,” International Journal of Advanced Scientific and Technical Research, vol. 1, no. 2, pp. 61-70, 2012.
[Google Scholar] [Publisher Link]
[17] Haider Kadhim Hoomod, Intisar Al-Mejibli, and Abbas Issa Jabboory, “Analyzing Study of Path Loss Propagation Models in Wireless Communications at 0.8 GHz,” Journal of Physics: Conference Series, vol. 1003, no. 10, pp. 1-8, 2018.
[CrossRef] [Google Scholar] [Publisher Link]
[18] Altayeva, Aigerim Bakatkaliyevna, and Cho, Young Im, “Comparison of Radio Wave Propagation Models for Mobile Networks,” International Journal of Fuzzy Logic and Intelligent Systems, vol. 15, no. 3, pp. 192-199, 2015.
[CrossRef] [Google Scholar] [Publisher Link]