Development of A Propagation Path Loss Prediction Model for Mobile Communication Networks Deployment in Osogbo, Nigeria



Abstract Views
385

Downloads
526

Citations

Share

##plugins.themes.bootstrap3.article.sidebar##

Submitted May 30, 2017
Published Nov 6, 2017
10.24018/ejeng.2017.2.11.370

Abstract viewed = 385 times

Table of Contents

##plugins.themes.bootstrap3.article.main##

Path loss, a major parameter in the analysis and design of the link budget of a telecommunication system, could be explained as the reduction in power density of an electromagnetic wave as it travels through space, over a distance. Path loss prediction models are therefore vital tools in cell planning, cell parameter estimation, frequency assignments and interference evaluation. This paper reports on the development of a path loss prediction model that describes the signal attenuation between transmitting and receiving antennas as a function of the propagation distance and other parameters for Osogbo, Nigeria. The model is extensively useful for conducting feasibility studies for signal prediction, coverage optimization and interference analysis during the initial phase of network planning in the study area and other areas with similar environmental and propagation characteristics.

Keywords: Interference path loss frequency assignment cell planning link budget

Downloads

Download data is not yet available.

References

  1. Abidoye, L. K and Das, D. B, (2014). Artificial Neural Network Modelling of Two Phase Flow in Porous Media. Journal of Hydro Informatics, doi:10.2166/hydro.2014.079.
     Google Scholar
  2. Abhayawardhana V.S., Wassel I.J., Crosby D., Sellers M.P., and Brown M.G., (2005). Comparison of Empirical Propagation Path loss models for fixed wireless access systems. 61th IEEE Technology Conference, Stockholm, pp. 73-77, 2005.
     Google Scholar
  3. Chhaya Dalela., (2012). Propagation Path loss Modeling for Deployed WiMAX Network. International Journal of Emerging Technology and Advanced Engineering. Vol.2, Issue 8, pp. 172-176.
     Google Scholar
  4. Danladi T.A., Lawa A.U., and Aderinola M., (2013).Studies on Effects of Building Internal Pattern on Downlink Mobile Phone Signal Strengths and Power Loss. The International Journal of Engineering and Science (IJES). Vol.2, Issue 12, pp. 24-30.
     Google Scholar
  5. Egli J.J., (1957). Radio Propagation above 40 MC over Irregular Terrain. Proceedings of the IRE. Vol.45, Issue 10, pp. 1383–1391.
     Google Scholar
  6. Goldsmith A., (2005). Wireless Communication. Cambridge University Press, New York.
     Google Scholar
  7. Isabona Joseph., Konyeha. C. C., Chinule. C. Bright., and Isaiah Gregory Peter., (2013). Radio Field Strength Propagation Data and Pathloss calculation Methods in UMTS Network. Advances in Physics Theories and Applications, Vol.21, 2013.
     Google Scholar
  8. Jalel Chebi., Ali K. Lawas., and Rafiigul Islam M.D., (2013). Comparison between Measured and Predicted Path Loss for Mobile Communication in Malaysia. World Applied Sciences Journal (Mathematical Applications in Engineering). Vol.21, pp.123-128.
     Google Scholar
  9. Josip Milanovic, Rimac-Drlje S., and Bejuk K., (2007). Comparison of propagation model accuracy for WiMAX on 3.5GHz. 14th IEEE International conference on electronic circuits and systems, Morocco, pp. 111-114.
     Google Scholar
  10. Mohammad Shahajahan and Abdulla Hes-Shafi A.Q.M., (2009). Analysis of Propagation Models for WiMAX at 3.5GHz. MSc, Blekinge Institute of Technology, Karlskrona, Sweden.
     Google Scholar
  11. Segun I.P., and Olasunkanmi F.O., (2014). Empirical Path Loss Models for GSM Network Deployment in Makurdi, Nigeria. International Refereed Journal of Engineering and Science (IRJES). Vol.3, Issue6, pp.85-94.
     Google Scholar
  12. Sylvain Ranvier, (2004). Path loss models: Physical layer methods in wireless communication systems. SMARAD.
     Google Scholar