Determination of Pathloss Exponent 4G LTE Signal in Urban and Rural Environment of Southern Nigeria (Asaba in Delta State and Onitsha in Anambra State)

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Published: 2024-02-02

Page: 20-35


G. O. Chimezie

Department of Industrial Physics, Chukwuemeka Odumegwu Ojukwu University, Anambra State, Nigeria.

C. C. Onuchukwu *

Department of Industrial Physics, Chukwuemeka Odumegwu Ojukwu University, Anambra State, Nigeria.

N. A. Okereke

Department of Industrial Physics, Chukwuemeka Odumegwu Ojukwu University, Anambra State, Nigeria.

*Author to whom correspondence should be addressed.


Abstract

We investigated the radio frequency channel behavior based on extensive measurements of signal strength and other propagation parameters up to 1200 m from the base stations, adopting single sector verification technique in wet and dry season in urban and rural environments of Delta and Anambra States in Nigeria. The measurements were carried out at 800 MHz bands using Sony Ericson Test Mobile System (TEMS) phones and global positioning system connected to a laptop equipped with TEMS software and cell refs of the base stations in the studied areas. The estimated pathloss values were compared with four commonly used propagation models namely: Erceg, Cost-231, Ericson, and Standard University Interim (SUI). SUI model presented a better agreement with the measured pathloss based on root mean square error (RMSE) metrics analysis in all the considered environments in both seasons. Modification of the SUI model was carried out by including the pathloss exponent which performed better in predicting the pathloss compared with commonly used SUI propagation models. Climatological parameters such as pressure, temperature and relative humidity at ground surface over all the monitored environments were obtained between 2022 and 2023. These data were used to compute the refractivity gradient, effective earth radius (k-factor), and geoclimatic factor for the studied area. Results show that using the standard value of 1.33 for k-factor in the investigated environments, the required height of antenna for line-of-sight communication link setup may not be achieved. This may result in overestimation or underestimation of the required link budget needed for urban and rural environments in southern Nigeria environment.

Keywords: Pathloss, test mobile system, k-factor, geoclimatic factor


How to Cite

Chimezie , G. O., C. C. Onuchukwu, and N. A. Okereke. 2024. “Determination of Pathloss Exponent 4G LTE Signal in Urban and Rural Environment of Southern Nigeria (Asaba in Delta State and Onitsha in Anambra State)”. Asian Basic and Applied Research Journal 6 (1):20-35. https://jofresearch.com/index.php/ABAARJ/article/view/136.

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References

Sharma PK, Dinesh S, Singh RK. Development of propagation model by considering different climatic conditions. Magnt Research Report. 2014;2(6):389-401.

Teletopax. Requirement for interference and carrier to interference ratio in GSM. Telecom Techniques Guide; 2012 December 19.

Nigeria Bureau of Statistics Bulletin; 2006.

Onitsha Population. World Population Review; 2023. Available:https://worldpopulationreview.com/world-cities/onitsha-population

Perez FF, Marino PE. Modelling the Wireless Propagation Channel a simulation approach with matlab. A John Willey and Sons Publication Ltd; 2008.

Akinyemi P. Optimization of Path Loss Model for Macro-Cellular Network; 2016.

Abiodun CI, Azi SO, Ojo JS, Akinyemi P. Assessment of pathloss prediction models for wireless propagation channels at L-band frequency over different micro-cellular environments of Ekiti state, Southwestern Nigeria. World Academy of Science, Engineering and Technology. International Journal of Electronics and Communication Engineering. 2017;11(10): 1103-1109.

James D, Gadze KA, Agyekum SJ, Nuagah EA. Improved propagation models for lte path loss prediction in urban & suburban

Ghana. International Journal of Wireless & Mobile Networks (IJWMN). 2019;11(6).

Mason PS. Atmospheric effects on radio frequency wave propagation in a humid near-surface environment. Nava Postgraduate School Monterey CA;2010.

Zubar M. Atmospheric influences on satellite communications. Przglad Elektrotechnczny. 2011;87(5):261-264.

Application in Selected State in Nigeria. Ph.D thesis, Department of Physics, University of Benin, Benin City Edo State Nigeria. 2011;Chapter 3:97-100.

Ononiwu G, Simon O, Constance K. Determination of the dominant fading and the effective fading for the rain zones. European Journal of Mathematics and Computer Science. 2015;22.

Ojo OL, Ajewole M, Adediji A, Ojo JS. Estimation of clear-air fades depth due to Radio Climatological parameters for microwave link applications in Akure Nigeria. International Journal of Engineering. 2012;7(3):1-8.

International Telecommunications Union. The radio refractive index, its formular and refractive data. International Telecommunications Union, Recommendation of ITU-4539; 2003.

International Telecommunications Union. The radio refractive index, its formular and refractive data. International Telecommunications Union, Geneva, Recommendation of ITU-453-8; 2000.

Agbo GA, Okoro ON, Amechi AO. Atmospheric refractivity over Abuja. Nigeria International Research Journal of Pure and Applied Physics. 2013;37-45.

Abu-Almal A, Al-Ansari K. Calculation of effective earth radius and point refractivity gradient in UAE. International Journal of Antenna and Propagation; 2010.

International Telecommunications Union. Propagation data and prediction methods required for the design of terrestrial LOS systems. International Telecommunication Union Recommendation ITU- P.530-14; 2012.

Nasir F, Adeseko AA, Yunusa AA. On the study of empirical pathloss models for accurate prediction of TV signal for secondary users. Progress in Electromagnetic Research B. 2013;49:155-176.

Erceg V, Tjandra SY, Parkoff SR, Gupta A, Kulie B, Julius AA, Bianchi R. An empirically based path loss model for wireless channels in suburban environment. IEEE Journal in Selected Areas in Communications. 1999;17(7): 1205-1210.

Abiodun IC, Idogho J. Variations of GSM path loss exponent with Propagation distance at L-band frequencies in different microcellular environment of southwestern Nigeria. African Journal of Electrical and Electronics Research. 2021; 4(1):1-9.

Fanimokun A, Frolic J. Effects of natural propagation environments on wireless sensor network coverage area. Proceedings of the 30th Southern Symposium on System Theory. 2003:6-20.

Turkka J, Ranfor M. Path loss measurements for a non-line-of-sight mobile-mobile environment. Proceedings of the International Conference on Intelligent Transport System Telecommunications. Phuket, Thailand, October. 2008;22-24.

Bruce LC. Prediction of seasonal trends in cellular dropped call probability. IEEE Proceedings of International Conference on Electro/Information Technology. 2006; 613-618.

Bultitude RJC, Bedal GK. Propagation characteristics on microcellular urban mobile radio channel at 910 MHz. IEEE Journal on Selected Areas in Communications. 1989;31-39.

Jalel C, Ali KL, Rafiqul MD. Comparison between measured and predicted pathloss for mobile communication in malaysia. World Applied Science Journal 21 (Mathematical Application in Engineering). 2013;123-128.

Joshi GG. Near ground channel measurement over line of sight and forested paths. IEEE Proceedings on Microwaves, Antenna and Propagation. 2005;589-596.

Julio CC. Analysis and optimization of empirical path loss models and shadowing effects for Tampa Bay area in the 2.6 GHz band. M.Sc. Thesis, Department of Electrical Engineering, University of South Florida. 2008;Chapter 3 and 4:12-27.

Kanagalu RM. Coverage estimation for mobile cellular networks from signal strength measurement. Ph.D Dissertation in Electrical Engineering, University of Texas Dalas; 1999.