Empirical Valuation of Multi-Parameters and RMSE-Based Tuning Approaches for the Basic and Extended Stanford University Interim (SUI) Propagation Models

Constance Kalu, Bliss Utibe-Abasi Stephen, Mfonobong Charles Uko


In this paper, the prediction performance evaluation of Stanford University Interim (SUI) Model and the extended SUI model are presented. More importantly, the effectiveness of two model tuning approaches, namely, RMSE-based tuning and multi-parameter tuning are assessed based on empirical pathloss data obtained for a suburban area in Uyo, Akwa Ibom state.  Although the RMSE tuning is quite simple, the results showed that in some cases it does not minimize the prediction error to an acceptable level (6dB to 7dB) for practical applications. However, in the two models, the multi-parameter tuning effectively minimized the prediction error to an acceptable level with mean prediction error of about 0.00001 dB, RMSE that are less than 2.45 dB and prediction accuracies above 98.2%. On the other hand, the RMSE-tuned models have mean prediction error of above ± 1.5 dB, RMSE that above 8.8 dB and prediction accuracies less than 94.3%. In all, the SUI model performed better than the extended SUI.


Pathloss; Model Tuning; Empirical Pathloss Models; Stanford University Interim (SUI) Model; Multi-parameter tuning; RMSE-based Tuning

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Lanbo, L., Shengli, Z., & Jun‐Hong, C. (2008). Prospects and problems of wireless communication for underwater sensor networks. Wireless Communications and Mobile Computing, 8(8), 977-994.

Andrusenko, J., Burbank, J., & Ward, J. (2009). Modeling and simulation for RF propagation. The Jonhs Hopkins University Design & Developers Fourm IEEE Globecom.

Burbank, J. L., Kasch, W., & Ward, J. (2011). An introduction to network modeling and simulation for the practicing engineer (Vol. 5). John Wiley & Sons.

Anthony, O. N., & Okonkwo Obikwelu, R. (2014). Characterization of Signal Attenuation using Pathloss Exponent in South-South Nigeria. International Journal of Emerging Trends & Technology in Computer Science (IJETTCS), 100-104.

Wang, J., & Wang, Q. (2012). Body area communications: channel modeling, communication systems, and EMC. John Wiley & Sons.

Popoola, S. I., & Oseni, O. F. (2014). Empirical Path Loss Models for GSM Network Deployment in Makurdi, Nigeria. International Refereed Journal of Engineering and Science (IRJES), 3(6), 85-94.

Mawjoud, S. A. (2013). Path Loss Propagation Model Prediction for GSM Network Planning. International Journal of Computer Applications, 84(7).

Francis, A. K., & Ezekiel‘Dunsin, O. (2013). Path Loss Prediction Model For UHF Radiowaves Propagation in Akure Metropolis. International Journal of Engineering (IJE), 8(3), 30.

Ogbulezie, J. C., Onuu, M. U., Ushie, J. O., & Usibe, B. E. (2013). Propagation models for GSM 900 and 1800 MHz for Port Harcourt and Enugu, Nigeria. Network and Communication Technologies, 2(2), 1.

Akinwole, B. O. H., & Biebuma, J. J. (2013). Comparative Analysis Of Empirical Path Loss Model For Cellular Transmission In Rivers State. Jurnal Ilmiah Electrical/Electronic Engineering, 2, 24-31.

Roslee, M. B., & Kwan, K. F. (2010). Optimization of Hata propagation prediction model in suburban area in Malaysia. Progress In Electromagnetics Research C, 13, 91-106.

Thomas, T., & Vivek, M. V. (2015). Path loss Determination Using Hata Model and Effect of Path loss in OFDM. International Journal of Advanced Research in Biology, Ecology, Science and Technology(IJARBEST)Vol. 1, Issue 8.

Faruk, N., Ayeni, A., & Adediran, Y. A. (2013). On the study of empirical path loss models for accurate prediction of TV signal for secondary users. Progress In Electromagnetics Research B, 49, 155-176.

Alotaibi, F. D., & Ali, A. A. (2008). Tuning of Lee path loss model based on recent RF measurements in 400 MHz conducted in Riyadh city, Saudi Arabia. Arabian Journal for Science and Engineering, 33(1), 145.

Bhuvaneshwari, A., Hemalatha, R., & Satyasavithri, T. (2013). Statistical tuning of the best suited prediction model for measurements made in Hyderabad city of Southern India. Proceedings of the world congress on engineering and computer science (Vol. 2).

Joseph, I., & Konyeha, C. C. (2013). Urban Area Path loss Propagation Prediction and Optimisation Using Hata Model at 800MHz. IOSR Journal of Applied Physics (IOSR-JAP), 3, 8-18.

Nadir, Z., Elfadhil, N., & Touati, F. (2008). Pathloss determination using Okumura-Hata model and spline interpolation for missing data for Oman. In Proceedings of the world congress on Engineering (Vol. 1).

Arulampalam, M. S., Maskell, S., Gordon, N., & Clapp, T. (2002). A tutorial on particle filters for online nonlinear/non-Gaussian Bayesian tracking. IEEE Transactions on signal processing, 50(2), 174-188.

Deme, A., Dajab, D., Buba Bajoga, M. M. A., & Choji, D. (2013). Hata-Okumura Model Computer Analysis for Path Loss Determination at 900MHz for Maiduguri, Nigeria. Mathematical Theory and Modeling, 3(3), 1-9.

Wilson, R. D., & Scholtz, R. A. (2003). Comparison of CDMA and modulation schemes for UWB radio in a multipath environment. In Global Telecommunications Conference, 2003. GLOBECOM'03. IEEE (Vol. 2, pp. 754-758). IEEE.

Nadir, Z., & Suwailam, M. (2014) Pathloss Analysis at 900 MHz for Outdoor Environment. In Proceedings of the 2014 International Conference on Communications, Signal Processing and Computers,(EUROPMENT 2014)(pp. 182-186).

Swiątek, J., Grzech, A., Świątek, J., & Tomczak, J. M. (Eds.). (2013). Advances in Systems Science: Proceedings of the International Conference on Systems Science 2013 (ICSS 2013) (Vol. 240). Springer Science & Business Media.

Nadir, Z., & Ahmad, M. I. (2014). RF Coverage and Pathloss Forecast Using Neural Network. In Advances in Systems Science (pp. 375-384). Springer International Publishing.

Wu, J., & Yuan, D. (1998, September). Propagation measurements and modeling in Jinan city. In Personal, Indoor and Mobile Radio Communications, 1998. The Ninth IEEE International Symposium on (Vol. 3, pp. 1157-1160). IEEE.

Erceg, V., Greenstein, L. J., Tjandra, S. Y., Parkoff, S. R., Gupta, A., Kulic, B., & Bianchi, R. (1999). An empirically based path loss model for wireless channels in suburban environments. IEEE Journal on selected areas in communications, 17(7), 1205-1211.

Frank, H., & Ball, P. (2015). Mobile Networks Beyond 4G. In Proceedings of the World Congress on Engineering (Vol. 1).

A Bhuvaneshwari, R Hemalatha, T Satyasavithri. (2013). Statistical Tuning of the Best suited Prediction Model for Measurements made in Hyderabad City of Southern India. Proceedings of the World Congress on Engineering and Computer Science. San Francisco. 2013; 2.

Segun IP, Olasunkanmi FO. Empirical Path Loss Models for GSM Network Deployment in Makurdi, Nigeria. International Refereed Journal of Engineering and Science (IRJES). 2014; 3: 85-94.

Sachin SK, AN Jadhav (2013) An Empirically Based Path Loss Models for LTE Advanced Network and Modeling for 4G Wireless Systems at 2.4 GHz, 2.6 GHz and 3.5 GHz. International Journal of Application or Innovation in Engineering & Management (IJAIEM). 2013; 2(9): 252-257.

Rekawt SH, TA Rahman, AY Abdulrahman (2014). LTE Coverage Network Planning and Comparison with Different Propagation Models. TELKOMNIKA Telecommunication Computing Electronics and Control. 2014; 12(1): 153-162.

Kale, S., & Jadhav, A. N. (2013). An Empirically Based Path Loss Models for LTE Advanced Network and Modeling for 4G Wireless Systems at 2.4 GHz, 2.6 GHz and 3.5 GHz, International Journal of Application or Innovation in Engineering & Management (IJAIEM), 2(9), 252-257.

Senarath, G., Tong, W., Zhu, P., Zhang, H., Steer, D., Yu, D., & Kitchener, D. (2007). Multi-hop relay system evaluation methodology (channel model and performance metric). IEEE C802. 16j-06/013r3.

Tahcfulloh, S., & Riskayadi, E. (2015). Optimized Suitable Propagation Model for GSM 900 Path Loss Prediction. Indonesian Journal of Electrical Engineering and Computer Science, 14(1), 154-162.

Erceg, V. et al. (2001). Channel Models for Fixed Wireless Applications, Project IEEE 802.16 Broadband Wireless Access Working Group< http://ieee802. org/16>.

Artemenko, O., Nayak, A. H., Menezes, S. B., & Mitschele-Thiel, A. (2015, September). Evaluation of Different Signal Propagation Models for a Mixed Indoor-Outdoor Scenario Using Empirical Data. In International Conference on Ad Hoc Networks (pp. 3-14). Springer International Publishing.


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