Calibration of Empirical Models for Path Loss Prediction in Urban Environment

Abstract

The reliability and accuracy of radio propagation models depends on the unique localized features in the area under study. In this paper, we calibrate empirical radio propagation models for 1800 MHz cellular network planning in Lagos Metropolis, Nigeria. Drive test are conducted to obtain measured data within suburban and dense urban propagation environment. Received Signal Strength (RSS) and path loss values of radio signals in 1800 MHz cellular networks are recorded for model calibration and evaluation. COST 231–Hata model achieved the closest prediction results relative to the field measurement. Mean Error (ME), Standard Deviation (SD) and Root Mean Square (RMS) results are 11.004 dB, 12.194 dB and 16.43 dB respectively in dense suburban, while the corresponding results are 9.151 dB, 8.151 dB and 12.254 dB in dense urban. ME of all the calibrated propagation prediction models reduced to nearly zero ($\approx 0$ dB). Also, the SD and the RMS fall within the calibration quality target with ME as less than 1 dB and SD is less than 8.5 dB for each of the calibrated models. In conclusion, the proposed calibrated path loss models achieved minimum mean error and standard deviation. Prediction results improved when terrain type and clutter data were taken into account during path loss calculations.