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On the Response of Basic Walfisch-Ikegami and Walfisch-Bertoni Models to QMM Calibration

International Journal of Computer Applications
Foundation of Computer Science (FCS), NY, USA
Year of Publication: 2021
Ayotunde Ayorinde, Hisham Muhammed, A. Ike Mowete

Ayotunde Ayorinde, Hisham Muhammed and Ike A Mowete. On the Response of Basic Walfisch-Ikegami and Walfisch-Bertoni Models to QMM Calibration. International Journal of Computer Applications 174(18):53-64, February 2021. BibTeX

	author = {Ayotunde Ayorinde and Hisham Muhammed and A. Ike Mowete},
	title = {On the Response of Basic Walfisch-Ikegami and Walfisch-Bertoni Models to QMM Calibration},
	journal = {International Journal of Computer Applications},
	issue_date = {February 2021},
	volume = {174},
	number = {18},
	month = {Feb},
	year = {2021},
	issn = {0975-8887},
	pages = {53-64},
	numpages = {12},
	url = {},
	doi = {10.5120/ijca2021921100},
	publisher = {Foundation of Computer Science (FCS), NY, USA},
	address = {New York, USA}


This paper systematically examines the response to Quasi-Moment-Method (QMM) calibration, of the basic COST231-Walfisch-Ikegami, ITUR-Walfisch-Ikegami, and Walfisch-Bertoni models. First, it is demonstrated that the component parameters of the models are suitable candidates for use as expansion/testing functions with QMM pathloss model calibration schemes; and thereafter, the basic models are subjected to calibration, using measurement data available in the open literature. Computational results reveal that the COST231-Walfisch-Ikegami and ITU-Walfisch-Ikegami models have virtually identical QMM-calibration root mean square error (RMSE) responses; and that the Walfisch-Bertoni model has better RMSE responses than both of them. A particular attribute revealed by the simulation results is that all QMM-calibrated ‘Walfisch-type’ basic models have excellent mean prediction error (MPE) metrics (in general, less than 0.001dB). In addition to pathloss prediction profiles, the paper also presents profiles of disaggregated net pathloss, in terms of contributions by component parameters, including ‘roof-top-to-street’ diffraction and scatter loss and multiscreen diffraction loss.


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Quasi-Moment-Method; Walfisch-Ikegami; Walfisch-Bertoni; ECC-33