Title :
Quantifying uncertainty in ray-tracing models of radiowave propagation using polynomial chaos
Author :
Austin, Andrew C. M. ; Sood, Neeraj ; Sarris, Costas D.
Author_Institution :
Dept. of Electr. & Comput. Eng., Univ. of Toronto, Toronto, ON, Canada
Abstract :
Randomness in the input parameters of a ray-tracing simulator introduces uncertainty in the predictions of the received power and voltage. The polynomial chaos method is applied to efficiently estimate the uncertainty arising from randomness in the material properties for a site-specific ray-tracing analysis of an indoor hallway. The uncertainty is compared against a converged set of Monte-Carlo simulations and with experimental measurements of the sector-averaged received power. Results indicate a 2-3 dB variation in the received power can exist for relatively small material parameter uncertainties.
Keywords :
Monte Carlo methods; indoor radio; polynomials; radiowave propagation; ray tracing; wireless channels; Monte-Carlo simulations; indoor hallway; indoor wireless channels; material properties randomness; parameter uncertainties; polynomial chaos; quantifying uncertainty estimation; radiowave propagation; ray-tracing models; sector-averaged received power; Chaos; Computational modeling; Material properties; Monte Carlo methods; Polynomials; Ray tracing; Uncertainty; Propagation; Ray-Tracing; Uncertainty;
Conference_Titel :
Antennas and Propagation (EuCAP), 2014 8th European Conference on
Conference_Location :
The Hague
DOI :
10.1109/EuCAP.2014.6902136