Gaussian Coarse Graining of a Master Equation Extension of Clarke's Model
2012 (English)Report (Other academic) [Artistic work]
We study the error and computational cost of generating outputsignal realizations for the channel model of a moving receiver in a scatteringenvironment, as in Clarke’s model, with the extension that scatterers randomlyflip on and off. At micro scale, the channel is modeled by a Multipath FadingChannel (MFC) model, and by coarse graining the micro scale model we derivea macro scale Gaussian process model. Four algorithms are presented for gen-erating stochastic signal realizations, one for the MFC model and three for theGaussian process model. A computational cost comparison of the presentedalgorithms indicates that Gaussian process algorithms generate signal realiza-tions more efficiently than the MFC algorithm does. Numerical examples ofgenerating signal realizations in time independent and time dependent scatter-ing environments are given, and the problem of estimating model parametersfrom real life signal measurements is also studied.
Place, publisher, year, edition, pages
Stockholm: KTH Royal Institute of Technology, 2012. , 30 p.
Trita-NA, ISSN 0348-2952 ; 2012:5
Wireless channel modeling; signal theory; master equations; Gaussian processes
Probability Theory and Statistics
IdentifiersURN: urn:nbn:se:kth:diva-94105OAI: oai:DiVA.org:kth-94105DiVA: diva2:525317
Funded by Centre for Industrial and Applied Mathematics (CIAM). QC 201205082012-05-082012-05-072012-05-08Bibliographically approved