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Proceedings Paper

Nonstationary fading channel modeling with adaptive variable length Markov chains (VLMC)
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Paper Abstract

A novel adaptive mapping from physical measurements in a non-stationary wireless environment to a variable length Markov chain (VLMC) model is proposed in this research. The proposed scheme consists of two main components: the estimation of channel signal-to-noise ratio (SNR) distribution and discrete VLMC modeling. To obtain the channel SNR distribution, a kernel density stimation algorithm is used to track local hanges of channel statistics resulting from varying mobile environments. With the estimated channel SNR distribution, an iterative partitioning mechanism is performed to construct the VLMC model, which yields a much larger and structurally richer class of models than ordinary higher order Markov chains. Application of this model is presented, which is the computation of fading parameters such as the fading duration and the level crossing rate. The accuracy of the proposed VLMC scheme and the performance of its applications are demonstrated via simulation in a micro-cell non-stationary wireless environment.

Paper Details

Date Published: 12 November 2002
PDF: 12 pages
Proc. SPIE 4869, Emerging Technologies for Future Generation Wireless Communications, (12 November 2002); doi: 10.1117/12.455396
Show Author Affiliations
Wuttipong Kumwilaisak, Univ. of Southern California (United States)
C.-C. Jay Kuo, Univ. of Southern California (United States)


Published in SPIE Proceedings Vol. 4869:
Emerging Technologies for Future Generation Wireless Communications
Carl R. Nassar, Editor(s)

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