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

Wuttipong Kumwilaisak; C.-C. Jay Kuo

doi:10.1117/12.455396

12 November 2002 Nonstationary fading channel modeling with adaptive variable length Markov chains (VLMC)

Proceedings Volume 4869, Emerging Technologies for Future Generation Wireless Communications; (2002) https://doi.org/10.1117/12.455396
Event: ITCom 2002: The Convergence of Information Technologies and Communications, 2002, Boston, MA, United States

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.

Citation Download Citation

Wuttipong Kumwilaisak and C.-C. Jay Kuo "Nonstationary fading channel modeling with adaptive variable length Markov chains (VLMC)", Proc. SPIE 4869, Emerging Technologies for Future Generation Wireless Communications, (12 November 2002); https://doi.org/10.1117/12.455396

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KEYWORDS

Signal to noise ratio

Doppler effect

Statistical modeling

Data modeling

Systems modeling

Telecommunications

Computer simulations

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