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Proceedings Paper

An adaptive channel prediction algorithm based on fractal Brownian motion model
Author(s): Gang Su; Yingzhuang Liu; Hao Chen
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Paper Abstract

Adaptive channel prediction (ACP) technology is a promising tool for improving the spectral efficiency on time-varying mobile channels while keeping a predictable bit error rate (BER). In this paper, we describe the fractal Brownian motion (FBM) model and get the interior affiliation between the multi-path fading and FBM model by comparing various fractal characteristics of fading signals, especially the existence of self-similarity. The self-similarity of fractal characteristics indicates the existence of a nontrivial predictive structure, where the fractal dimension and variance are important parameters for describing the signal propagation. The wavelet synthesis algorithm based on FBM is proposed to reconstruct multi-path signals, yielding reasonably accurate replication at a cost of allowable calculating error. Simulation results indicate that the FBM model could predict wireless channel more accurately and effectively than those statistical models on the minimum SNR.

Paper Details

Date Published: 4 January 2006
PDF: 5 pages
Proc. SPIE 5985, International Conference on Space Information Technology, 59851J (4 January 2006); doi: 10.1117/12.657301
Show Author Affiliations
Gang Su, Huazhong Univ. of Science and Technology (China)
Yingzhuang Liu, Huazhong Univ. of Science and Technology (China)
Hao Chen, Huazhong Univ. of Science and Technology (China)

Published in SPIE Proceedings Vol. 5985:
International Conference on Space Information Technology
Cheng Wang; Shan Zhong; Xiulin Hu, Editor(s)

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