An adaptive channel prediction algorithm based on fractal Brownian motion model

Gang Su; Yingzhuang Liu; Hao Chen

doi:10.1117/12.657301

4 January 2006 An adaptive channel prediction algorithm based on fractal Brownian motion model

Gang Su, Yingzhuang Liu, Hao Chen

Proceedings Volume 5985, International Conference on Space Information Technology; 59851J (2006) https://doi.org/10.1117/12.657301
Event: International Conference on Space information Technology, 2005, Wuhan, China

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.

Citation Download Citation

Gang Su, Yingzhuang Liu, and Hao Chen "An adaptive channel prediction algorithm based on fractal Brownian motion model", Proc. SPIE 5985, International Conference on Space Information Technology, 59851J (4 January 2006); https://doi.org/10.1117/12.657301

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