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Window-Based Channel Impulse Response Prediction for Time-Varying Ultra-Wideband Channels

This work proposes channel impulse response (CIR) prediction for time-varying ultra-wideband (UWB) channels by exploiting the fast movement of channel taps within delay bins. Considering the sparsity of UWB channels, we introduce a window-based CIR (WB-CIR) to approximate the high temporal resolutio...

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Detalles Bibliográficos
Autores principales: Al-Samman, A. M., Azmi, M. H., Rahman, T. A., Khan, I., Hindia, M. N., Fattouh, A.
Formato: Online Artículo Texto
Lenguaje:English
Publicado: Public Library of Science 2016
Materias:
Acceso en línea:https://www.ncbi.nlm.nih.gov/pmc/articles/PMC5167263/
https://www.ncbi.nlm.nih.gov/pubmed/27992445
http://dx.doi.org/10.1371/journal.pone.0164944
Descripción
Sumario:This work proposes channel impulse response (CIR) prediction for time-varying ultra-wideband (UWB) channels by exploiting the fast movement of channel taps within delay bins. Considering the sparsity of UWB channels, we introduce a window-based CIR (WB-CIR) to approximate the high temporal resolutions of UWB channels. A recursive least square (RLS) algorithm is adopted to predict the time evolution of the WB-CIR. For predicting the future WB-CIR tap of window w(k), three RLS filter coefficients are computed from the observed WB-CIRs of the left w(k−1), the current w(k) and the right w(k+1) windows. The filter coefficient with the lowest RLS error is used to predict the future WB-CIR tap. To evaluate our proposed prediction method, UWB CIRs are collected through measurement campaigns in outdoor environments considering line-of-sight (LOS) and non-line-of-sight (NLOS) scenarios. Under similar computational complexity, our proposed method provides an improvement in prediction errors of approximately 80% for LOS and 63% for NLOS scenarios compared with a conventional method.