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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...
Autores principales: | , , , , , |
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Formato: | Online Artículo Texto |
Lenguaje: | English |
Publicado: |
Public Library of Science
2016
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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 |
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author | Al-Samman, A. M. Azmi, M. H. Rahman, T. A. Khan, I. Hindia, M. N. Fattouh, A. |
author_facet | Al-Samman, A. M. Azmi, M. H. Rahman, T. A. Khan, I. Hindia, M. N. Fattouh, A. |
author_sort | Al-Samman, A. M. |
collection | PubMed |
description | 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. |
format | Online Article Text |
id | pubmed-5167263 |
institution | National Center for Biotechnology Information |
language | English |
publishDate | 2016 |
publisher | Public Library of Science |
record_format | MEDLINE/PubMed |
spelling | pubmed-51672632017-01-04 Window-Based Channel Impulse Response Prediction for Time-Varying Ultra-Wideband Channels Al-Samman, A. M. Azmi, M. H. Rahman, T. A. Khan, I. Hindia, M. N. Fattouh, A. PLoS One Research Article 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. Public Library of Science 2016-12-19 /pmc/articles/PMC5167263/ /pubmed/27992445 http://dx.doi.org/10.1371/journal.pone.0164944 Text en © 2016 Al-Samman et al http://creativecommons.org/licenses/by/4.0/ This is an open access article distributed under the terms of the Creative Commons Attribution License (http://creativecommons.org/licenses/by/4.0/) , which permits unrestricted use, distribution, and reproduction in any medium, provided the original author and source are credited. |
spellingShingle | Research Article Al-Samman, A. M. Azmi, M. H. Rahman, T. A. Khan, I. Hindia, M. N. Fattouh, A. Window-Based Channel Impulse Response Prediction for Time-Varying Ultra-Wideband Channels |
title | Window-Based Channel Impulse Response Prediction for Time-Varying Ultra-Wideband Channels |
title_full | Window-Based Channel Impulse Response Prediction for Time-Varying Ultra-Wideband Channels |
title_fullStr | Window-Based Channel Impulse Response Prediction for Time-Varying Ultra-Wideband Channels |
title_full_unstemmed | Window-Based Channel Impulse Response Prediction for Time-Varying Ultra-Wideband Channels |
title_short | Window-Based Channel Impulse Response Prediction for Time-Varying Ultra-Wideband Channels |
title_sort | window-based channel impulse response prediction for time-varying ultra-wideband channels |
topic | Research Article |
url | 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 |
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