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Broadband physical layer cognitive radio with an integrated photonic processor for blind source separation

The expansion of telecommunications incurs increasingly severe crosstalk and interference, and a physical layer cognitive method, called blind source separation (BSS), can effectively address these issues. BSS requires minimal prior knowledge to recover signals from their mixtures, agnostic to the c...

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Autores principales: Zhang, Weipeng, Tait, Alexander, Huang, Chaoran, Ferreira de Lima, Thomas, Bilodeau, Simon, Blow, Eric C., Jha, Aashu, Shastri, Bhavin J., Prucnal, Paul
Formato: Online Artículo Texto
Lenguaje:English
Publicado: Nature Publishing Group UK 2023
Materias:
Acceso en línea:https://www.ncbi.nlm.nih.gov/pmc/articles/PMC9971366/
https://www.ncbi.nlm.nih.gov/pubmed/36849533
http://dx.doi.org/10.1038/s41467-023-36814-4
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author Zhang, Weipeng
Tait, Alexander
Huang, Chaoran
Ferreira de Lima, Thomas
Bilodeau, Simon
Blow, Eric C.
Jha, Aashu
Shastri, Bhavin J.
Prucnal, Paul
author_facet Zhang, Weipeng
Tait, Alexander
Huang, Chaoran
Ferreira de Lima, Thomas
Bilodeau, Simon
Blow, Eric C.
Jha, Aashu
Shastri, Bhavin J.
Prucnal, Paul
author_sort Zhang, Weipeng
collection PubMed
description The expansion of telecommunications incurs increasingly severe crosstalk and interference, and a physical layer cognitive method, called blind source separation (BSS), can effectively address these issues. BSS requires minimal prior knowledge to recover signals from their mixtures, agnostic to the carrier frequency, signal format, and channel conditions. However, previous electronic implementations did not fulfil this versatility due to the inherently narrow bandwidth of radio-frequency (RF) components, the high energy consumption of digital signal processors (DSP), and their shared weaknesses of low scalability. Here, we report a photonic BSS approach that inherits the advantages of optical devices and fully fulfils its “blindness” aspect. Using a microring weight bank integrated on a photonic chip, we demonstrate energy-efficient, wavelength-division multiplexing (WDM) scalable BSS across 19.2 GHz processing bandwidth. Our system also has a high (9-bit) resolution for signal demixing thanks to a recently developed dithering control method, resulting in higher signal-to-interference ratios (SIR) even for ill-conditioned mixtures.
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spelling pubmed-99713662023-03-01 Broadband physical layer cognitive radio with an integrated photonic processor for blind source separation Zhang, Weipeng Tait, Alexander Huang, Chaoran Ferreira de Lima, Thomas Bilodeau, Simon Blow, Eric C. Jha, Aashu Shastri, Bhavin J. Prucnal, Paul Nat Commun Article The expansion of telecommunications incurs increasingly severe crosstalk and interference, and a physical layer cognitive method, called blind source separation (BSS), can effectively address these issues. BSS requires minimal prior knowledge to recover signals from their mixtures, agnostic to the carrier frequency, signal format, and channel conditions. However, previous electronic implementations did not fulfil this versatility due to the inherently narrow bandwidth of radio-frequency (RF) components, the high energy consumption of digital signal processors (DSP), and their shared weaknesses of low scalability. Here, we report a photonic BSS approach that inherits the advantages of optical devices and fully fulfils its “blindness” aspect. Using a microring weight bank integrated on a photonic chip, we demonstrate energy-efficient, wavelength-division multiplexing (WDM) scalable BSS across 19.2 GHz processing bandwidth. Our system also has a high (9-bit) resolution for signal demixing thanks to a recently developed dithering control method, resulting in higher signal-to-interference ratios (SIR) even for ill-conditioned mixtures. Nature Publishing Group UK 2023-02-27 /pmc/articles/PMC9971366/ /pubmed/36849533 http://dx.doi.org/10.1038/s41467-023-36814-4 Text en © The Author(s) 2023 https://creativecommons.org/licenses/by/4.0/Open Access This article is licensed under a Creative Commons Attribution 4.0 International License, which permits use, sharing, adaptation, distribution and reproduction in any medium or format, as long as you give appropriate credit to the original author(s) and the source, provide a link to the Creative Commons license, and indicate if changes were made. The images or other third party material in this article are included in the article’s Creative Commons license, unless indicated otherwise in a credit line to the material. If material is not included in the article’s Creative Commons license and your intended use is not permitted by statutory regulation or exceeds the permitted use, you will need to obtain permission directly from the copyright holder. To view a copy of this license, visit http://creativecommons.org/licenses/by/4.0/ (https://creativecommons.org/licenses/by/4.0/) .
spellingShingle Article
Zhang, Weipeng
Tait, Alexander
Huang, Chaoran
Ferreira de Lima, Thomas
Bilodeau, Simon
Blow, Eric C.
Jha, Aashu
Shastri, Bhavin J.
Prucnal, Paul
Broadband physical layer cognitive radio with an integrated photonic processor for blind source separation
title Broadband physical layer cognitive radio with an integrated photonic processor for blind source separation
title_full Broadband physical layer cognitive radio with an integrated photonic processor for blind source separation
title_fullStr Broadband physical layer cognitive radio with an integrated photonic processor for blind source separation
title_full_unstemmed Broadband physical layer cognitive radio with an integrated photonic processor for blind source separation
title_short Broadband physical layer cognitive radio with an integrated photonic processor for blind source separation
title_sort broadband physical layer cognitive radio with an integrated photonic processor for blind source separation
topic Article
url https://www.ncbi.nlm.nih.gov/pmc/articles/PMC9971366/
https://www.ncbi.nlm.nih.gov/pubmed/36849533
http://dx.doi.org/10.1038/s41467-023-36814-4
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