IDEAS home Printed from https://ideas.repec.org/a/nat/natcom/v14y2023i1d10.1038_s41467-023-36814-4.html
   My bibliography  Save this article

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

Author

Listed:
  • Weipeng Zhang

    (Princeton University)

  • Alexander Tait

    (Queen’s University)

  • Chaoran Huang

    (The Chinese University of Hong Kong)

  • Thomas Ferreira de Lima

    (Princeton University
    NEC Laboratories America)

  • Simon Bilodeau

    (Princeton University)

  • Eric C. Blow

    (Princeton University)

  • Aashu Jha

    (Princeton University)

  • Bhavin J. Shastri

    (Queen’s University)

  • Paul Prucnal

    (Princeton University)

Abstract

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.

Suggested Citation

  • Weipeng Zhang & Alexander Tait & Chaoran Huang & Thomas Ferreira de Lima & Simon Bilodeau & Eric C. Blow & Aashu Jha & Bhavin J. Shastri & Paul Prucnal, 2023. "Broadband physical layer cognitive radio with an integrated photonic processor for blind source separation," Nature Communications, Nature, vol. 14(1), pages 1-10, December.
  • Handle: RePEc:nat:natcom:v:14:y:2023:i:1:d:10.1038_s41467-023-36814-4
    DOI: 10.1038/s41467-023-36814-4
    as

    Download full text from publisher

    File URL: https://www.nature.com/articles/s41467-023-36814-4
    File Function: Abstract
    Download Restriction: no

    File URL: https://libkey.io/10.1038/s41467-023-36814-4?utm_source=ideas
    LibKey link: if access is restricted and if your library uses this service, LibKey will redirect you to where you can use your library subscription to access this item
    ---><---

    Citations

    Citations are extracted by the CitEc Project, subscribe to its RSS feed for this item.
    as


    Cited by:

    1. Joshua C. Lederman & Weipeng Zhang & Thomas Ferreira Lima & Eric C. Blow & Simon Bilodeau & Bhavin J. Shastri & Paul R. Prucnal, 2023. "Real-time photonic blind interference cancellation," Nature Communications, Nature, vol. 14(1), pages 1-10, December.
    2. Kaihang Lu & Zengqi Chen & Hao Chen & Wu Zhou & Zunyue Zhang & Hon Ki Tsang & Yeyu Tong, 2024. "Empowering high-dimensional optical fiber communications with integrated photonic processors," Nature Communications, Nature, vol. 15(1), pages 1-8, December.
    3. Junwei Cheng & Chaoran Huang & Jialong Zhang & Bo Wu & Wenkai Zhang & Xinyu Liu & Jiahui Zhang & Yiyi Tang & Hailong Zhou & Qiming Zhang & Min Gu & Jianji Dong & Xinliang Zhang, 2024. "Multimodal deep learning using on-chip diffractive optics with in situ training capability," Nature Communications, Nature, vol. 15(1), pages 1-10, December.

    More about this item

    Statistics

    Access and download statistics

    Corrections

    All material on this site has been provided by the respective publishers and authors. You can help correct errors and omissions. When requesting a correction, please mention this item's handle: RePEc:nat:natcom:v:14:y:2023:i:1:d:10.1038_s41467-023-36814-4. See general information about how to correct material in RePEc.

    If you have authored this item and are not yet registered with RePEc, we encourage you to do it here. This allows to link your profile to this item. It also allows you to accept potential citations to this item that we are uncertain about.

    We have no bibliographic references for this item. You can help adding them by using this form .

    If you know of missing items citing this one, you can help us creating those links by adding the relevant references in the same way as above, for each refering item. If you are a registered author of this item, you may also want to check the "citations" tab in your RePEc Author Service profile, as there may be some citations waiting for confirmation.

    For technical questions regarding this item, or to correct its authors, title, abstract, bibliographic or download information, contact: Sonal Shukla or Springer Nature Abstracting and Indexing (email available below). General contact details of provider: http://www.nature.com .

    Please note that corrections may take a couple of weeks to filter through the various RePEc services.

    IDEAS is a RePEc service. RePEc uses bibliographic data supplied by the respective publishers.