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Real-time photonic blind interference cancellation

Author

Listed:
  • Joshua C. Lederman

    (Princeton University)

  • Weipeng Zhang

    (Princeton University)

  • Thomas Ferreira Lima

    (Princeton University
    NEC Laboratories America)

  • Eric C. Blow

    (Princeton University
    NEC Laboratories America)

  • Simon Bilodeau

    (Princeton University)

  • Bhavin J. Shastri

    (Queen’s University)

  • Paul R. Prucnal

    (Princeton University)

Abstract

mmWave devices can broadcast multiple spatially-separated data streams simultaneously in order to increase data transfer rates. Data transfer can, however, be compromised by interference. Photonic blind interference cancellation systems offer a power-efficient means of mitigating interference, but previous demonstrations of such systems have been limited by high latencies and the need for regular calibration. Here, we demonstrate real-time photonic blind interference cancellation using an FPGA-photonic system executing a zero-calibration control algorithm. Our system offers a greater than 200-fold reduction in latency compared to previous work, enabling sub-second cancellation weight identification. We further investigate key trade-offs between system latency, power consumption, and success rate, and we validate sub-Nyquist sampling for blind interference cancellation. We estimate that photonic interference cancellation can reduce the power required for digitization and signal recovery by greater than 74 times compared to the digital electronic alternative.

Suggested Citation

  • 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.
    • Handle: RePEc:nat:natcom:v:14:y:2023:i:1:d:10.1038_s41467-023-43982-w
    DOI: 10.1038/s41467-023-43982-w
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    References listed on IDEAS

    as
    1. 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.
    2. Cheng Wang & Mian Zhang & Xi Chen & Maxime Bertrand & Amirhassan Shams-Ansari & Sethumadhavan Chandrasekhar & Peter Winzer & Marko Lončar, 2018. "Integrated lithium niobate electro-optic modulators operating at CMOS-compatible voltages," Nature, Nature, vol. 562(7725), pages 101-104, October.
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