Broadband physical layer cognitive radio with an integrated photonic processor for blind source separation
Weipeng Zhang, Alexander Tait, Chaoran Huang, Thomas Ferreira de Lima,, Simon Bilodeau, Eric Blow, Aashu Jha, Bhavin J. Shastri, Paul Prucnal

TL;DR
This paper introduces a broadband, energy-efficient photonic system for blind source separation that overcomes the bandwidth and scalability limitations of electronic methods, enabling versatile signal recovery across standard frequency bands.
Contribution
It presents a novel photonic BSS approach with integrated microring weight banks, achieving high bandwidth, energy efficiency, and resolution, surpassing previous electronic implementations.
Findings
Demonstrated WDM-scalable BSS over 19.2 GHz bandwidth
Achieved high (9-bit) resolution for signal demixing
Provided higher SIR for complex mixtures
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 carrier frequency, signal format, and channel conditions. However, previous electronic implementations of BSS did not fulfill this versatility requirement 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 can fully fulfill its "blindness" aspect. Using a microring weight bank integrated on a photonic chip, we demonstrate energy-efficient, WDM-scalable BSS across 19.2 GHz…
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Taxonomy
TopicsOptical Network Technologies · Neural Networks and Reservoir Computing · Advanced Photonic Communication Systems
