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

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 of bandwidth, covering many standard frequency bands. 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.