Abstract
Here we develop the first optical neuromorphic processor for frequency-multiplexed and multi-channel signals and demonstrate its application for orthogonal frequency-division multiplexing and wavelength-division multiplexing. The presented architecture supports multichannel operation through incorporation of the optical Fourier transform and dispersion-managed fiber echo state network analogue enabling processing of dual-quadrature high bandwidth signals. We demonstrate applicability of the design for prediction and equalization tasks. The proposed technology paves the way to multi-channel neuromorphic signal processing.
Highlights
The growing surge in optical neuromorphic computing [1] is driven by the emerging artificial intelligence (AI) and Internet of things (IoT) applications, which require fast signal processing and flexible design
The existing neuromorphic systems are limited to a single-channel operation, while typical transmission systems are multi-channel, such as orthogonal frequency-division multiplexing (OFDM) [7, 8] or wavelength division multiplexing (WDM) [9]
To illustrate applicability for various bandwidth parameters, we modelled two cases (i) future 5G-oriented case with the enhanced bandwidth plotted in figure 3 and (ii) standard OFDM parameters plotted in figures 4 and 5
Summary
The growing surge in optical neuromorphic computing [1] is driven by the emerging artificial intelligence (AI) and Internet of things (IoT) applications, which require fast signal processing and flexible design. The existing neuromorphic systems are limited to a single-channel operation, while typical transmission systems are multi-channel, such as orthogonal frequency-division multiplexing (OFDM) [7, 8] or wavelength division multiplexing (WDM) [9]. Current trends, including 5G and IoT, envision even more applications for signal multiplexing. The emerging technologies, such as massive connectivity and spectrum slicing, require flexibility in spectrum allocation, which poses a requirement for neuromorphic systems to operate frequency-multiplexed signals, while current neurmorphic systems are typically designed for time-multiplexing. There is a demand for neuromorphic technologies capable for processing frequency-multiplexed signals and support multi-channel operation
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