42 research outputs found
Experimental demonstration of nonlinear fibre distortion compensation with integrated photonic reservoir computing
No full textOptical reservoir computing is a machine learning technique in which a photonic chip can be trained on classification tasks of time signals. This paper presents experimental results where linear and nonlinear fibre distortions are mitigated to below the 0.2×10 −3 FEC limit using a photonic reservoir
Photonic reservoir computing for nonlinear equalization of 64-QAM signals with a Kramers-Kronig receiver
No full textPhotonic reservoir computing is a promising processing solution for the equalization of fiber optic communication signals. We simulate the nonlinear equalization of 64 Quadrature-Amplitude Modulated signals using a fully passive space multiplexed reservoir. The system deploys direct detection using the recently proposed Kramers-Kronig receiver. (C) 2022 The Author(s
Experimental realization of integrated photonic reservoir computing for nonlinear fiber distortion compensation
No full textNonlinearity mitigation in optical fiber networks is typically handled by electronic Digital Signal Processing (DSP) chips. Such DSP chips are costly, power-hungry and can introduce high latencies. Therefore, optical techniques are investigated which are more efficient in both power consumption and processing cost. One such a machine learning technique is optical reservoir computing, in which a photonic chip can be trained on certain tasks, with the potential advantages of higher speed, reduced power consumption and lower latency compared to its electronic counterparts. In this paper, experimental results are presented where nonlinear distortions in a 32 GBPS OOK signal are mitigated to below the 0.2 x 10(-3) FEC limit using a photonic reservoir. Furthermore, the results of the reservoir chip are compared to a tapped delay line filter to clearly show that the system performs nonlinear equalisation. (C) 2021 Optical Society of America under the terms of the OSA Open Access Publishing Agreemen
Experimental Demonstration of 4-Port Photonic Reservoir Computing for Equalization of 4 and 16 QAM Signals
No full textWe experimentally demonstrate the application of a passive 16-node photonic reservoir for analogue, hardware-based equalization of coherently modulated signals at 28 Gbaud. This integrated photonic network, termed the 4-port reservoir, replaces computationally expensive digital signal processing (DSP) procedures for both fiber impairment equalization, including chromatic dispersion, as well as for transceiver imbalance equalization. For full mitigation of transmission impairments, our photonic solution can seamlessly integrate with DSP blocks for frequency offset compensation and blind phase search, achieving bit error rates on-par with the legacy DSP blocks it replaces. The same reservoir is shown to successfully equalize both 4 and 16 QAM signals in a range of linear and nonlinear transmissions
Wavelength dimension in waveguide-based photonic reservoir computing
No full textExisting work on coherent photonic reservoir computing (PRC) mostly concentrates on single-wavelength solutions. In this paper, we discuss the opportunities and challenges related to exploiting the wavelength dimension in integrated photonic reservoir computing systems. Different strategies are presented to be able to process several wavelengths in parallel using the same readout. Additionally, we present multiwavelength training techniques that allow to increase the stable operating wavelength range by at least a factor of two. It is shown that a single-readout photonic reservoir system can perform with approximate to 0% BER on several WDM channels in parallel for bit-level tasks and nonlinear signal equalization. This even when taking manufacturing deviations and laser wavelength drift into account. (C) 2022 Optica Publishing Group under the terms of the Optica Open Access Publishing Agreemen
Experimental results on nonlinear distortion compensation using photonic reservoir computing with a single set of weights for different wavelengths
No full textPhotonics-based computing approaches in combination with wavelength division multiplexing offer a potential solution to modern data and bandwidth needs. This paper experimentally takes an important step towards wavelength division multiplexing in an integrated waveguide-based photonic reservoir computing platform by using a single set of readout weights for up to at least 3 ITU-T channels to efficiently scale the data bandwidth when processing a nonlinear signal equalization task on a 28 Gbps modulated on-off keying signal. Using multiple-wavelength training, we obtain bit error rates well below that of the 1.5 x 10(-2) forward error correction limit at high fiber input powers of 18 dBm, which result in high nonlinear distortion. The results of the reservoir chip are compared to a tapped delay line filter and clearly show that the system performs nonlinear equalization. This was achieved using only limited post processing which in future work can be implemented in optical hardware as well
Photonic reservoir computing for wavelength multiplexed nonlinear fiber distortion mitigation
No full textWe seek to improve nonlinear fiber distortion mitigation for wavelength multiplexed telecommunications in terms of both processing speed and energy efficiency. We propose a photonic reservoir computing hardware implementation maximizing the chip footprint to processing power ratio by employing a single readout for all wavelengths
