Digital All-Optical Physical-Layer Network Coding

Network coding (NC) has recently attracted intense research focus for its potential to provide network throughput enhancements, security and reduced network congestions, improving in this way the overall network performance without requiring additional resources. In this chapter, the all-optical physical-layer network coding (AOPNC) technique is presented, focusing on digital encoding schemes that are based on optical XOR logical gates. It is also discussed how digital AOPNC can be implemented between sub-carrier-modulated (SCM) optical signals in radio-over-fiber (RoF) networks, circumventing the enhanced complexity arising by the use of SCM signals and the asynchrony that might exist between the data arriving at the encoding unit. AOPNC demonstrations are described for simple on/off keyed (OOK)-SCM data signals, as well as for more sophisticated higher-order phase modulation formats aiming to further improve spectrum efficiency and transmission capacity

Chapter Efficient and Validated Time Domain Numerical Modeling of Semiconductor Optical Amplifiers (SOAs) and SOA-based Circuits

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Efficient and Validated Time Domain Numerical Modeling of Semiconductor Optical Amplifiers (SOAs) and SOA-based Circuits

Semiconductor optical amplifiers (SOAs) have been extensively used in a wealth of telecom and datacom applications as a powerful building block that features large optical gain, all-optical gating function, fast response, and ease of integration with other functional semiconductor devices. As fabrication technologies are steadily maturing toward enhanced yield, SOAs are foreseen to play a pivotal role in complex photonics integrated circuits (PICs) of the near future. From a design standpoint, accurate numerical modeling of SOA devices is required toward optimizing PICs response from a system perspective, while enhanced circuit complexity calls for efficient solvers. In this book chapter, we present established experimentally validated SOA numerical modeling techniques and a gain parameterization procedure applicable to a wide range of SOA devices. Moreover, we describe multigrid concepts and implicit schemes that have been only recently presented to SOA modeling, enabling adaptive time stepping at the SOA output, with dense sampling at transient phenomena during the gain recovery and scarce sampling during the steady-state response. Overall, a holistic simulation methodology approach along with recent research trends are described, aiming to form the basis of further developments in SOA modeling

Coherent photonic crossbar as a universal linear operator

Linear optics aim at realizing any real- and/or complex-valued matrix operator via optical elements, addressing a broad field of applications in the areas of quantum photonics, microwave photonics and optical neural networks. The transfer of linear operators into photonic experimental layouts typically relies on Singular Value Decomposition (SVD) techniques combining meshes of cascaded 2x2 Mach Zehnder Interferometers (MZIs), with the main challenges being the precision in the experimental representation of the targeted matrix, referred to as fidelity, and the overall insertion loss. We demonstrate a novel interferometric coherent photonic crossbar architecture (Xbar) that demarcates from state-of-the-art SVD implementations and can realize any linear operator, supporting full restoration of the loss-induced fidelity. Its novel interferometric design allows for the direct mapping of each matrix element to a single, designated Xbar node, bringing down the number of programming steps to only one. We present the theoretical foundations of the Xbar, proving that its insertion losses scale linearly with the node losses as opposed to the exponential scaling witnessed by the SVD counterparts. This leads to a matrix design with significantly lower overall insertion losses compared to SVD-based schemes when utilizing state-of-the-art silicon photonic fabrication metrics, allowing for alternative node technologies with lower energy consumption and higher operational speed credentials to be employed. Finally, we validate that our Xbar architecture is the first linear operator that supports fidelity restoration, outperforming SVD schemes in loss- and phase-error fidelity performance and forming a significantly more robust layout to loss and phase deviations

4-channel 200 Gb/s WDM O-band silicon photonic transceiver sub-assembly

We demonstrate a 200G capable WDM O-band optical transceiver comprising a 4-element array of Silicon Photonics ring modulators (RM) and Ge photodiodes (PD) co-packaged with a SiGe BiCMOS integrated driver and a SiGe transimpedance amplifier (TIA) chip. A 4 x 50 Gb/s data modulation experiment revealed an average extinction ratio (ER) of 3.17 dB, with the transmitter exhibiting a total energy efficiency of 2 pJ/bit. Data reception has been experimentally validated at 50 Gb/s per lane, achieving an interpolated 10E-12 bit error rate (BER) for an input optical modulation amplitude (OMA) of -9.5 dBm and a power efficiency of 2.2 pJ/bit, yielding a total power efficiency of 4.2 pJ/bit for the transceiver, including heater tuning requirements. This electro-optic subassembly provides the highest aggregate data-rate among O-band RM-based silicon photonic transceiver implementations, highlighting its potential for next generation WDM Ethernet transceivers. (C) 2020 Optical Society of America under the terms of the OSA Open Access Publishing Agreement

52 km-long transmission link using a 50 Gb/s O-band silicon microring modulator co-packaged with a 1V-CMOS driver

We present an O-band silicon microring modulator with up to 50 Gb/s modulation rates, co-packaged with a 1V-CMOS driver in a dispersion un-compensated, transmission experiment through 52 km of standard single-mode fiber. The experimental results show 10(-9) error-rate operation with a negligible power penalty of 0.2 dB for 40 Gb/s and wide-open eye diagrams for 50 Gb/s data, corresponding to a record high bandwidth-distance product of 2600 Gb.km/s. A comparative analysis between the proposed transmitter assembly and a commercial LiNbO3 modulator revealed a moderate increase of 3.8 dB in power penalty, requiring only 20% of the driving voltage level used by the commercial modulator

High-performance end-to-end deep learning IM/DD link using optics-informed neural networks

: In this paper, we introduce optics-informed Neural Networks and demonstrate experimentally how they can improve performance of End-to-End deep learning models for IM/DD optical transmission links. Optics-informed or optics-inspired NNs are defined as the type of DL models that rely on linear and/or nonlinear building blocks whose mathematical description stems directly from the respective response of photonic devices, drawing their mathematical framework from neuromorphic photonic hardware developments and properly adapting their DL training algorithms. We investigate the application of an optics-inspired activation function that can be obtained by a semiconductor-based nonlinear optical module and is a variant of the logistic sigmoid, referred to as the Photonic Sigmoid, in End-to-End Deep Learning configurations for fiber communication links. Compared to state-of-the-art ReLU-based configurations used in End-to-End DL fiber link demonstrations, optics-informed models based on the Photonic Sigmoid show improved noise- and chromatic dispersion compensation properties in fiber-optic IM/DD links. An extensive simulation and experimental analysis revealed significant performance benefits for the Photonic Sigmoid NNs that can reach below BER HD FEC limit for fiber lengths up to 42 km, at an effective bit transmission rate of 48 Gb/s