Infinera (United States)

This paper presents the thermal cycling reliability of two types of 1657 I/O ceramic column grid array (CGA) assemblies subjected to sequential thermal cycling. It includes a newly developed CGA with braided columns in comparison with a standard copper-wrapped column version. CGA packages are widely used for high-reliability (HR) electronics applications. The daisy-chain CGA packages were assembled onto inversed paired daisy-chain printed circuit boards, primarily using vapor phase reflow, with two assemblies completed using a rework station. The paper first compares the material and mechanical characteristics of the two column types, including pull and bending fatigue strengths. Following visual inspection of peripheral columns and daisy chain verifications, all CGA assemblies were subjected to sequential thermal cycling to determine cycles-to-failures (CTFs). Cycling was performed between <tex xmlns:mml="http://www.w3.org/1998/Math/MathML" xmlns:xlink="http://www.w3.org/1999/xlink">$-55^{\circ} \mathrm{C}$</tex> and <tex xmlns:mml="http://www.w3.org/1998/Math/MathML" xmlns:xlink="http://www.w3.org/1999/xlink">$+125^{\circ} \mathrm{C}$</tex> for 200 cycles. Subsequently, the cold-side temperature was reduced to <tex xmlns:mml="http://www.w3.org/1998/Math/MathML" xmlns:xlink="http://www.w3.org/1999/xlink">$-100^{\circ} \mathrm{C}$</tex> to evaluate the effect of extreme cold temperature on solder-joint failure mechanisms and reliability. Daisy-chain continuity was verified after 200 cycles within the <tex xmlns:mml="http://www.w3.org/1998/Math/MathML" xmlns:xlink="http://www.w3.org/1999/xlink">$-100^{\circ} \mathrm{C}$</tex> to <tex xmlns:mml="http://www.w3.org/1998/Math/MathML" xmlns:xlink="http://www.w3.org/1999/xlink">$+125^{\circ} \mathrm{C}$</tex> range. Results of thermal cycling and inspections are presented with failures identified either due to workmanship issues or wear out mechanisms for the two CGA types. Failure locations were established via five-zone daisy-chain patterns to determine CTF dependency on the distance from the neutral point (DNP) and to identify potential shifts in failure mechanisms under extreme cold cycling conditions.

Abstract The fields of machine learning and artificial intelligence drive researchers to explore energy-efficient, brain-inspired new hardware. Reservoir computing encompasses recurrent neural networks for sequential data processing and matches the performance of other recurrent networks with less training and lower costs. However, traditional software-based neural network (NN) require high energy due to computational demands and massive data transfer needs. A hybrid photonic–electronic reservoir computing (RC) system overcomes this challenge with neuromorphic photonic integrated circuits or NeuroPICs, combining passive photonic reservoirs with electronic readout layers. Here, we introduce a hybrid photonic–electronic RC solution for modulation format identification in C-band telecommunication network monitoring. The NeuroPIC is built on a silicon-on-insulator platform featuring a 4-port reservoir architecture. We discuss the NeuroPIC design, fabrication, experimental performance, and compare it with simulations. The system incorporates nonlinearity through a simple digital readout and achieves close to 100% accuracy in identifying quadrature amplitude modulation formats transmitted over 20 km of optical fiber at a 32 Gbaud symbol rate. The NeuroPIC performance is robust against fabrication imperfections like waveguide propagation loss, phase randomization, and delay line length variations. Experimental results surpassed simulations, attributed to enhanced ‘richness’ of signal interference in the physical system. By integrating an energy-efficient photonic analog processing with electronic readout, this hybrid system reduces the dependence on fully digital NNs, offering a pathway for high-speed temporal data processing in various applications. While system-level energy metrics require further exploration, our work highlights the potential of hybrid approaches to balance performance, fabrication tolerance, and computational efficiency in real-world applications.

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Traditionally, traffic from the access nodes is aggregated in metro-aggregation hubs over rings or horseshoes in a fixed configuration using multiple optical point-to-point (P2P) transceivers. However, this static setup limits dynamic scalability and often leads to inefficient resource usage and high costs, especially under increasing and varying traffic conditions. Coherent optical point-to-multipoint (P2MP) transceivers offer a promising solution for aggregation at this network level. These transceivers allow a single (aggregation) node to communicate with multiple (access) nodes simultaneously via digital subcarrier multiplexing (DSCM) technology. Additionally, their long-distance transmission capabilities enable the placement of the P2MP transceiver root deeper in the hierarchy. In this paper, we propose an extended access aggregation architecture that incorporates modified reconfigurable optical add–drop multiplexers (ROADMs) to support both traditional P2P and P2MP connections. This architecture allows the creation of light-trees to enable P2MP communication and hence to boost transmission flexibility and multiplexing gains. We propose a mixed-integer linear programming (MILP) model to determine the optimal placement of P2MP transceivers and the establishment of light-trees, considering physical layer impairments (PLIs) and the required quality of transmission (QoT) for the connections. To tackle the high algorithm complexity, we also introduce a best-fit decreasing heuristic to efficiently exploit the trade-off between execution time and performance. Our simulation experiments using real network topologies showcase that our proposed architecture can greatly enhance multiplexing gains while considering the operational costs tied to network expansions and upgrades.

This article conducts a comparative study of the complexity reduction of neural network (NN) models for nonlinearity compensation used in digital subcarrier multiplexing (DSCM)-based optical communication systems. We employ the NN model based on bi-directional long short-term memory (biLSTM) and 1D-convolutional NN (1D-CNN) layers. To reduce the computation complexity of the proposed solution, weight clustering is applied to the NN. We specifically compare the performance of our proposed NN-based equalizer with traditional methods such as chromatic dispersion compensation (CDC), digital back-propagation (DBP) and alternative NN, based on triplet coefficients in perturbation analysis, proposed in previous literature, evaluating both Q-factor performance and computational complexity. Our findings show that the NN-based equalizer offers competitive Q-factor improvements while significantly reducing computational complexity, particularly when weight clustering is used. We show that the complexity of the NN can be reduced by up to 91.1% compared to the NN based on the perturbation analysis proposed in previous literature and by 31.5% compared to the DBP with 1 step per span. The results underscore the potential of NN-based approaches to deliver high-performance nonlinear compensation with lower computational demands, positioning them as a promising solution for future optical nonlinear equalizers.

We demonstrate, for the first time, 100Gb/s OTU4 over 400GE PLE (Private Line Emulation) across a packet network with OTN like service over a packet backbone. With the decrease of interest in OTN and emergence of IP over DWDM, PLE is an attractive proposal in the IETF for provisioning leased-lines (which continue to be high-margin services for providers). PLE involves the mapping of high-speed OTN services (OTU4 typically, but also OTU2) on to packets and use a smart signaling infrastructure of the packet switched network to provision pseudo-wires. We developed PLE hardware and interfaces it with IP routers to create 100Gb/s OTU4 over 400Gb/s Ethernet. We showed deterministic latency and low jitter in addition to significant network-wide power saving (up to 50%). Results also conform to the requirements of traditional circuit (OTN) communication.

We report experimental studies of a self-injection locking technique with optically filtered feedback and its influence on optical linewidth, RF linewidth, carrier side-band suppression and frequency stability of a monolithically integrated InP passive mode-locked laser. We use a Fabry-Perot etalon as the photonic filter placed in an external fiber feedback loop for filtering the mode-locked laser output and subsequently self-injection locking. Using this technique, we demonstrate optical axial mode linewidth narrowing by a factor of 100x from 600 MHz to 6 MHz, while improving the RF linewidth by a factor of 50x from 109 kHz to 2.2 kHz. The external cavity modes arising from the fiber feedback loop were suppressed by 20 dB, while the phase noise at 200 kHz offset from the carrier is suppressed by 35 dB. Finally, we implement a coupled optoelectronic loop by using the photo-detected output from the self-injection locked laser and provide feedback to drive the integrated electro-absorption modulator in the laser cavity. The coupled optoelectronic loop is referenced to an external RF source to transfer the stability and further improve the noise performance of the self-injection locked laser. The Allan deviation at 10 s averaging time is 5 x 10 <sup xmlns:mml="http://www.w3.org/1998/Math/MathML" xmlns:xlink="http://www.w3.org/1999/xlink">-12</sup> , showing an improvement of 5 orders of magnitude over passive mode-locking operation.

In the second issue of the Optical Communications and Networks Series in 2023, we have selected four fascinating articles reporting on recent advances in optical communications and networking. They address terabit-class high speed receiver, sunlight data transmission, space division multiplexing (SDM) technology, and transfer learning assisted framework for low-latency human-to-machine (H2M) communications.

This article presents two improvements to, and a warning about a previously unrecognized issue with, statistical modeling, characterization, and simulation. We focus on mismatch, which is key for analog IC design, but the topics addressed are generic. For relative variation (i.e., % difference), we show that conventional measures have significant issues when the variation is large. We present two new measures of % difference between <inline-formula xmlns:mml="http://www.w3.org/1998/Math/MathML" xmlns:xlink="http://www.w3.org/1999/xlink"> <tex-math notation="LaTeX">$y_{2}$ </tex-math></inline-formula> and <inline-formula xmlns:mml="http://www.w3.org/1998/Math/MathML" xmlns:xlink="http://www.w3.org/1999/xlink"> <tex-math notation="LaTeX">$y_{1}$ </tex-math></inline-formula> and show that <inline-formula xmlns:mml="http://www.w3.org/1998/Math/MathML" xmlns:xlink="http://www.w3.org/1999/xlink"> <tex-math notation="LaTeX">$100 \cdot {\mathrm {ln}} (y_{2} / y_{1})$ </tex-math></inline-formula> is the only measure that is physically correct for mismatch. We review existing, but not widely known, robust alternatives to the textbook approach to estimate standard deviation, show the limitations of these, and propose a new method that is intermediate between, and overcomes limitations of, the textbook and robust approaches. We then show how the accuracy of mismatch simulation, critical for analog IC design, is affected by “spurious correlation” between statistical samples; we are not aware that the importance of this has been recognized previously.