Helmut Griesser

ADVA Optical Networking SE · Advanced Technology

Quantum key distribution (QKD) has become a promising option for transmitting sensitive data due to the increased maturity of QKD devices and the threat scalable quantum computers imposes on asymmetric public-key cryptosystems. By utilizing existing infrastructure, e.g., amplifier huts and dark fibers, the cost and complexity of deploying QKD netwo...

For an emulated QKD network, a decentralized key management system is automatically deployed as VNF. We show that dynamic key re-routing overcomes failures in the key distribution layer of meshed QKD-secured OTNs under realistic conditions.

Passive optical network (PON) systems are vulnerable to a variety of failures, including fiber cuts and optical network unit (ONU) transmitter/receiver failures. Any service interruption caused by a fiber cut can result in huge financial losses for service providers or operators. Identifying the faulty ONU becomes difficult in the case of nearly eq...

The rapidly growing traffic demands in fiber-optical networks require flexibility and accuracy in configuring lightpaths, for which fast and accurate quality of transmission (QoT) estimation is of pivotal importance. This paper introduces a machine learning (ML)-based QoT estimation approach that meets these requirements. The proposed gradient-boos...

Optical spectrum as a service (OSaaS) spanning over multiple transparent optical network domains can significantly reduce the investment and operational costs of the end-to-end service. Based on the black-link approach, these services are empowered by reconfigurable transceivers and the emerging disaggregation trend in optical transport networks. T...

A machine learning approach for improving monitoring in passive optical networks with almost equidistant branches is proposed and experimentally validated. It achieves a high diagnostic accuracy of 98.7% and an event localization error of 0.5m

Passive optical networks (PONs) have become a promising broadband access network solution thanks to their wide bandwidth, low-cost deployment and maintenance, and scalability. To ensure a reliable transmission, and to meet service level agreements, PON systems have to be monitored constantly in order to quickly identify and localize network faults...

A machine learning approach for improving monitoring in passive optical networks with almost equidistant branches is proposed and experimentally validated. It achieves a high diagnostic accuracy of 98.7% and an event localization error of 0.5m. © 2022 The Author(s). 1. Introduction Optical passive networks (PONs) have gained popularity as a promisi...

Based on suitable system architectures and realistic specifications, transmit OSNR penalties and spectral constraints of multi-wavelength transponders are identified and analyzed in a network study. We report up to 70% less required lasers at the expense of a slight increase in number of lightpaths.

Operators depend on reliable Q-margin estimates to reliably operate wide-band Optical Spectrum Services. We use long-term performance tracking in live Raman-enabled links to derive service margins for a 375-GHz Optical Spectrum Service.

Lasers are widely regarded as the most critical components in optical communication systems. Their reliability has a significant impact on the system's availability and performance. Conventionally, the methods adopted for laser reliability estimation are based on extrapolation to experimental reliability data derived from accelerated aging tests, a...

The rapidly growing traffic demands in fiber-optical networks require flexibility and accuracy in configuring lightpaths, for which fast and accurate quality of transmission (QoT) estimation is of pivotal importance. This paper introduces a machine learning (ML)-based QoT estimation approach that meets these requirements. The proposed gradient-boos...

Semiconductor lasers, one of the key components for optical communication systems, have been rapidly evolving to meet the requirements of next generation optical networks with respect to high speed, low power consumption, small form factor etc. However, these demands have brought severe challenges to the semiconductor laser reliability. Therefore,...

Semiconductor lasers have been rapidly evolving to meet the demands of next-generation optical networks. This imposes much more stringent requirements on the laser reliability, which are dominated by degradation mechanisms (e.g., sudden degradation) limiting the semiconductor laser lifetime. Physics-based approaches are often used to characterize t...

Encouraged by the emerging disaggregation trend in optical transport networks, operators are willing to offer flexible and future-proof optical spectrum as a service (OSaaS) instead of classical capacity services. To define this modern service in commercial offerings, a commonly accepted, reliable, and easy-to-use service characterization method ha...

Secure and reliable data communication in optical networks is critical for high-speed Internet. However, optical fibers, serving as the data transmission medium providing connectivity to billons of users worldwide, are prone to a variety of anomalies resulting from hard failures (e.g., fiber cuts) and malicious physical attacks [e.g., optical eaves...

We propose a deep learning approach based on an autoencoder for identifying and localizing fiber faults in passive optical networks. The experimental results show that the proposed method detects faults with 97% accuracy, pinpoints them with an RMSE of 0.18 m and outperforms conventional techniques.

In this paper, a data-driven diagnostic and prognostic approach based on machine learning is proposed to detect laser failure modes and to predict the remaining useful life (RUL) of a laser during its operation. We present an architecture of the proposed cognitive predictive maintenance framework and demonstrate its effectiveness using synthetic da...

A hybrid prognostic model based on convolutional neural networks (CNN) and long short-term memory (LSTM) is proposed to predict the laser remaining useful life (RUL). The experimental results show that it outperforms the conventional methods.

A new privacy-preserving federated learning framework allowing laser manufacturers to collaboratively build a robust ML-based laser lifetime prediction model, is proposed. It achieves a mean absolute error of 0.1 years and a significant performance improvement

Optical time-domain reflectometry (OTDR) has been widely used for characterizing fiber optical links and for detecting and locating fiber faults. OTDR traces are prone to be distorted by different kinds of noise, causing blurring of the backscattered signals, and thereby leading to a misleading interpretation and a more cumbersome event detection t...

A novel approach based on an artificial neural network (ANN) for lifetime prediction of 1.55 um InGaAsP MQW-DFB laser diodes is presented. It outperforms the conventional lifetime projection using accelerated aging tests.

Fast and accurate fault detection and localization in fiber optic cables is extremely important to ensure the optical network survivability and reliability. Hence there exists a crucial need to develop an automatic and reliable algorithm for real time optical fiber fault detection and diagnosis leveraging the telemetry data obtained by an optical t...

Secure and reliable data communication in optical networks is critical for high-speed Internet. However, optical fibers, serving as the data transmission medium providing connectivity to billons of users worldwide, are prone to a variety of anomalies resulting from hard failures (e.g., fiber cuts) and malicious physical attacks (e.g., optical eaves...

To reduce operation-and-maintenance expenses (OPEX) and to ensure optical network survivability, optical network operators need to detect and diagnose faults in a timely manner and with high accuracy. With the rapid advancement of telemetry technology and data analysis techniques, data-driven approaches leveraging telemetry data to tackle the fault...

A new privacy-preserving federated learning framework allowing laser manufacturers to collaboratively build a robust ML-based laser lifetime prediction model, is proposed. It achieves a mean absolute error of 0.1 years and a significant performance improvement.

A novel multitask learning approach based on stacked bidirectional long short-term memory (BiLSTM) networks and convolutional neural networks (CNN) for detecting, locating, characterizing, and identifying fiber faults is proposed. It outperforms conventionally employed techniques.

An ML model based on precomputed per-channel SCI is proposed. Due to its superior accuracy over closed-form GN, an average SNR gain of 1.1 dB in an end-to-end link optimization and a 40% reduction in required lightpaths to meet traffic requests in a network planning scenario are shown.

We demonstrate QoT estimation in a live network utilizing neural networks trained on synthetic data spanning a large parameter space. The ML-model predicts the measured lightpath performance with <0.5dB SNR error over a wide configuration range.

We propose a deep learning approach based on an autoencoder for identifying and localizing fiber faults in passive optical networks. The experimental results show that the proposed method detects faults with 97% accuracy, pinpoints them with an RMSE of 0.18 m and outperforms conventional techniques.

We test the concept of extended channel probing in an Optical Spectrum as a Service scenario in coherent optimized flex-grid long-haul and 10Gbit/s OOK optimized 100-GHz fixed-grid dispersion-managed legacy DWDM networks. An estimation accuracy better than +/- 0.1dB in GSNR implementation margin is obtained for both networks by using flexible coher...

The potential to operate third-party terminals over multi-domain transparent optical networks attracts operators and customers to implement Optical Spectrum as a Service (OSaaS). As infrastructure information cannot always be shared with OSaaS end customers, alternatives to off-line Quality of Transmission (QoT) estimation tools are required to ass...

We use channel probing to determine the best transponder configurations for spectral services in a long-haul production network. An estimation accuracy better than +/- 0,7dB in GSNR margin is obtained for lightpaths up to 5738km.

A hybrid prognostic model based on convolutional neural networks (CNN) and long short-term memory (LSTM) is proposed to predict the laser remaining useful life (RUL). The experimental results show that it outperforms the conventional methods.

A novel multitask learning approach based on stacked bidirectional long short-term memory (BiLSTM) networks and convolutional neural networks (CNN) for detecting, locating, characterizing, and identifying fiber faults is proposed. It outperforms conventionally employed techniques.

To reduce operation-and-maintenance expenses (OPEX) and to ensure optical network survivability, optical network operators need to detect and diagnose faults in a timely manner and with high accuracy. With the rapid advancement of telemetry technology and data analysis techniques, data-driven approaches leveraging telemetry data to tackle the fault...

The potential to operate third-party terminals over multi-domain transparent optical networks attracts operators and customers to implement optical spectrum as a service (OSaaS). Because infrastructure information cannot always be shared with OSaaS end customers, alternatives to off-line quality of transmission (QoT) estimation tools are required t...

We demonstrate a practical key management scheme for a quantum key distribution network. Multi-vendor QKD systems are interoperated via a standard interface and a key relay is dynamically routed by SDN.

We demonstrate QoT estimation in a live network utilizing neural networks trained on synthetic data spanning a large parameter space. The ML-model predicts the measured lightpath performance with < 0.5dB SNR error over a wide configuration range.

Probabilistic constellation shaping (PCS) offers a significant performance improvement over uniform signaling. It was recently discovered that long blocks are not required to achieve maximum shaping gain when transmitting over the nonlinear fiber channel because short-length PCS effectively mitigates fiber nonlinear interference (NLI). The reason f...

We test the concept of extended channel probing in a Optical Spectrum as a Service scenario in coherent optimized flex-grid long-haul and 10Gbit/s OOK optimized 100-GHz fixed-grid dispersion managed legacy DWDM networks. An estimation accuracy better than ±0.1dB in GSNR implementation margin is obtained for both networks by using flexible coherent...

We demonstrate up to 12 km, 56 Gb/s DMT transmission using high-speed VCSELs in the 1.5 um wavelength range for future 400Gb/s intra-data center connects, enabled by vestigial sideband filtering of the transmit signal.

We review some currently discussed solutions for 400 Gbit/s inter-data center WDM transmission for up to 100 km. We focus on direct detected solutions, namely PAM4 and DMT, and present two WDM systems based on these formats.

We review three solutions for low-cost data center interconnects with a target reach of up to 80 km. Directly detected DMT, PAM-4 and multi-band CAP are promising modulation schemes, enabling 400 Gbit/s by combining eight channels of 56 Gbit/s.

We review currently discussed solutions for 80 km DWDM transmission targeting inter data-center connections at 100G and 400G line rates. PDM-64QAM, PAM4 and DMT are investigated, while the focus lies on directly detected solutions.

Discrete multi-tone transmission (DMT) is a promising candidate for future 400G data center interconnects. Eight channels, each carrying 56 Gb/s of data can be combined in a 50-GHz channel grid to form a 400 Gb/s superchannel. For a fully loaded 96 channel DWDM system this leads to a total capacity of 4.8 Tb/s. To meet the requirements of the targe...

We experimentally evaluate a flexible DMT system using 4 to 8 50-GHz-grid C-band channels to transmit 448 Gb/s over up to 240 km SSMF. VSB filtering enabled by detuned lasers significantly reduces the impact of chromatic dispersion.

The novel 3-dimensional modulation format 3D-Simplex offers potentially 1.2 dB higher OSNR tolerance than DP-DPSK while exhibiting the same spectral occupancy, modulating two bits per symbol. We verify this benefit experimen-tally and evaluate the transmission performance in a non-linear environment. All experimental results are confirmed by simula...

Enabled by channel adaptive bit and power loading, we experimentally demonstrate discrete multitone transmission at 56Gb/s with simple intensity modulation and direct detection and achieve 50 km reach in the 1.55um window.

In this paper, a data-driven diagnostic and prognostic approach based on machine learning is proposed to detect laser failure modes and to predict the remaining useful life (RUL) of a laser during its operation. We present an architecture of the proposed cognitive predictive maintenance framework and demonstrate its effectiveness using synthetic da...

In this paper, we study amplitude shaping schemes for the probabilistic amplitude shaping (PAS) framework as well as algorithms for constant-composition distribution matching (CCDM). Huffman-coded sphere shaping (HCSS) is discussed in detail, which internally uses Huffman coding to determine the composition to be used and relies on conventional CCD...

In order to realize probabilistically shaped signaling within the probabilistic amplitude shaping (PAS) framework, a shaping device outputs sequences that follow a certain nonuniform distribution. In case of constant-composition (CC) distribution matching (CCDM), the sequences differ only in the ordering of their constituent symbols, whereas the nu...

We report on 112 Gbit/s real-time DMT transmission over up to 60 km, targeted at DCI applications. Chromatic dispersion mitigation by vestigial sideband filtering is compared to the use of dispersion compensating fiber.

DMT at 25 Gbit/s, 50 Gbit/s and 100 Gbit/s in passive systems with electro-absorption modulators is investigated. Transmission in C- and O-band are compared, yielding up to 22 km reach, 100 Gbit/s in O-band. All results are obtained with a real-time signal processing ASIC.

We experimentally demonstrate a novel 3-dimensional modulation format with 1.2-dB OSNR tolerance improvement potential compared to DP-BPSK, as verified for the linear case. The non-linearity tolerance is evaluated in single-span transmission over 300km SSMF.

In this paper, we study amplitude shaping schemes for the probabilistic amplitude shaping (PAS) framework as well as algorithms for constant-composition distribution matching (CCDM). Huffman-coded sphere shaping (HCSS) is discussed in detail, which internally uses Huffman coding to determine the composition to be used and relies on conventional CCD...

We show that short-length probabilistic shaping reduces nonlinear interference in optical fiber transmission. SNR improvements of up to 0.8 dB are obtained. The shaping gain vanishes when interleaving is employed and not undone before transmission.

A novel approach based on an artificial neural network (ANN) for lifetime prediction of 1.55 µm InGaAsP MQW-DFB laser diodes is presented. It outperforms the conventional lifetime projection using accelerated aging tests.

We use channel probing to determine the best transponder configurations for spectral services in a long-haul production network. An estimation accuracy better than ±0,7dB in GSNR margin is obtained for lightpaths up to 5738km.

We show that short-length probabilistic shaping reduces nonlinear interference in optical fiber transmission. SNR improvements of up to 0.8 dB are obtained. The shaping gain vanishes when interleaving is employed and not undone before transmission.

The McEliece cryptosystem isoneof the public-key cryptosystems that do not have known vulnerabilities to attacks using quantum computers. However, the McEliece cryptosystem has not been widely used for practical applications due to the large key size. We present an authenticated key exchange protocol based on the McEliece cryptosystem. We show that...

We assess the gains in achievable information rate for 64-GBd PDM-64QAM signal transmission with Volterra-based digital predistortion of nonlinear transmitter components and show an improvement of up to 0.6 bit/4D-symbol over conventional linear predistortion

For a future 5G Ethernet-based fronthaul architecture, 100G trunk lines of a transmission distance up to 10 km standard single mode fiber (SSMF) in combination with cheap grey optics to daisy chain cell site network interfaces are a promising cost- and power-efficient solution. For such a scenario, different intensity modulation and direct detect (...

We report on the modeling of silicon photonic IQ-modulators with monolithically co-integrated BiCMOS segmented drivers. The structure is evaluated for coherent inter-DCI applications with symbol rates up to 64GBd and modulation formats up to DP-64QAM.

We report on 112 Gbit/s real-time DMT transmission over up to 60 km, targeted at DCI applications. Chromatic dispersion mitigation by vestigial sideband filtering is compared to the use of dispersion compensating fiber.

We demonstrate 84 Gb/s four-level pulse amplitude modulation (PAM-4) over up to 1.6 km standard single mode fiber (SSMF) using a 20-GHz single mode short cavity vertical cavity surface emitting laser diode (VCSEL) at a transmission wave-length of 1525 nm. Different equalizer approaches including a common feedforward equalizer (FFE), a non-linear Vo...

We report real-time 4x56.26-Gb/s DWDM PAM-4 transmission over 80-km SSMF with novel optical transmitter sub-assembly comprising multi-wavelength quantum-dot laser and silicon ring modulators. Pre-FEC BERs below 1E-4 are achieved after 80-km, allowing error-free operation with HD-FEC.

We establish bandwidth requirements for 64Gbaud coherent transceivers, and show comparisons with commercial device models. Compared to theory, our results suggest OSNR penalties as low as 2.2dB for DP-64QAM and DP-16QAM, and 1.1dB for DP-4QAM.

We explain data center interconnect (DCI) use cases and analyze coherent and direct detect transponder technologies to address current and future data center operator needs. Recent research results and standardization activities will be discussed.