Advanced DSP Techniques for High-Capacity and Energy-Efficient Optical Fiber Communications

The rapid proliferation of the Internet has been driving communication networks closer and closer to their limits, while available bandwidth is disappearing due to an ever-increasing network load. Over the past decade, optical fiber communication technology has increased per fiber data rate from 10 Tb/s to exceeding 10 Pb/s. The major explosion came after the maturity of coherent detection and advanced digital signal processing (DSP). DSP has played a critical role in accommodating channel impairments mitigation, enabling advanced modulation formats for spectral efficiency transmission and realizing flexible bandwidth. This book aims to explore novel, advanced DSP techniques to enable multi-Tb/s/channel optical transmission to address pressing bandwidth and power-efficiency demands. It provides state-of-the-art advances and future perspectives of DSP as well

Anwendung von maschinellem Lernen in der optischen Nachrichtenübertragungstechnik

Aufgrund des zunehmenden Datenverkehrs wird erwartet, dass die optischen Netze zukünftig mit höheren Systemkapazitäten betrieben werden. Dazu wird bspw. die kohärente Übertragung eingesetzt, bei der das Modulationsformat erhöht werden kann, erforder jedoch ein größeres SNR. Um dies zu erreichen, wird die optische Signalleistung erhöht, wodurch die Datenübertragung durch die nichtlinearen Beeinträchtigungen gestört wird. Der Schwerpunkt dieser Arbeit liegt auf der Entwicklung von Modellen des maschinellen Lernens, die auf diese nichtlineare Signalverschlechterung reagieren. Es wird die Support-Vector-Machine (SVM) implementiert und als klassifizierende Entscheidungsmaschine verwendet. Die Ergebnisse zeigen, dass die SVM eine verbesserte Kompensation sowohl der nichtlinearen Fasereffekte als auch der Verzerrungen der optischen Systemkomponenten ermöglicht. Das Prinzip von EONs bietet eine Technologie zur effizienten Nutzung der verfügbaren Ressourcen, die von der optischen Faser bereitgestellt werden. Ein Schlüsselelement der Technologie ist der bandbreitenvariable Transponder, der bspw. die Anpassung des Modulationsformats oder des Codierungsschemas an die aktuellen Verbindungsbedingungen ermöglicht. Um eine optimale Ressourcenauslastung zu gewährleisten wird der Einsatz von Algorithmen des Reinforcement Learnings untersucht. Die Ergebnisse zeigen, dass der RL-Algorithmus in der Lage ist, sich an unbekannte Link-Bedingungen anzupassen, während vergleichbare heuristische Ansätze wie der genetische Algorithmus für jedes Szenario neu trainiert werden müssen

Impact of Analog and Digital Pre-emphasis on the Signal-to-Noise Ratio of Bandwidth-limited Optical Transceivers

The ever-growing machine-to-machine traffic in data centers has stimulated the increase of transceiver data rate from 25Gb/s/λ to 100Gb/s/λ and beyond. It is believed that advanced modulation formats and digital-to-analog converters (DACs) will be employed in next generation short-reach transceivers. Digital pre-emphasis techniques are widely employed in DAC-based transceivers to compensate for the high frequency roll-off due to the RF and optoelectronics components in optical transceivers. However, digital pre-emphasis essentially reduces the magnitude of the signal low frequency components for a flat frequency response, which unavoidably increases quantization error, reducing the overall signal-to-noise ratio. This trade-off between SNR and bandwidth conflicts with the high SNR requirement of advanced modulation formats such as the Nyquist-shaped pulse amplitude modulation (PAM). To mitigate the quantization error induced SNR degradation, we show that analog pre-emphasis filters can be used in conjunction with digital pre-emphasis for improved system performance. To understand the impact of the analog pre-emphasis filter on system performance, we analyze the relationship between the flatness of the system frequency response and the SNR degradation due to digital pre-emphasis, and demonstrate 1.1-dB increase of receiver sensitivities, for both 64-Gb/s and 128-Gb/s intensity-modulation direct detection (IM-DD) 20 PAM4 signals, respectively employing a directly modulated laser (DML) and an electroabsorption modulator (EAM)

Split-enabled 350–630 Gb/s optical interconnect with direct detection NOMA-CAP and 7-core multi-core fiber

The ever-growing data traffic volume inside data centers caused by the popularization of cloud services and edge computing demands scalable and cost-efficient network infrastructures. With this premise, optical interconnects have recently gained more and more research attention as a key building block to ensure end-to-end energy efficient solutions, offering high throughput, low latency and reduced energy consumption compared to current networks based on active optical cables. An efficient way for performing such optical interconnects is to make use of multi-core fibers (MCFs), which enables the multiplexing of several spatial channels, each using a different core inside the same fiber cladding. Moreover, non-orthogonal multiple access combined with multi-band carrierless amplitude and phase modulation (NOMA-CAP) has been recently proposed as a potential candidate to increase the network capacity and an efficiency/flexibility resource management. In this paper, using direct detection we experimentally demonstrate the transmission of NOMA-CAP signals through a 2 km MCF with 7 spatial channels for high capacity optical interconnect applications. The results show negligible transmission penalty for different total aggregated traffics ranging from 350 Gb/s to 630 Gb/s.This work was supported in part by ALLIANCE (TEC2017-90034-C2-2-R) project co-funded by FEDER, the European Union’s Horizon 2020 research and innovation programme under grant agreement no780997 (plaCMOS), as well as MINECO FPI-BES-2015-074302Peer ReviewedPostprint (author's final draft

Performance limits in optical communications due to fiber nonlinearity

In this paper, we review the historical evolution of predictions of the performance of optical communication systems. We will describe how such predictions were made from the outset of research in laser based optical communications and how they have evolved to their present form, accurately predicting the performance of coherently detected communication systems