7 research outputs found

    Training Symbol-Based Equalization for Quadrature Duobinary PDM-FTN Systems

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    A training symbol-based equalization algorithm is proposed for polarization de-multiplexing in quadrature duobinary (QDB) modulated polarization division multiplexedfaster-than-Nyquist (FTN) coherent optical systems. The proposed algorithm is based on the least mean square algorithm, and multiple location candidates of a symbol are considered in order to make use of the training symbols with QDB modulation.Results show that an excellent convergence performance is obtained using the proposed algorithm under different polarization alignment scenarios. The optical signal-to-noise ratio required to attain a bit error rate of 2*10-2 is reduced by 1.7 and 1.8 dB using the proposed algorithm, compared to systems using the constant modulus algorithm with differential coding for 4-ary quadrature amplitude modulation(4-QAM) and 16-QAM systems with symbol-by-symbol detection, respectively.Furthermore, comparisons with the Tomlinson-Harashima precoding-based FTN systems illustrate that QDB is preferable when 4-QAM is utilized

    A survey on fiber nonlinearity compensation for 400 Gbps and beyond optical communication systems

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    Optical communication systems represent the backbone of modern communication networks. Since their deployment, different fiber technologies have been used to deal with optical fiber impairments such as dispersion-shifted fibers and dispersion-compensation fibers. In recent years, thanks to the introduction of coherent detection based systems, fiber impairments can be mitigated using digital signal processing (DSP) algorithms. Coherent systems are used in the current 100 Gbps wavelength-division multiplexing (WDM) standard technology. They allow the increase of spectral efficiency by using multi-level modulation formats, and are combined with DSP techniques to combat the linear fiber distortions. In addition to linear impairments, the next generation 400 Gbps/1 Tbps WDM systems are also more affected by the fiber nonlinearity due to the Kerr effect. At high input power, the fiber nonlinear effects become more important and their compensation is required to improve the transmission performance. Several approaches have been proposed to deal with the fiber nonlinearity. In this paper, after a brief description of the Kerr-induced nonlinear effects, a survey on the fiber nonlinearity compensation (NLC) techniques is provided. We focus on the well-known NLC techniques and discuss their performance, as well as their implementation and complexity. An extension of the inter-subcarrier nonlinear interference canceler approach is also proposed. A performance evaluation of the well-known NLC techniques and the proposed approach is provided in the context of Nyquist and super-Nyquist superchannel systems.Comment: Accepted in the IEEE Communications Surveys and Tutorial

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

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    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

    Bandwidth Compressed Waveform and System Design for Wireless and Optical Communications: Theory and Practice

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    This thesis addresses theoretical and practical challenges of spectrally efficient frequency division multiplexing (SEFDM) systems in both wireless and optical domains. SEFDM improves spectral efficiency relative to the well-known orthogonal frequency division multiplexing (OFDM) by non-orthogonally multiplexing overlapped sub-carriers. However, the deliberate violation of orthogonality results in inter carrier interference (ICI) and associated detection complexity, thus posing many challenges to practical implementations. This thesis will present solutions for these issues. The thesis commences with the fundamentals by presenting the existing challenges of SEFDM, which are subsequently solved by proposed transceivers. An iterative detection (ID) detector iteratively removes self-created ICI. Following that, a hybrid ID together with fixed sphere decoding (FSD) shows an optimised performance/complexity trade-off. A complexity reduced Block-SEFDM can subdivide the signal detection into several blocks. Finally, a coded Turbo-SEFDM is proved to be an efficient technique that is compatible with the existing mobile standards. The thesis also reports the design and development of wireless and optical practical systems. In the optical domain, given the same spectral efficiency, a low-order modulation scheme is proved to have a better bit error rate (BER) performance when replacing a higher order one. In the wireless domain, an experimental testbed utilizing the LTE-Advanced carrier aggregation (CA) with SEFDM is operated in a realistic radio frequency (RF) environment. Experimental results show that 40% higher data rate can be achieved without extra spectrum occupation. Additionally, a new waveform, termed Nyquist-SEFDM, which compresses bandwidth and suppresses out-of-band power leakage is investigated. A 4th generation (4G) and 5th generation (5G) coexistence experiment is followed to verify its feasibility. Furthermore, a 60 GHz SEFDM testbed is designed and built in a point-to-point indoor fiber wireless experiment showing 67% data rate improvement compared to OFDM. Finally, to meet the requirements of future networks, two simplified SEFDM transceivers are designed together with application scenarios and experimental verifications

    Optics for AI and AI for Optics

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    Artificial intelligence is deeply involved in our daily lives via reinforcing the digital transformation of modern economies and infrastructure. It relies on powerful computing clusters, which face bottlenecks of power consumption for both data transmission and intensive computing. Meanwhile, optics (especially optical communications, which underpin today’s telecommunications) is penetrating short-reach connections down to the chip level, thus meeting with AI technology and creating numerous opportunities. This book is about the marriage of optics and AI and how each part can benefit from the other. Optics facilitates on-chip neural networks based on fast optical computing and energy-efficient interconnects and communications. On the other hand, AI enables efficient tools to address the challenges of today’s optical communication networks, which behave in an increasingly complex manner. The book collects contributions from pioneering researchers from both academy and industry to discuss the challenges and solutions in each of the respective fields

    Anwendung von maschinellem Lernen in der optischen NachrichtenĂĽbertragungstechnik

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    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
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