Frigöra full fiberoptisk kapacitet

Forskningsprojekt, 2019 – 2024

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Relaterade styrkeområden och infrastruktur

Hållbar utveckling

Drivkrafter

Publikationer

Superefficient microcombs at the wafer level

Machine learning opportunities for integrated polarization sensing and communication in optical fibers

Inter-Channel Interference Cancellation for Long-Haul Superchannel System

Advanced Digital Signal Processing for High Spectral Efficiency Multidimensional Transmission

12.2 bit/s/Hz C-band Transmission with High-Gain Low-Complexity 24-Dimensional Geometric Shaping

Efficient microresonator frequency combs

Characterisation and Modeling of Coupled-Core Optical Fibers

Phase Noise and Polarization Effects in Fiber-Optic Communication Systems: Modeling, Compensation, Capacity, and Sensing

Dynamic Model for Coupled-Core Fibers

Learning to Extract Distributed Polarization Sensing Data from Noisy Jones Matrices

Corrections to “Power-Efficient Voronoi Constellations for Fiber-Optic Communication Systems”

Autoencoders for Physical-Layer Communications: Approaches and Applications

Blind Frequency-Domain Equalization Using Vector-Quantized Variational Autoencoders

Wafer-level processing of ultralow-loss Si3N4

Physical Realizations of Multidimensional Voronoi Constellations in Optical Communication Systems

End-to-End Learning for VCSEL-based Optical Interconnects: State-of-the-Art, Challenges, and Opportunities

Voronoi Constellations for Coherent Fiber-Optic Communication Systems

Blind Frequency-Domain Equalization Using Vector-Quantized Variational Autoencoders

Pilot distributions for phase noise estimation in electro-optic frequency comb systems

Analysis of the scalar and vector random coupling models for a four coupled-core fiber

Power-Efficient Voronoi Constellations for Fiber-Optic Communication Systems

Data preprocessing for machine-learning-based adaptive data center transmission

Improved Polarization Tracking in the Presence of PDL

Low-Complexity Voronoi Shaping for the Gaussian Channel

Characterisation of Optical Fibers Using Dual-Comb Swept-Wavelength Interferometry

Comparison of Physical Realizations of Multidimensional Voronoi Constellations in Single Mode Fibers

Capacity Bounds under Imperfect Polarization Tracking

Experimental Demonstration of Learned Pulse Shaping Filter for Superchannels

Model-Based End-to-End Learning for WDM Systems With Transceiver Hardware Impairments

Polarization Tracking in the Presence of PDL and Fast Temporal Drift

Periodicity-Enabled Size Reduction of Symbol Based Predistortion for High-Order QAM

Data-Driven Estimation of Capacity Upper Bounds

Multidimensional Constellation Shaping for Coherent Optical Communication Systems

Benchmarking and Interpreting End-to-end Learning of MIMO and Multi-User Communication

Performance Prediction Recipes for Optical Links

Characterisation of a Coupled-Core Fiber Using Dual-Comb Swept-Wavelength Interferometry

Symbol-Based Supervised Learning Predistortion for Compensating Transmitter Nonlinearity

End-to-end Autoencoder for Superchannel Transceivers with Hardware Impairments

Over-the-fiber Digital Predistortion Using Reinforcement Learning

Dual-Comb Swept Wavelength Interferometry

Optimization of Transmitter-Side Signal Rotations in the Presence of Laser Phase Noise

Joint Superchannel Digital Signal Processing for Effective Inter-Channel Interference Cancellation

Compensation of Laser Phase Noise Using DSP in Multichannel Fiber-Optic Communications

General QoS-Aware Scheduling Procedure for Passive Optical Networks

Learning Physical-Layer Communication with Quantized Feedback

Pilot Distributions for Joint-Channel Carrier-Phase Estimation in Multichannel Optical Communications

Look-up Table based Pre-distortion for Transmitters Employing High-Spectral-Efficiency Modulation Formats

Benchmarking End-to-end Learning of MIMO Physical-Layer Communication

On the Impact of Intercore Skew on Joint-Core Carrier-Phase Estimation

On the Performance of Joint-Core Carrier-Phase Estimation in the Presence of Intercore Skew

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