Advanced Modulation Techniques for Flexible Optical Transceivers: The Rate/Reach Tradeoff

This tutorial paper reviews advanced modulation techniques that have been proposed in the literature for the implementation of flexible (or reconfigurable) transceivers, which are fundamental building blocks of next-generation software-defined optical networks. Using a common reference multi-span propagation system scenario, the performance of transceivers employing standard quadrature amplitude modulation with variable-rate forward error correction, probabilistic constellation-shaping, and time-domain hybrid formats is assessed, highlighting the achievable flexibility in terms of continuous tradeoff between transmission rate and distance. The combination of these techniques with sub-carrier multiplexing, which enables an increase of the fiber nonlinearity tolerance thanks to the optimization of the symbol rate per sub-carrier, is also discussed

Spectrally and Energy Efficient Wireless Communications: Signal and System Design, Mathematical Modelling and Optimisation

This thesis explores engineering studies and designs aiming to meeting the requirements of enhancing capacity and energy efficiency for next generation communication networks. Challenges of spectrum scarcity and energy constraints are addressed and new technologies are proposed, analytically investigated and examined. The thesis commences by reviewing studies on spectrally and energy-efficient techniques, with a special focus on non-orthogonal multicarrier modulation, particularly spectrally efficient frequency division multiplexing (SEFDM). Rigorous theoretical and mathematical modelling studies of SEFDM are presented. Moreover, to address the potential application of SEFDM under the 5th generation new radio (5G NR) heterogeneous numerologies, simulation-based studies of SEFDM coexisting with orthogonal frequency division multiplexing (OFDM) are conducted. New signal formats and corresponding transceiver structure are designed, using a Hilbert transform filter pair for shaping pulses. Detailed modelling and numerical investigations show that the proposed signal doubles spectral efficiency without performance degradation, with studies of two signal formats; uncoded narrow-band internet of things (NB-IoT) signals and unframed turbo coded multi-carrier signals. The thesis also considers using constellation shaping techniques and SEFDM for capacity enhancement in 5G system. Probabilistic shaping for SEFDM is proposed and modelled to show both transmission energy reduction and bandwidth saving with advantageous flexibility for data rate adaptation. Expanding on constellation shaping to improve performance further, a comparative study of multidimensional modulation techniques is carried out. A four-dimensional signal, with better noise immunity is investigated, for which metaheuristic optimisation algorithms are studied, developed, and conducted to optimise bit-to-symbol mapping. Finally, a specially designed machine learning technique for signal and system design in physical layer communications is proposed, utilising the application of autoencoder-based end-to-end learning. Multidimensional signal modulation with multidimensional constellation shaping is proposed and optimised by using machine learning techniques, demonstrating significant improvement in spectral and energy efficiencies

Advanced Digital Signal Processing Techniques for High-Speed Optical Links

L'abstract è presente nell'allegato / the abstract is in the attachmen

WDM Based 10.8 Gbps Visible Light Communication with Probabilistic Shaping

In this work, we study probabilistic shaping (PS) for optical wireless communications and apply the technique to wavelength division multiplexing (WDM) based visible light communication (VLC). The performance of the proposed scheme is validated with an experimental demonstration. The experimental set up uses lenses to collimate the light beam for triple LEDs. The system parameters of the WDM based VLC system are then optimised, the channel response measured, and PS based symbols are allocated to the individual orthogonal frequency division multiplexing (OFDM) subcarriers. For the channel conditions under consideration, PS resulted in a near Shannon capacity transmission rate of 10.81 Gb/s. Comparatively, the PS resulted in 25 % higher transmission rate than the widely used adaptive bit-power loading algorithm under the same channel conditions

Neural network-aided receivers for soliton communication impaired by solitonic interaction

In this paper, different neural network-based methods are proposed to improvethe achievable information rate in amplitude-modulated soliton communication systems. The proposed methods use simulated data to learn effective soliton detection by suppressing nonlinear impairments beyond amplifier noise, including intrinsic inter-soliton interaction, Gordon-Haus effect-induced timing jitter, and their combined impact. We first present a comprehensive study of these nonlinear impairments based on numerical simulations. Then, two neural network designs are developed based on a regression network and a classifier. We estimate the achievable information rates of the proposed learning-based soliton detection schemes as well as two modelbased benchmark schemes, including the nonlinear Fourier transform eigenvalue estimation and continuous spectrum-aided eigenvalue estimation schemes. Our results demonstrate that bothlearning-based designs lead to substantial performance gains when compared to the benchmark schemes. Importantly, we highlight that exploiting the channel memory, introduced by solitonic interactions, can yield additional gains in the achievable information rate. Through a comparative analysis of the two neural network designs, we establish that the classifier design exhibits superioradaptability to interaction impairment and is more suitable for symbol detection tasks in the context of the investigated scenarios

End-to-end optimization of coherent optical communications over the split-step Fourier method guided by the nonlinear Fourier transform theory

Optimizing modulation and detection strategies for a given channel is critical to maximize the throughput of a communication system. Such an optimization can be easily carried out analytically for channels that admit closed-form analytical models. However, this task becomes extremely challenging for nonlinear dispersive channels such as the optical fiber. End-to-end optimization through autoencoders (AEs) can be applied to define symbol-to-waveform (modulation) and waveform-to-symbol (detection) mappings, but so far it has been mainly shown for systems relying on approximate channel models. Here, for the first time, we propose an AE scheme applied to the full optical channel described by the nonlinear Schr\{"o}dinger equation (NLSE). Transmitter and receiver are jointly optimized through the split-step Fourier method (SSFM) which accurately models an optical fiber. In this first numerical analysis, the detection is performed by a neural network (NN), whereas the symbol-to-waveform mapping is aided by the nonlinear Fourier transform (NFT) theory in order to simplify and guide the optimization on the modulation side. This proof-of-concept AE scheme is thus benchmarked against a standard NFT-based system and a threefold increase in achievable distance (from 2000 to 6640 km) is demonstrated

Next-generation High-Capacity Communications with High Flexibility, Efficiency, and Reliability

The objective of this dissertation is to address the flexibility, efficiency and reliability in high-capacity heterogeneous communication systems. We will experimentally investigate the shaping techniques, and further extend them to more diverse and complicated scenarios, which result in more flexible systems. The scenarios include 1) entropy allocation scheme under uneven frequency response for multi-carrier system, 2) fiber-free space optics link using unipolar pairwise distribution, and 3) flexible rate passive optical network with a wide range of received optical powers. Next, we perform efficiency analysis in inter-data center and long-haul communications. We will characterize the impact of the laser linewidth, jitter tones, and the flicker noise on coherent systems with different baud rates and fiber lengths through theoretical analysis, simulation, and experimental validation. The trade-off analysis indicates the importance of setting up frequency noise power spectral density masks to qualify the transceiver laser design. Besides efficiency analysis, we will also work on efficient system architecture and algorithm design. We investigate the combined impact of various hardware impairments using proposed simplified DSP schemes in beyond 800G self-homodyne coherent system. The proposed scheme is very promising for next-generation intra-data center applications. On the other hand, to improve the data efficiency of the nonlinearity correction algorithm in broadband communication systems, we leverage the semi-supervised method and Lasso. Experimental results validate that Lasso can reduce the required pilot symbol number by exploiting the sparsity of the tap coefficients. Semi-supervised method can further enhance the system performance without introducing additional overhead. Last but not least, regarding reliability, we propose and experimentally demonstrate an ultra-reliable integrated millimeter wave and free space optics analog radio over fiber system with algorithm design. The multiple-spectra operation shows superior performance in reliability and sensitivity compared to the conventional systems, even in extreme weather conditions and strong burst interference.Ph.D