Digital Signal Processing for Optical Communications and Coherent LiDAR

Internet data traffic within data centre, access and metro networks is experiencing unprecedented growth driven by many data-intensive applications. Significant efforts have been devoted to the design and implementation of low-complexity digital signal processing (DSP) algorithms that are suitable for these short-reach optical links. In this thesis, a novel low-complexity frequency-domain (FD) multiple-input multiple-output (MIMO) equaliser with momentum-based gradient descent algorithm is proposed, capable of mitigating both static and dynamic impairments arising from the optical fibre. The proposed frequency-domain equaliser (FDE) also improves the robustness of the adaptive equaliser against feedback latencies which is the main disadvantage of FD adaptive equalisers under rapid channel variations. The development and maturity of optical fibre communication techniques over the past few decades have also been beneficial to many other fields, especially coherent light detection and ranging (LiDAR) techniques. Many applications of coherent LiDAR are also cost-sensitive, e.g., autonomous vehicles (AVs). Therefore, in this thesis, a low-cost and low-complexity single-photodiode-based coherent LiDAR system is investigated. The receiver sensitivity performance of this receiver architecture is assessed through both simulations and experiments, using two ranging waveforms known as double-sideband (DSB) amplitude-modulated chirp signal and single-sideband (SSB) frequency-modulated continuous-wave (FMCW) signals. Besides, the impact of laser phase noise on the ranging precision when operating within and beyond the laser coherence length is studied. Achievable ranging precision beyond the laser coherence length is quantified

Compensação digital de distorções da fibra em sistemas de comunicação óticos de longa distância

The continuous increase of traffic demand in long-haul communications motivated the network operators to look for receiver side techniques to mitigate the nonlinear effects, resulting from signal-signal and signal-noise interaction, thus pushing the current Capacity boundaries. Machine learning techniques are a very hot-topic with given proofs in the most diverse applications. This dissertation aims to study nonlinear impairments in long-haul coherent optical links and the current state of the art in DSP techniques for impairment mitigation as well as the integration of machine learning strategies in optical networks. Starting with a simplified fiber model only impaired by ASE noise, we studied how to integrate an ANN-based symbol estimator into the signal pipeline, enabling to validate the implementation by matching the theoretical performance. We then moved to nonlinear proof of concept with the incorporation of NLPN in the fiber link. Finally, we evaluated the performance of the estimator under realistic simulations of Single and Multi- Channel links in both SSFM and NZDSF fibers. The obtained results indicate that even though it may be hard to find the best architecture, Nonlinear Symbol Estimator networks have the potential to surpass more conventional DSP strategies.O aumento contínuo de tráfego nas comunicações de longo-alcance motivou os operadores de rede a procurar técnicas do lado do receptor para atenuar os efeitos não lineares resultantes da interacção sinal-sinal e sinal-ruído, alargando assim os limites da capacidade do sistema. As técnicas de aprendizagem-máquina são um tópico em ascenção com provas dadas nas mais diversas aplicações e setores. Esta dissertação visa estudar as principais deficiências nas ligações de longo curso e o actual estado da arte em técnicas de DSP para mitigação das mesmas, bem como a integração de estratégias de aprendizagem-máquina em redes ópticas. Começando com um modelo simplificado de fibra apenas perturbado pelo ruído ASE, estudámos como integrar um estimador de símbolos baseado em ANN na cadeia do prodessamento de sinal, conseguindo igualar o desempenho teórico. Procedemos com uma prova de conceito perante não linearidades com a incorporação do ruído de fase não linear na propagação. Finalmente, avaliamos o desempenho do estimador com simulações realistas de links Single e Multi canal tanto em fibras SSFM como NZDSF. Os resultados obtidos indicam que apesar da dificuldade de encontrar a melhor arquitectura, a estimação não linear baseada em redes neuronais têm o potencial para ultrapassar estratégias DSP mais convencionais.Mestrado em Engenharia Eletrónica e Telecomunicaçõe

Visible Light Communication (VLC)

Visible light communication (VLC) using light-emitting diodes (LEDs) or laser diodes (LDs) has been envisioned as one of the key enabling technologies for 6G and Internet of Things (IoT) systems, owing to its appealing advantages, including abundant and unregulated spectrum resources, no electromagnetic interference (EMI) radiation and high security. However, despite its many advantages, VLC faces several technical challenges, such as the limited bandwidth and severe nonlinearity of opto-electronic devices, link blockage and user mobility. Therefore, significant efforts are needed from the global VLC community to develop VLC technology further. This Special Issue, “Visible Light Communication (VLC)”, provides an opportunity for global researchers to share their new ideas and cutting-edge techniques to address the above-mentioned challenges. The 16 papers published in this Special Issue represent the fascinating progress of VLC in various contexts, including general indoor and underwater scenarios, and the emerging application of machine learning/artificial intelligence (ML/AI) techniques in VLC

Chip-scale optical frequency comb sources for terabit communications

The number of devices connected to the internet and the required data transmission speeds are increasing exponentially. To keep up with this trend, data center interconnects should scale up to provide multi-Tbit/s connectivity. With typical distances from a few kilometers to 100 km, these links require the use of a high number of WDM channels. The associated transceivers should have low cost and footprint. The scalability of the number of channels, however, is still limited by the lack of adequate optical sources. In this book, we investigate novel chip-scale frequency comb generators as multi-wavelength light sources in WDM links. With a holistic model, we estimate the performance of comb-based WDM links, and we compare the transmission performance of different comb generator types, namely a quantum-dash mode-locked laser diode and a microresonator-based Kerr comb generator. We characterize their potential for massively-parallel WDM transmission with various transmission experiments. Combined with photonic integrated circuits, these comb sources offer a path towards highly scalable, compact, and energy-efficient Tbit/s transceivers

Chip-scale optical frequency comb sources for terabit communications

To keep up with the ever-increasing data transmission speed needs, data center interconnects are scaling up to provide multi-Tbit/s connectivity. These links require a high number of WDM channels, while the associated transceivers should be compact and energy efficient. Scaling the number of channels, however, is still limited by the lack of adequate optical sources. In this book, we investigate novel chip-scale frequency comb generators as multi-wavelength light sources for Tbit/s WDM links

Chip-scale optical frequency comb sources for terabit communications

To keep up with the ever-increasing data transmission speed needs, data center interconnects are scaling up to provide multi-Tbit/s connectivity. These links require a high number of WDM channels, while the associated transceivers should be compact and energy efficient. Scaling the number of channels, however, is still limited by the lack of adequate optical sources. In this book, we investigate novel chip-scale frequency comb generators as multi-wavelength light sources for Tbit/s WDM links

Signal Design and Machine Learning Assisted Nonlinearity Compensation for Coherent Optical Fibre Communication Links

This thesis investigates low-complexity digital signal processing (DSP) for signal design and nonlinearity compensation strategies to improve the performance of single-mode optical fibre links over different distance scales. The performance of a novel ML-assisted inverse regular perturbation technique that mitigates fibre nonlinearities was investigated numerically with a dual-polarization 64 quadrature amplitude modulation (QAM) link over 800 km distance. The model outperformed the heuristically-optimised digital backpropagation approach with <5 steps per span and mitigated the gain expansion issue, which limits the accuracy of an untrained model when the balance between the nonlinear and linear components becomes considerable. For short reach links, the phase noise due to low-cost, high-linewidth lasers is a more significant channel impairment. A novel constellation optimisation algorithm was, therefore, proposed to design modulation formats that are robust against both additive white Gaussian noise (AWGN) and the residual laser phase noise (i.e., after carrier phase estimation). Subsequently, these constellations were numerically validated in the context of a 400ZR standard system, and achieved up to 1.2 dB gains in comparison with the modulation formats which were optimised only for the AWGN channel. The thesis concludes by examining a joint strategy to modulate and demodulate signals in a partially-coherent AWGN (PCAWGN) channel. With a low-complexity PCAWGN demapper, 8- to 64-ary modulation formats were designed and validated through numerical simulations. The bit-wise achievable information rates (AIR) and post forward error correction (FEC) bit error rates (BER) of the designed constellations were numerically validated with: the theoretically optimum, Euclidean (conventional), and low-complexity PCAWGN demappers. The resulting constellations demonstrated post-FEC BER shaping gains of up to 2.59 dB and 2.19 dB versus uniform 64 QAM and 64-ary constellations shaped for the purely AWGN channel model, respectively. The described geometric shaping strategies can be used to either relax linewidth and/or carrier phase estimator requirements, or to increase signal-to-noise ratio (SNR) tolerance of a system in the presence of residual phase noise