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

High Speed Optical Links Using CAP Modulation and Novel Equalisation Techniques

High speed optical links suffer from inter-symbol-interference (ISI) due to their limited bandwidth. Equalisation is typically used to mitigate ISI and therefore improve the link capacity. This dissertation explores novel equalisation techniques for carrierless amplitude and phase (CAP) modulation based optical communication systems including OM4 based and plastic optical fibre (POF) based links. An 850 nm VCSEL based OM4 link using CAP-16 scheme is studied. For the first time, the CAP equaliser, is proposed to mitigate both crosstalk channel interference (CCI) and ISI in the link at the receiver side. Performance comparisons are studied between the CAP-16 scheme using CAP equaliser and a conventional equaliser, pulse amplitude modulation (PAM-4) scheme, and discrete multitone (DMT) scheme. CAP based data transmission of 112 Gb/s is achieved over 150 m OM4 fibre with this novel equaliser, while the conventional equaliser can only support over 1 m OM4 fibre and fails to recover the signals at the same data rate. In addition, this novel equaliser provides a 1.2 dB and 1.7 dB improvement in receiver sensitivity over PAM-4 and DMT schemes, respectively, at 112 Gb/s over 100 m OM4 fibre. A novel pre-CAP-equaliser solving CCI at the transmitter side is also proposed. Data transmission of 56 Gb/s over 100 m OM4 fibre is reported experimentally with an improvement of 0.7 dB in receiver sensitivity compared to using the CAP equaliser at the receiver side. A simulation study shows a 2 dB improvement in receiver sensitivity at 112 Gb/s over 100 m OM4 fibre. Furthermore, an artificial neural network (ANN) equaliser in conjunction with the CAP equaliser structure is explored in a VCSEL based OM4 fibre link in order to further mitigate the nonlinear impairments. For 112 Gb/s data transmission over 100 m OM4 fibre, a 2.4 dB improvement of receiver sensitivity is achieved compared to the CAP equaliser. In addition to the electrical equalisers, a monolithically integrated silicon optical equaliser consisting of three taps is used for 50 Gb/s data transmission. After 10 km standard single mode fibre (SSMF), error free eye diagrams at the receiver are demonstrated. A μLED based POF link based on an APD receiver is also investigated with the CAP equaliser at the receiver side. Data transmission rates of 4 Gb/s over 25 m and 5 Gb/s over 10 m POF links are demonstrated with this equaliser while the conventional equaliser can only support 4 Gb/s over 10 m and fails to recover the signals for 5 Gb/s data transmission

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

Design of neural network-based nonlinear equalisers for coherent optical communication systems

Recent advancements in beyond 5G (B5G) networks and future communications demand ultra-high capacity and, therefore, impose stringent requirements on fibre-optic transmission infrastructures. Optical fibre channel impairments such as nonlinearities induced by the Kerr effect and their interactions with chromatic dispersion pose a significant challenge in achieving desirable transmission capacity in current coherent optical communication systems. Digital signal processing techniques, such as electronic dispersion compensation and digital backpropagation, may achieve suboptimal performance or require impractical high computing resources. Machine learning (ML) techniques offer a promising solution to the optical fibre nonlinearity equalisation problem due to their ability to exploit underlying features among the vast volume of digital information available in modern society. This thesis focuses on the design of nonlinear equalisers using machine learning, specifically neural networks (NNs), for coherent optical communication systems. A comprehensive study of machine learning algorithms, including unsupervised and supervised learning algorithms, applied in nonlinear equalisation is conducted, demonstrating that the bit error rate performance of these algorithms is superior to conventional symbol detection using mean square error. The results demonstrate the potential of machine learning algorithms, particularly NNs, for nonlinearity equalisation in coherent optical systems and provide a motivation for further exploration. The ML- and recurrent neural network (RNN)-based nonlinear equalisers with sequential symbol input are investigated. The results suggest the input sequences can provide relevant residual channel memory information for these equalisers to enhance the system performance after training, offering confidence in the design of low-complexity NN-based equalisers. Furthermore, an attention-aided partial bidirectional recurrent neural network (BRNN)-based nonlinear equaliser is proposed, successfully reducing complexity of ∼56.2% with the assistance of the attention mechanism, which also provides evidence of symbol-wise nonlinear memory. The contributions presented in this thesis demonstrate the potential of machine learning algorithms and NN-based equalisers, investigate and validate the feasibility of sequential input for them, and provide an effective evidence-based pruning process for the design of NN-based equalisers for optical transmission systems. xv

Performance analysis of 2D-OCDMA system in long-reach passive optical network

International audienceIn this paper, a performance analysis is reported for optical code division multiplexing (OCDM) system for long-reach passive optical network (LR-PON) systems by taking into account multiple access interference (MAI), single-mode fiber (SMF) channel effects and receiver noise. The mathematical model representing the 2-D optical code parameters for different receiver structures used in optical code division multiplexing access (OCDMA) are developed, optimized and implemented using Matlab simulations, where channel imperfections, such as attenuation losses and chromatic dispersion have been considered. In the proposed system configuration, we have investigated the probability of error for Back-to-Back (B2B) with conventional correlation receiver (CCR), SMF with CCR receiver and SMF channel with successive interference cancelation (SIC) receiver. Additionally, SMF channel with SIC receiver system performance has been addressed by taking into account two key metrics, such as BER and Q-factor as function of simultaneous users, and fiber length, respectively. We have managed to substantially improve simultaneous multiuser data transmission over significant fiber lengths without use of amplification, where Q-factor of 6 at fiber length of 190 and 120 km, while a SIC receiver using 5 stages cancelation is employed for 2D prime hop system (2D-PHS) and for 2D hybrid codes (2D-HC), respectively

A review of gallium nitride LEDs for multi-gigabit-per-second visible light data communications

The field of visible light communications (VLC) has gained significant interest over the last decade, in both fibre and free-space embodiments. In fibre systems, the availability of low cost plastic optical fibre (POF) that is compatible with visible data communications has been a key enabler. In free-space applications, the availability of hundreds of THz of the unregulated spectrum makes VLC attractive for wireless communications. This paper provides an overview of the recent developments in VLC systems based on gallium nitride (GaN) light-emitting diodes (LEDs), covering aspects from sources to systems. The state-of-the-art technology enabling bandwidth of GaN LEDs in the range of >400 MHz is explored. Furthermore, advances in key technologies, including advanced modulation, equalisation, and multiplexing that have enabled free-space VLC data rates beyond 10 Gb/s are also outlined

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