Advanced digital signal processing for coherent optical OFDM transmissions

Coherent optical orthogonal frequency division multiplexing (CO-OFDM) has been actively considered as a potential candidate for long-haul transmission and 400 Gb/s to 1 Tb/s Ethernet transport because of its high spectral efficiency, efficient implementation, flexibility and robustness against linear impairments such as chromatic dispersion and polarization mode dispersion. However, due to the long symbol duration and narrow subcarrier spacing, CO-OFDM systems are sensitive to laser phase noise and fibre nonlinearity induced penalties. As a result, the development of CO-OFDM transmission technology crucially relies on efficient techniques to compensate for the laser phase noise and fibre nonlinearity impairments. In this thesis, high performance and low complexity digital signal processing techniques for laser phase noise and fibre nonlinearity compensation in CO-OFDM transmissions are demonstrated. For laser phase noise compensation, three novel techniques, namely quasipilot-aided, decision-directed-free blind and multiplier-free blind are introduced. For fibre nonlinear compensation, two novel techniques which are referred to as phase conjugated pilots and phase conjugated subcarrier coding, are proposed. All these abovementioned digital signal processing techniques offer high performances and flexibilities while requiring relatively low complexities in comparison with other existing phase noise and nonlinear compensation techniques. As a result of the developments of these digital signal processing techniques, CO-OFDM technology is expected to play a significant role in future ultra-high capacity optical network. In addition, this thesis also presents preliminary study on nonlinear Fourier transform based transmission schemes in which OFDM is a highly suitable modulation format. The obtained result paves the way towards a truly flexible nonlinear wave-division multiplexing system that allows the current nonlinear transmission limitations to be exceeded.

Periodic polymer photonic bandgap structures for on-chip optical cavities

Integrated on-chip optical platforms enable high performance in applications of high-speed all-optical or electro-optical switching, wide-range multi-wavelength on-chip lasing for communication, and lab-on-chip optical sensing. Integrated optical resonators with high quality factor are a fundamental component in these applications. Periodic photonic structures (photonic crystals) exhibit a photonic band gap, which can be used to manipulate photons in a way similar to the control of electrons in semiconductor circuits. This makes it possible to create structures with radically improved optical properties. Compared to silicon, polymers offer a potentially inexpensive material platform with ease of fabrication at low temperatures and a wide range of material properties when doped with nanocrystals and other molecules. In this research work, several polymer periodic photonic structures are proposed and investigated to improve optical confinement and optical sensing. We developed a fast numerical method for calculating the quality factor of a photonic crystal slab (PhCS) cavity. The calculation is implemented via a 2D-FDTD method followed by a post-process for cavity surface energy radiation loss. Computational time is saved and good accuracy is demonstrated compared to other published methods. Also, we proposed a novel concept of slot-PhCS which enhanced the energy density 20 times compared to traditional PhCS. It combines both advantages of the slot waveguide and photonic crystal to localize the high energy density in the low index material. This property could increase the interaction between light and material embedded with nanoparticles like quantum dots for active device development. We also demonstrated a wide range bandgap based on a one dimensional waveguide distributed Bragg reflector with high coupling to optical waveguides enabling it to be easily integrated with other optical components on the chip. A flexible polymer (SU8) grating waveguide is proposed as a force sensor. The proposed sensor can monitor nN range forces through its spectral shift. Finally, quantum dot - doped SU8 polymer structures are demonstrated by optimizing spin coating and UV exposure. Clear patterns with high emission spectra proved the compatibility of the fabrication process for applications in optical amplification and lasing.

Suppression of nonlinear distortion in few-mode fibres using strong mode coupling

In this paper, we investigate the impact of linear mode coupling on the efficiency of intermodal four-wave mixing and on the group delay statistics in few-mode fibres. The investigation will include not only the weak or strong linear coupling regimes, but also the transition region between them, the intermediate coupling regime. This analysis will allow to assess the level of coupling strength require to suppress the nonlinear distortion in a few-mode fibre below the level of distortion for single-mode propagation without mode coupling.

Constructing eigenmode excitation spectrum in synthetic photonic lattices using optical heterodyning

A method based on optical heterodyning is proposed for measuring relative optical phases of pulses circulating in a synthetic photonic lattices. The knowledge of the phases can be further used for qualitative reconstruction of an eigenmode excitation spectrum in the synthetic photonic lattice.

Temporal scaling of optical rogue waves in unidirectional ring fiber laser

A fiber mode-lock laser allows generation of the optical rogue wave (ORW) at different time scales. The criteria for distinguishing between them is a comparison of the event lifetime with the main characteristic time of the system. The characteristic time can be estimated from the decay of an autocorrelation function (AF). Thus, in comparison with AF characteristic time, fast optical rogue wave (FORW) events have duration less than the AF decay time and it appeared due to pulse-pulse interaction and nonlinear pulses dynamics. While slow optical rogue wave (SORW) have a duration much more longer than the decay time of the AF which it papered due to hopping between different attractors. Switching between regimes can be managed by change the artificial birefringence that induced in a laser cavity. For understanding the role playing by the periodical amplification and the resonator, we have performed an unidirectional fiber laser experiments without a saturable absorber. This laser experiment allowed to generate of most of the RW patterns which were either observed experimentally or predicted theoretically. In this way, we have observed the generation of an FORW along with SORW under similar conditions. Most of the patterns were found to be mutually exclusive which means that only one RW mechanism was realized in each regime of generation.

Enhanced nonlinear spectral compression in fiber by external sinusoidal phase modulation

We propose a new, simple approach to enhance the spectral compression process arising from nonlinear pulse propagation in an optical fiber. We numerically show that an additional sinusoidal temporal phase modulation of the pulse enables efficient reduction of the intensity level of the side lobes in the spectrum that are produced by the mismatch between the initial linear negative chirp of the pulse and the self-phase modulation-induced nonlinear positive chirp. Remarkable increase of both the extent of spectrum narrowing and the quality of the compressed spectrum is afforded by the proposed approach across a wide range of experimentally accessible parameters.

Enhanced nonlinear spectral compression in fibre by sinusoidal phase modulation

We propose a simple approach to enhance the spectral compression arising from nonlinear pulse propagation in a Kerr medium. We numerically show that an additional sinusoidal temporal phase modulation enables efficient reduction of the intensity level of spectral side lobes.

Nonlinear distortion in mode delay compensated few-mode fibre spans with intermediate coupling

Nonlinear distortion in delay-compensated spans for intermediate coupling is studied for the first time. Coupling strengths under -30dB/100m allow distortion reduction using shorter compensation lengths and higher delays. For higher coupling strengths no significant penalty results from shorter compensation lengths.

Periodic nonlinear Fourier transform for fiber-optic communications, Part I:theory and numerical methods

In this work, we introduce the periodic nonlinear Fourier transform (PNFT) method as an alternative and efficacious tool for compensation of the nonlinear transmission effects in optical fiber links. In the Part I, we introduce the algorithmic platform of the technique, describing in details the direct and inverse PNFT operations, also known as the inverse scattering transform for periodic (in time variable) nonlinear Schrödinger equation (NLSE). We pay a special attention to explaining the potential advantages of the PNFT-based processing over the previously studied nonlinear Fourier transform (NFT) based methods. Further, we elucidate the issue of the numerical PNFT computation: we compare the performance of four known numerical methods applicable for the calculation of nonlinear spectral data (the direct PNFT), in particular, taking the main spectrum (utilized further in Part II for the modulation and transmission) associated with some simple example waveforms as the quality indicator for each method. We show that the Ablowitz-Ladik discretization approach for the direct PNFT provides the best performance in terms of the accuracy and computational time consumption.

Periodic nonlinear Fourier transform for fiber-optic communications, Part II:eigenvalue communication

In this paper we propose the design of communication systems based on using periodic nonlinear Fourier transform (PNFT), following the introduction of the method in the Part I. We show that the famous "eigenvalue communication" idea [A. Hasegawa and T. Nyu, J. Lightwave Technol. 11, 395 (1993)] can also be generalized for the PNFT application: In this case, the main spectrum attributed to the PNFT signal decomposition remains constant with the propagation down the optical fiber link. Therefore, the main PNFT spectrum can be encoded with data in the same way as soliton eigenvalues in the original proposal. The results are presented in terms of the bit-error rate (BER) values for different modulation techniques and different constellation sizes vs. the propagation distance, showing a good potential of the technique.

Experimental comparison of artificial neural network and volterra based nonlinear equalization for CO-OFDM

A novel artificial neural network (ANN)-based nonlinear equalizer (NLE) of low complexity is demonstrated for 40-Gb/s CO-OFDM at 2000 km, revealing ∼1.5 dB enhancement in Q-factor compared to inverse Volterra-series transfer function based NLE.

Nonlinear soil-structure interaction for buried pressure pipes under differential ground motion

Pipelines extend thousands of kilometers across wide geographic areas as a network to provide essential services for modern life. It is inevitable that pipelines must pass through unfavorable ground conditions, which are susceptible to natural disasters. This thesis investigates the behaviour of buried pressure pipelines experiencing ground distortions induced by normal faulting. A recent large database of physical modelling observations on buried pipes of different stiffness relative to the surrounding soil subjected to normal faults provided a unique opportunity to calibrate numerical tools. Three-dimensional finite element models were developed to enable the complex soil-structure interaction phenomena to be further understood, especially on the subjects of gap formation beneath the pipe and the trench effect associated with the interaction between backfill and native soils. Benchmarked numerical tools were then used to perform parametric analysis regarding project geometry, backfill material, relative pipe-soil stiffness and pipe diameter. Seismic loading produces a soil displacement profile that can be expressed by isoil, the distance between the peak curvature and the point of contraflexure. A simplified design framework based on this length scale (i.e., the Kappa method) was developed, which features estimates of longitudinal bending moments of buried pipes using a characteristic length, ipipe, the distance from peak to zero curvature. Recent studies indicated that empirical soil springs that were calibrated against rigid pipes are not suitable for analyzing flexible pipes, since they lead to excessive conservatism (for design). A large-scale split-box normal fault simulator was therefore assembled to produce experimental data for flexible PVC pipe responses to a normal fault. Digital image correlation (DIC) was employed to analyze the soil displacement field, and both optical fibres and conventional strain gauges were used to measure pipe strains. A refinement to the Kappa method was introduced to enable the calculation of axial strains as a function of pipe elongation induced by flexure and an approximation of the longitudinal ground deformations. A closed-form Winkler solution of flexural response was also derived to account for the distributed normal fault pattern. Finally, these two analytical solutions were evaluated against the pipe responses observed in the large-scale laboratory tests.

A Generalized Fuzzy Linguistic Model for Predicting Component Concentrations in an Optical Gas Sensing System

Motivated by environmental protection concerns, monitoring the flue gas of thermal power plant is now often mandatory due to the need to ensure that emission levels stay within safe limits. Optical based gas sensing systems are increasingly employed for this purpose, with regression techniques used to relate gas optical absorption spectra to the concentrations of specific gas components of interest (NOx, SO2 etc.). Accurately predicting gas concentrations from absorption spectra remains a challenging problem due to the presence of nonlinearities in the relationships and the high-dimensional and correlated nature of the spectral data. This article proposes a generalized fuzzy linguistic model (GFLM) to address this challenge. The GFLM is made up of a series of “If-Then” fuzzy rules. The absorption spectra are input variables in the rule antecedent. The rule consequent is a general nonlinear polynomial function of the absorption spectra. Model parameters are estimated using least squares and gradient descent optimization algorithms. The performance of GFLM is compared with other traditional prediction models, such as partial least squares, support vector machines, multilayer perceptron neural networks and radial basis function networks, for two real flue gas spectral datasets: one from a coal-fired power plant and one from a gas-fired power plant. The experimental results show that the generalized fuzzy linguistic model has good predictive ability, and is competitive with alternative approaches, while having the added advantage of providing an interpretable model.

A generalized fuzzy linguistic model for predicting component concentrations in an optical gas sensing system

Motivated by environmental protection concerns, monitoring the flue gas of thermal power plant is now often mandatory due to the need to ensure that emission levels stay within safe limits. Optical based gas sensing systems are increasingly employed for this purpose, with regression techniques used to relate gas optical absorption spectra to the concentrations of specific gas components of interest (NO_x, SO₂ etc.). Accurately predicting gas concentrations from absorption spectra remains a challenging problem due to the presence of nonlinearities in the relationships and the high-dimensional and correlated nature of the spectral data. This article proposes a generalized fuzzy linguistic model (GFLM) to address this challenge. The GFLM is made up of a series of “If-Then” fuzzy rules. The absorption spectra are input variables in the rule antecedent. The rule consequent is a general nonlinear polynomial function of the absorption spectra. Model parameters are estimated using least squares and gradient descent optimization algorithms. The performance of GFLM is compared with other traditional prediction models, such as partial least squares, support vector machines, multilayer perceptron neural networks and radial basis function networks, for two real flue gas spectral datasets: one from a coal-fired power plant and one from a gas-fired power plant. The experimental results show that the generalized fuzzy linguistic model has good predictive ability, and is competitive with alternative approaches, while having the added advantage of providing an interpretable model.

Studies on betanin natural dye incorporated ZnO composites at nano and micro scale for photonic device applications

Green energy and Green technology are the most of the quoted terms in the context of modern science and technology. Technology which is close to nature is the necessity of the modern world which is haunted by global warming and climatic alterations. Proper utilization of solar energy is one of the goals of Green Energy Movement. The present thesis deals with the work carried out in the eld of nanotechnology and its possible use in various applications (employing natural dyes) like solar cells. Unlike arti cial dyes, the natural dyes are available, easy to prepare, low in cost, non-toxic, environmentally friendly and fully biodegradable. Looking to the 21st century, the nano/micro sciences will be a chief contributor to scienti c and technological developments. As nanotechnology progresses and complex nanosystems are fabricated, a growing impetus is being given to the development of multi-functional and size-dependent materials. The control of the morphology, from the nano to the micrometer scales, associated with the incorporation of several functionalities can yield entirely new smart hybrid materials. They are special class of materials which provide a new method for the improvement of the environmental stability of the material with interesting optical properties and opening a land of opportunities for applications in the eld of photonics. Zinc oxide (ZnO) is one such multipurpose material that has been explored for applications in sensing, environmental monitoring, and bio-medical systems and communications technology. Understanding the growth mechanism and tailoring their morphology is essential for the use of ZnO crystals as nano/micro electromechanical systems and also as building blocks of other nanosystems.