Optical information capacity processing

The never-stopping increase in demand for information transmission capacity has been met with technological advances in telecommunication systems, such as the implementation of coherent optical systems, advanced multilevel multidimensional modulation formats, fast signal processing, and research into new physical media for signal transmission (e.g. a variety of new types of optical fibers). Since the increase in the signal-to-noise ratio makes fiber communication channels essentially nonlinear (due to the Kerr effect for example), the problem of estimating the Shannon capacity for nonlinear communication channels is not only conceptually interesting, but also practically important. Here we discuss various nonlinear communication channels and review the potential of different optical signal coding, transmission and processing techniques to improve fiber-optic Shannon capacity and to increase the system reach.

Recent developments in all-optical nonlinear data processing

Photonic technologies for data processing in the optical domain are expected to play a major role in future high-speed communications. Nonlinear effects in optical fibres have many attractive features and great, but not yet fully explored potential for optical signal processing. Here we provide an overview of our recent advances in developing novel techniques and approaches to all-optical processing based on fibre nonlinearities.

Fibre-based devices for next generation photonics communication systems

The future broadband information network will undoubtedly integrate the mobility and flexibility of wireless access systems with the huge bandwidth capacity of photonics solutions to enable a communication system capable of handling the anticipated demand for interactive services. Towards wide coverage and low cost implementations of such broadband wireless photonics communication networks, various aspects of the enabling technologies are continuingly generating intense research interest. Among the core technologies, the optical generation and distribution of radio frequency signals over fibres, and the fibre optic signal processing of optical and radio frequency signals, have been the subjects for study in this thesis. Based on the intrinsic properties of single-mode optical fibres, and in conjunction with the concepts of optical fibre delay line filters and fibre Bragg gratings, a number of novel fibre-based devices, potentially suitable for applications in the future wireless photonics communication systems, have been realised. Special single-mode fibres, namely, the high birefringence (Hi-Bi) fibre and the Er/Yb doped fibre have been employed so as to exploit their merits to achieve practical and cost-effective all-fibre architectures. A number of fibre-based complex signal processors for optical and radio frequencies using novel Hi-Bi fibre delay line filter architectures have been illustrated. In particular, operations such as multichannel flattop bandpass filtering, simultaneous complementary outputs and bidirectional nonreciprocal wavelength interleaving, have been demonstrated. The proposed configurations featured greatly reduced environmental sensitivity typical of coherent fibre delay line filter schemes, reconfigurable transfer functions, negligible chromatic dispersions, and ease of implementation, not easily achievable based on other techniques. A number of unique fibre grating devices for signal filtering and fibre laser applications have been realised. The concept of the superimposed fibre Bragg gratings has been extended to non-uniform grating structures and into Hi-Bi fibres to achieve highly useful grating devices such as overwritten phase-shifted fibre grating structure and widely/narrowly spaced polarization-discriminating filters that are not limited by the intrinsic fibre properties. In terms of the-fibre-based optical millimetre wave transmitters, unique approaches based on fibre laser configurations have been proposed and demonstrated. The ability of the dual-mode distributed feedback (DFB) fibre lasers to generate high spectral purity, narrow linewidth heterodyne signals without complex feedback mechanisms has been illustrated. A novel co-located dual DFB fibre laser configuration, based on the proposed superimposed phase-shifted fibre grating structure, has been further realised with highly desired operation characteristics without the need for costly high frequency synthesizers and complex feedback controls. Lastly, a novel cavity mode condition monitoring and optimisation scheme for short length, linear-cavity fibre lasers has been proposed and achieved. Based on the concept and simplicity of the superimposed fibre laser cavities structure, in conjunction with feedback controls, enhanced output performances from the fibre lasers have been achieved. The importance of such cavity mode assessment and feedback control for optimised fibre laser output performance has been illustrated.

Recent advances in fibre grating devices and their sensing applications

Over the last twenty years, we have been continuously seeing R&D efforts and activities in developing optical fibre grating devices and technologies and exploring their applications for telecommunications, optical signal processing and smart sensing, and recently for medical care and biophotonics. In addition, we have also witnessed successful commercialisation of these R&Ds, especially in the area of fibre Bragg grating (FBG) based distributed sensor network systems and technologies for engineering structure monitoring in industrial sectors such as oil, energy and civil engineering. Despite countless published reports and papers and commercial realisation, we are still seeing significant and novel research activities in this area. This invited paper will give an overview on recent advances in fibre grating devices and their sensing applications with a focus on novel fibre gratings and their functions and grating structures in speciality fibres. The most recent developments in (i) femtosecond inscription for microfluidic/grating devices, (2) tilted grating based novel polarisation devices and (3) dual-peak long-period grating based DNA hybridisation sensors will be discussed.

Novel hardwired distributive tactile sensing system for medical applications

This thesis described the research carried out on the development of a novel hardwired tactile sensing system tailored for the application of a next generation of surgical robotic and clinical devices, namely a steerable endoscope with tactile feedback, and a surface plate for patient posture and balance. Two case studies are examined. The first is a one-dimensional sensor for the steerable endoscope retrieving shape and ‘touch’ information. The second is a two-dimensional surface which interprets the three-dimensional motion of a contacting moving load. This research can be used to retrieve information from a distributive tactile sensing surface of a different configuration, and can interpret dynamic and static disturbances. This novel approach to sensing has the potential to discriminate contact and palpation in minimal invasive surgery (MIS) tools, and posture and balance in patients. The hardwired technology uses an embedded system based on Field Programmable Gate Arrays (FPGA) as the platform to perform the sensory signal processing part in real time. High speed robust operation is an advantage from this system leading to versatile application involving dynamic real time interpretation as described in this research. In this research the sensory signal processing uses neural networks to derive information from input pattern from the contacting surface. Three neural network architectures namely single, multiple and cascaded were introduced in an attempt to find the optimum solution for discrimination of the contacting outputs. These architectures were modelled and implemented into the FPGA. With the recent introduction of modern digital design flows and synthesis tools that essentially take a high-level sensory processing behaviour specification for a design, fast prototyping of the neural network function can be achieved easily. This thesis outlines the challenge of the implementations and verifications of the performances.

Analysis of magnetoencephaoographic data as a nonlinear dynamical system

This thesis presents the results from an investigation into the merits of analysing Magnetoencephalographic (MEG) data in the context of dynamical systems theory. MEG is the study of both the methods for the measurement of minute magnetic flux variations at the scalp, resulting from neuro-electric activity in the neocortex, as well as the techniques required to process and extract useful information from these measurements. As a result of its unique mode of action - by directly measuring neuronal activity via the resulting magnetic field fluctuations - MEG possesses a number of useful qualities which could potentially make it a powerful addition to any brain researcher's arsenal. Unfortunately, MEG research has so far failed to fulfil its early promise, being hindered in its progress by a variety of factors. Conventionally, the analysis of MEG has been dominated by the search for activity in certain spectral bands - the so-called alpha, delta, beta, etc that are commonly referred to in both academic and lay publications. Other efforts have centred upon generating optimal fits of "equivalent current dipoles" that best explain the observed field distribution. Many of these approaches carry the implicit assumption that the dynamics which result in the observed time series are linear. This is despite a variety of reasons which suggest that nonlinearity might be present in MEG recordings. By using methods that allow for nonlinear dynamics, the research described in this thesis avoids these restrictive linearity assumptions. A crucial concept underpinning this project is the belief that MEG recordings are mere observations of the evolution of the true underlying state, which is unobservable and is assumed to reflect some abstract brain cognitive state. Further, we maintain that it is unreasonable to expect these processes to be adequately described in the traditional way: as a linear sum of a large number of frequency generators. One of the main objectives of this thesis will be to prove that much more effective and powerful analysis of MEG can be achieved if one were to assume the presence of both linear and nonlinear characteristics from the outset. Our position is that the combined action of a relatively small number of these generators, coupled with external and dynamic noise sources, is more than sufficient to account for the complexity observed in the MEG recordings. Another problem that has plagued MEG researchers is the extremely low signal to noise ratios that are obtained. As the magnetic flux variations resulting from actual cortical processes can be extremely minute, the measuring devices used in MEG are, necessarily, extremely sensitive. The unfortunate side-effect of this is that even commonplace phenomena such as the earth's geomagnetic field can easily swamp signals of interest. This problem is commonly addressed by averaging over a large number of recordings. However, this has a number of notable drawbacks. In particular, it is difficult to synchronise high frequency activity which might be of interest, and often these signals will be cancelled out by the averaging process. Other problems that have been encountered are high costs and low portability of state-of-the- art multichannel machines. The result of this is that the use of MEG has, hitherto, been restricted to large institutions which are able to afford the high costs associated with the procurement and maintenance of these machines. In this project, we seek to address these issues by working almost exclusively with single channel, unaveraged MEG data. We demonstrate the applicability of a variety of methods originating from the fields of signal processing, dynamical systems, information theory and neural networks, to the analysis of MEG data. It is noteworthy that while modern signal processing tools such as independent component analysis, topographic maps and latent variable modelling have enjoyed extensive success in a variety of research areas from financial time series modelling to the analysis of sun spot activity, their use in MEG analysis has thus far been extremely limited. It is hoped that this work will help to remedy this oversight.

The application of parallel processing methods to vibrational analysis

The trend in modal extraction algorithms is to use all the available frequency response functions data to obtain a global estimate of the natural frequencies, damping ratio and mode shapes. Improvements in transducer and signal processing technology allow the simultaneous measurement of many hundreds of channels of response data. The quantity of data available and the complexity of the extraction algorithms make considerable demands on the available computer power and require a powerful computer or dedicated workstation to perform satisfactorily. An alternative to waiting for faster sequential processors is to implement the algorithm in parallel, for example on a network of Transputers. Parallel architectures are a cost effective means of increasing computational power, and a larger number of response channels would simply require more processors. This thesis considers how two typical modal extraction algorithms, the Rational Fraction Polynomial method and the Ibrahim Time Domain method, may be implemented on a network of transputers. The Rational Fraction Polynomial Method is a well known and robust frequency domain 'curve fitting' algorithm. The Ibrahim Time Domain method is an efficient algorithm that 'curve fits' in the time domain. This thesis reviews the algorithms, considers the problems involved in a parallel implementation, and shows how they were implemented on a real Transputer network.

Sparse signal representation by adaptive non-uniform B-spline dictionaries on a compact interval

Non-uniform B-spline dictionaries on a compact interval are discussed in the context of sparse signal representation. For each given partition, dictionaries of B-spline functions for the corresponding spline space are built up by dividing the partition into subpartitions and joining together the bases for the concomitant subspaces. The resulting slightly redundant dictionaries are composed of B-spline functions of broader support than those corresponding to the B-spline basis for the identical space. Such dictionaries are meant to assist in the construction of adaptive sparse signal representation through a combination of stepwise optimal greedy techniques.

Nonlinear pulse shaping in fibres for pulse generation and optical processing

The development of new all-optical technologies for data processing and signal manipulation is a field of growing importance with a strong potential for numerous applications in diverse areas of modern science. Nonlinear phenomena occurring in optical fibres have many attractive features and great, but not yet fully explored, potential in signal processing. Here, we review recent progress on the use of fibre nonlinearities for the generation and shaping of optical pulses and on the applications of advanced pulse shapes in all-optical signal processing. Amongst other topics, we will discuss ultrahigh repetition rate pulse sources, the generation of parabolic shaped pulses in active and passive fibres, the generation of pulses with triangular temporal profiles, and coherent supercontinuum sources. The signal processing applications will span optical regeneration, linear distortion compensation, optical decision at the receiver in optical communication systems, spectral and temporal signal doubling, and frequency conversion. © Copyright 2012 Sonia Boscolo and Christophe Finot.

Phase discrimination and simultaneous frequency conversion of the orthogonal components of an optical signal by four-wave mixing in an SOA

Simultaneous conversion of the two orthogonal phase components of an optical input to different output frequencies has been demonstrated by simulation and experiment. A single stage of four-wave mixing between the input signal and four pumps derived from a frequency comb was employed. The nonlinear device was a semiconductor optical amplifier, which provided overall signal gain and sufficient contrast for phase sensitive signal processing. The decomposition of a quadrature phase-shift keyed signal into a pair of binary phase-shift keyed outputs at different frequencies was also demonstrated by simulation.

Full-field electronic dispersion compensation of a 10 Gbit/s OOK signal over 4 x 124 km field-installed single-mode fibre

We experimentally demonstrate the use of full-field electronic dispersion compensation (EDC) to achieve a bit error rate of 5 x 10(-5) at 22.3 dB optical signal-to-noise ratio for single-channel 10 Gbit/s on-off keyed signal after transmission over 496 km field-installed single-mode fibre with an amplifier spacing of 124 km. This performance is achieved by designing the EDC so as to avoid electronic amplification of the noise content of the signal during full-field reconstruction. We also investigate the tolerance of the system to key signal processing parameters, and numerically demonstrate that single-channel 2160 km single mode fibre transmission without in-line optical dispersion compensation can be achieved using this technique with 80 km amplifier spacing and optimized system parameters.

Recent advances in fibre grating devices and their sensing applications

Over the last twenty years, we have been continuously seeing R&D efforts and activities in developing optical fibre grating devices and technologies and exploring their applications for telecommunications, optical signal processing and smart sensing, and recently for medical care and biophotonics. In addition, we have also witnessed successful commercialisation of these R&Ds, especially in the area of fibre Bragg grating (FBG) based distributed sensor network systems and technologies for engineering structure monitoring in industrial sectors such as oil, energy and civil engineering. Despite countless published reports and papers and commercial realisation, we are still seeing significant and novel research activities in this area. This invited paper will give an overview on recent advances in fibre grating devices and their sensing applications with a focus on novel fibre gratings and their functions and grating structures in speciality fibres. The most recent developments in (i) femtosecond inscription for microfluidic/grating devices, (2) tilted grating based novel polarisation devices and (3) dual-peak long-period grating based DNA hybridisation sensors will be discussed.

Digital fiber nonlinearity compensation:toward 1-Tb/s transport

The world is connected by a core network of long-haul optical communication systems that link countries and continents, enabling long-distance phone calls, data-center communications, and the Internet. The demands on information rates have been constantly driven up by applications such as online gaming, high-definition video, and cloud computing. All over the world, end-user connection speeds are being increased by replacing conventional digital subscriber line (DSL) and asymmetric DSL (ADSL) with fiber to the home. Clearly, the capacity of the core network must also increase proportionally. © 1991-2012 IEEE.

Proteomic analysis of phosphorylation, oxidation and nitrosylation in signal transduction

Signal transduction pathways control cell fate, survival and function. They are organized as intricate biochemical networks which enable biochemical protein activities, crosstalk and subcellular localization to be integrated and tuned to produce highly specific biological responses in a robust and reproducible manner. Post translational Modifications (PTMs) play major roles in regulating these processes through a wide variety of mechanisms that include changes in protein activities, interactions, and subcellular localizations. Determining and analyzing PTMs poses enormous challenges. Recent progress in mass spectrometry (MS) based proteomics have enhanced our capability to map and identify many PTMs. Here we review the current state of proteomic PTM analysis relevant for signal transduction research, focusing on two areas: phosphorylation, which is well established as a widespread key regulator of signal transduction; and oxidative modifications, which from being primarily viewed as protein damage now start to emerge as important regulatory mechanisms.

Photonic processing for wideband cancellation and spectral discrimination of RF signals

Photonic signal processing is used to implement common mode signal cancellation across a very wide bandwidth utilising phase modulation of radio frequency (RF) signals onto a narrow linewidth laser carrier. RF spectra were observed using narrow-band, tunable optical filtering using a scanning Fabry Perot etalon. Thus functions conventionally performed using digital signal processing techniques in the electronic domain have been replaced by analog techniques in the photonic domain. This technique was able to observe simultaneous cancellation of signals across a bandwidth of 1400 MHz, limited only by the free spectral range of the etalon. © 2013 David M. Benton.