This thesis is concerned with the use of diversely polarized antennas in an array system as the advantage of this array architecture over a uniformly polarized array is its capability to separate multiple signals based on their polarization characteristics. Overall system performance is substantially improved due to an extra degree of signal discrimination. In this thesis, the aim is to address and explore several issues regarding the employment of the diversely polarized antennas in order to assess the array performance and its characteristics. First of all, the geometrical properties of the array manifold associated with polarization-sensitive array are explored from the differential geometry perspective. The fact that the array manifold incorporates all information about the array and signal environments allows it to completely characterize the whole system. In this work, a new mathematical framework is proposed to analyze three- parameter diversely polarized manifold, where important notations to describe the local characteristics of the manifold are provided. Second, issues regarding the presence of uncertainties in polarization-sensitive arrays are investigated. The array system considered so far is assumed to be free from errors and uncertainties. However, in practice, the system performance is affected considerably by various types of uncertainties that deviate from the assumed conditions. A framework based on the sensitivity analysis of manifold shape property is presented to evaluate the array robustness to uncertainties. In addition, a novel calibration method is proposed utilizing the concept of diversely polarized manifold. Third, problems regarding the presence of manifold ambiguities are addressed. Manifold ambiguity is an undesirable situation often encountered when there exists linear dependence amongst array response vectors. This study aims to investigate issues regarding the identification, classification, as well as the eradication of some types of ambiguities. A general framework to identify diversely polarized manifold ambiguity is presented, followed by two novel techniques to resolve ambiguities. Finally, issues regarding the use of polarization-sensitive antennas in CDMA- based systems are addressed. The framework is essentially based on an integration of polarization-sensitive antennas, space-time array processing, and the spread-spectrum multiple access technology. First, the properties of Polarization- Spatio-Temporal ARray (Polar-STAR) manifold is investigated based on a direct relationship with the diversely polarized manifold. Then, the array's ultimate detection capabilities are presented. Finally, a self calibration method for a polarization-sensitive asynchronous DS-CDMA system is proposed.

I have developed a robust design methodology in a 0.18 [Mu]m commercial CMOS process to circumvent the performance issues of the integrated Ions Sensitive Field Effect Transistor (ISFET) for pH detection. In circuit design, I have developed frequency domain signal processing, which transforms pH information into a frequency modulated signal. The frequency modulated signal is subsequently digitized and encoded into a bit-stream of data. The architecture of the instrumentation system consists of a) A novel front-end averaging amplifier to interface an array of ISFETs for converting pH into a voltage signal, b) A high linear voltage controlled oscillator for converting the voltage signal into a frequency modulated signal, and c) Digital gates for digitizing and differentiating the frequency modulated signal into an output bit-stream. The output bit stream is indistinguishable to a 1st order sigma delta modulation, whose noise floor is shaped by +20dB/decade. The fabricated instrumentation system has a dimension of 1565 [Mu] m 1565 [Mu] m. The chip responds linearly to the pH in a chemical solution and produces a digital output, with up to an 8-bit accuracy. Most importantly, the fabricated chips do not need any post-CMOS processing for neutralizing any trapped-charged effect, which can modulate on-chip ISFETs’ threshold voltages into atypical values. As compared to other ISFET-related works in the literature, the instrumentation system proposed in this thesis can cope with the mismatched ISFETs on chip for analogue-to-digital conversions. The design methodology is thus very accurate and robust for chemical sensing.

Overview: The basic thesis for the advancement of millimetre-wave and terahertz electronics is represented in four sections: Signal Processing, Component Design and Realization, Modelling and Materials, and Paradigm Shift. The first section is at system and circuit levels and reports on complex signal process functions that have been performed directly on the millimetre-wave carrier signal, intended for realizing low-cost and adaptive communications and radar systems architectures. The second section is at circuit and component levels and reports on techniques for the design and realization of low-loss passives for use at millimetrewave frequencies. The third section is at component and material levels and reports on modelling techniques for passives for use at both millimetre-wave and terahertz frequencies. Finally, the fourth section introduces a revolutionary new technology that represents a paradigm shift in the way millimetre-wave and terahertz electronics (i.e. components, circuits and systems) can be implemented. As found with the new generation of mobile phone handsets, a fusion of two extreme technologies can take place; here, complex signal processing operations could be performed both directly on the carrier signal and with the use of a spatial light modulator. Based on a selection of 20 papers (co-)authored by the candidate †b, and published over a period of 15 years, it will be seen that a coherent theme runs throughout this body of work, for the advancement of knowledge in millimetre-wave and terahertz electronics.

This thesis is concerned with the development and study of ambipolar organic field-effect transistors (OFETs), with a specific focus on devices and structures that are relevant to opto-electronic processes. After giving an outline of the relevant theory and experimental methods, the thesis is divided into three experimental chapters. In the chapter on organic phototransistors (OPTs), the fabrication of low-voltage bilayer OPTs is carried out using self-assembled monolayer gate dielectrics. By combining two low-voltage OPTs, the output voltage of a so-called photo-inverter was observed to be modulated over a range of 1.5 V with an incident optical power density of 0 to 1.2 mWcm-2. The characteristics of a high-voltage polymer:fullerene blend photo-inverter device are modelled using variable-range hopping and simple circuit models, suggesting that the device operation is dominated by changes in the threshold voltage. In the second experimental chapter the relationship between the morphology of polymer:fullerene blends and the characteristics of OFETs is studied. It is shown that the thermally-induced clustering of fullerenes is manifest as a reduction in electron mobility, due to a reduction in percolating pathways. It is additionally found that higher molecularweight fullerenes require greater annealing temperature and/or times for this process to occur. The final experimental chapter is concerned with polymer:fullerene diffusion processes and the study of such phenomena using bilayer OFETs. A model based upon the diffusion equation and percolation theory is employed to quantify this process. Again, higher molecularweight fullerenes are observed to require greater annealing temperature for similar phenomena to be observed.

It is broadly trusted that effective scheduling of flexible demand and energy storage operation will offer opportunities for reduced investment in transmission and distribution assets together with the associated lower environmental footprint and avoidance of long delays in connecting renewable generation. Expected demand migration from transport and heat sectors in few next decades is going to give additional stress to the electricity networks as this load is characterized with relatively low diversity factors restricting the amount of demand growth that can be accommodated into existing networks. The potential benefits of using Demand Side Response (DSR) and Storage technologies for network applications have not been fully explored due to a lack of rigorous methodology for quantification of the effects of these technologies on network operation and development. In this context, this work focuses on the investigation of the potential benefits of utilization of DSR, Storage and Electric Vehicles (EV) as potential means for network congestion management and for maximizing the system capability to employ renewable energy sources. To this purpose, novel methodologies are developed based on a multi-period Optimal Power Flow (OPF), where DSR, Storage and EV are modelled as a part of the optimisation constraints. The proposed optimisation methodologies and techniques are applied to estimate a magnitude of order of potential value of DSR, Storage and EV for alternative development of the electricity systems. Without loss of generality, DSR principle explained is based on a batch of wet appliances (composed by dishwashers, washing machines, and tumble dryers). The benefits are evaluated by comparing scenarios without and with these enabling technologies. The expected outcome of the research is to identify trends and characteristic conditions in which the enabling technologies are likely to have a high value, and also to determine the key driving factors for the value of these technologies in the context of releasing latent network capacity.

Relays have been used to overcome existing network performance bottlenecks in meeting the growing demand for large bandwidth and high quality of service (QoS) in wireless networks. This thesis proposes several wireless transmission protocols using relays in practical multi-user broadcast and information exchange channels. The main theme is to demonstrate that efficient use of relays provides an additional dimension to improve reliability, throughput, power efficiency and secrecy. First, a spectrally efficient cooperative transmission protocol is proposed for the multiple-input and singleoutput (MISO) broadcast channel to improve the reliability of wireless transmission. The proposed protocol mitigates co-channel interference and provides another dimension to improve the diversity gain. Analytical and simulation results show that outage probability and the diversity and multiplexing tradeoff of the proposed cooperative protocol outperforms the non-cooperative scheme. Second, a two-way relaying protocol is proposed for the multi-pair, two-way relaying channel to improve the throughput and reliability. The proposed protocol enables both the users and the relay to participate in interference cancellation. Several beamforming schemes are proposed for the multi-antenna relay. Analytical and simulation results reveal that the proposed protocol delivers significant improvements in ergodic capacity, outage probability and the diversity and multiplexing tradeoff if compared to existing schemes. Third, a joint beamforming and power management scheme is proposed for multiple-input and multiple-output (MIMO) two-way relaying channel to improve the sum-rate. Network power allocation and power control optimisation problems are formulated and solved using convex optimisation techniques. Simulation results verify that the proposed scheme delivers better sum-rate or consumes lower power when compared to existing schemes. Fourth, two-way secrecy schemes which combine one-time pad and wiretap coding are proposed for the scalar broadcast channel to improve secrecy rate. The proposed schemes utilise the channel reciprocity and employ relays to forward secret messages. Analytical and simulation results reveal that the proposed schemes are able to achieve positive secrecy rates even when the number of users is large. All of these new wireless transmission protocols help to realise better throughput, reliability, power efficiency and secrecy for wireless broadcast and information exchange channels through the efficient use of relays.

Continuous scaling of CMOS technology has now reached a state of evolution, therefore, novel device structures and new materials have been proposed for this purpose. The Screen- Grid field Effect Transistor is introduced as a as a novel device structure that takes advantage of several innovative aspects of the FinFET while introducing new geometrical feature to improve a FET device performance. The idea is to design a FET which is as small as possible without down-scaling issues, at the same time satisfying optimum device performance for both analogue and digital applications. The analogue operation of the SGrFET shows some promising results which make it interesting to continue the investigation on SGrFET for digital applications. The SGrFET addresses some of the concerns of scaled CMOS such as Drain Induce Barrier Lowering and sub-threshold slope, by offering the superior short channel control. In this work in order to evaluate SGrFET performance, the proposed device compared to the classical MOSFET and provides comprehensive benchmarking with finFETs. Both AC and DC simulations are presented using TaurusTM and MediciTM simulators which are commercially available via Synopsis. Initial investigation on the novel device with the single gate structure is carried out. The multi-geometrical characteristic of the proposed device is used to reduce parasitic capacitance and increase ION/IOFF ratio to improve device performance in terms of switching characteristic in different circuit structures. Using TaurusTM AC simulation, a small signal circuit is introduced for SGrFET and evaluated using both extracted small signal elements from TaurusTM and Y-parameter extraction. The SGrFET allows for the unique behavioural characteristics of an independent-gate device. Different configurations of double-gate device are introduced and benchmark against the finFET serving as a double gate device. Five different logic circuits, the complementary and N-inverter, the NOR, NAND and XOR, and controllable Current Mirror circuits are simulated with finFET and SGrFET and their performance compared. Some digital key merits are extracted for both finFET and SGrFET such as power dissipation, noise margin and switching speed to compare the devices under the investigation performance against each other. It is shown that using multi-geometrical feature in SGrFET together with its multi-gate operation can greatly decrease the number of device needed for the logic function without speed degradation and it can be used as a potential candidate in mix-circuit configuration as a multi-gate device. The initial fabrication steps of the novel device explained together with some in-house fabrication process using E-Beam lithography. The fabricated SGrFET is characterised via electrical measurements and used in a circuit configuration.

This thesis explores the attitude estimation and control problem of a magnetically controlled small satellite in initial acquisition phase. During this phase, large data uncertainties pose estimation challenges, while highly nonlinear dynamics and inherent limitations of the magnetic actuation are primary issues in control. We aim to design algorithms, which can improve performance compared to the state of the art techniques and remain tractable for practical applications. Static attitude estimation, which is an essential part of a satellite control system, uses vector information and solves a constrained weighted least-square problem. With large data uncertainties, this technique results in large errors rendering divergence or infeasibility in dynamic filtering and control. When static estimation is the primary source of attitude, these errors become critical; for example in low budget small satellites. To address this issue, we formulate a robust static estimation problem with norm-bounded uncertainties, which is a difficult optimization problem due to its unfavorable convexity properties and nonlinear constraints. By deriving an analytical upper bound for the convex maximization, the robust min-max problem is approximated with a minimization problem with quadratic cost and constraints (a QCQP), which is non-convex. Semidefinite relaxation is used to upper bound the non-convex QCQP with a semi-definite program, which can efficiently be solved in a polynomial time. Furthermore, it is shown that the derived upper bound has no gap in solving the robust problem in practice. Semi-definite relaxations are also applied to solve the robust formulations of a more general class of problems known as the orthogonal Procrustes problem (OPP). It is shown that the solution of the relaxed OPP is exact when no uncertainties are considered; however, for the robust case, only a sub-optimal solution can be obtained. Finally, a satellite rate damping in initial acquisition phase is addressed by using nonlinear model predictive control (NMPC). Standard NMPC schemes with guaranteed stability show superior performance than existing techniques; however, they are computationally expensive. With large initial rates, the computational burden of NMPC becomes prohibitively excessive. For these cases, an algorithm is presented with an additional constraint on the cost reduction that allows an early termination of the optimizer based on the available computational resources. The presented algorithm significantly reduces the de-tumbling time due to the imposed cost reduction constraint.

In this research, a Surface Plasmon Resonance (SPR) based sensor system was developed for quick detection of not only silver nanoparticles at low concentrations, but also to a range of individual analytes, according to their optical properties. SPR-based sensors are extremely sensitive to changes in the optical properties of the local environment at this interface, making these instruments highly valuable for surface science and bio-sensing experiments. This has enabled silver in solution (silver nitrate) to be detected from colloidal nanoparticles. This study involves the theoretical development of an SPR system, where a glass prism and a multi-layered chip are used. The model presented is rigorous and applicable for any multilayer system. With this model, different parameters of the sensor can be selectively altered allowing the user to optimise the sensor’s response for a particular analyte and to determine system parameters on the basis of results obtained during experiments. Both theoretical predictions and experimental measurements show that the predicted effective permittivity of silver nanoparticles Ag NPs compared with silver nitrate AgNO3 enabled the presence of colloidal silver versus silver in solution to be differentiated down to a concentration limit of 0.1 mgl-1. Different materials were analysed for the compatibility and chemical stability for fabricating biochips. It has been successfully demonstrated that graphene-based SPR sensors are quite promising instruments owing to their improved sensitivity and other beneficial characteristics. Discussion related to different results obtained during experiments is also included together with some recommendations. Opportunities for future research are also mentioned, such as miniaturisation of an SPR sensor system for portable applications so that this technology can be utilised for detection of nano toxicants in the environment.

This thesis concerns the problem of prototype reduction in instance-based learning. In order to deal with problems such as storage requirements, sensitivity to noise and computational complexity, various algorithms have been presented that condense the number of stored prototypes, while maintaining competent classification accuracy. Instance selection, which recovers a smaller subset of the original training set, is the most widely used technique for instance reduction. But, prototype abstraction that generates new prototypes to replace the initial ones has also gained a lot of interest recently. The major contribution of this work is the proposal of four novel frameworks for performing prototype reduction, the Class Boundary Preserving algorithm (CBP), a hybrid method that uses both selection and generation of prototypes, Instance Seriation for Prototype Abstraction (ISPA), which is an abstraction algorithm, and two selective techniques, Spectral Instance Reduction (SIR) and Direct Weight Optimization (DWO). CBP is a multi-stage method based on a simple heuristic that is very effective in identifying samples close to class borders. Using a noise filter harmful instances are removed, while the powerful heuristic determines the geometrical distribution of patterns around every instance. Together with the concepts of nearest enemy pairs and mean shift clustering this algorithm decides on the final set of retained prototypes. DWO is a selection model whose output set of prototypes is decided by a set of binary weights. These weights are computed according to an objective function composed of the ratio between the nearest friend and nearest enemy of every sample. In order to obtain good quality results DWO is optimized using a genetic algorithm. ISPA is an abstraction technique that employs the concept of data seriation to organize instances in an arrangement that favours merging between them. As a result, a new set of prototypes is created. Results show that CBP, SIR and DWO, the three major algorithms presented in this thesis, are competent and efficient in terms of at least one of the two basic objectives, classification accuracy and condensation ratio. The comparison against other successful condensation algorithms illustrates the competitiveness of the proposed models. The SIR algorithm presents a set of border discriminating features (BDFs) that depicts the local distribution of friends and enemies of all samples. These are then used along with spectral graph theory to partition the training set in to border and internal instances.