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

Signal processing with Fourier analysis, novel algorithms and applications

Fourier analysis is the study of the way general functions may be represented or approximated by sums of simpler trigonometric functions, also analogously known as sinusoidal modeling. The original idea of Fourier had a profound impact on mathematical analysis, physics and engineering because it diagonalizes time-invariant convolution operators. In the past signal processing was a topic that stayed almost exclusively in electrical engineering, where only the experts could cancel noise, compress and reconstruct signals. Nowadays it is almost ubiquitous, as everyone now deals with modern digital signals. Medical imaging, wireless communications and power systems of the future will experience more data processing conditions and wider range of applications requirements than the systems of today. Such systems will require more powerful, efficient and flexible signal processing algorithms that are well designed to handle such needs. No matter how advanced our hardware technology becomes we will still need intelligent and efficient algorithms to address the growing demands in signal processing. In this thesis, we investigate novel techniques to solve a suite of four fundamental problems in signal processing that have a wide range of applications. The relevant equations, literature of signal processing applications, analysis and final numerical algorithms/methods to solve them using Fourier analysis are discussed for different applications in the electrical engineering/computer science. The first four chapters cover the following topics of central importance in the field of signal processing: • Fast Phasor Estimation using Adaptive Signal Processing (Chapter 2) • Frequency Estimation from Nonuniform Samples (Chapter 3) • 2D Polar and 3D Spherical Polar Nonuniform Discrete Fourier Transform (Chapter 4) • Robust 3D registration using Spherical Polar Discrete Fourier Transform and Spherical Harmonics (Chapter 5) Even though each of these four methods discussed may seem completely disparate, the underlying motivation for more efficient processing by exploiting the Fourier domain signal structure remains the same. The main contribution of this thesis is the innovation in the analysis, synthesis, discretization of certain well known problems like phasor estimation, frequency estimation, computations of a particular non-uniform Fourier transform and signal registration on the transformed domain. We conduct propositions and evaluations of certain applications relevant algorithms such as, frequency estimation algorithm using non-uniform sampling, polar and spherical polar Fourier transform. The techniques proposed are also useful in the field of computer vision and medical imaging. From a practical perspective, the proposed algorithms are shown to improve the existing solutions in the respective fields where they are applied/evaluated. The formulation and final proposition is shown to have a variety of benefits. Future work with potentials in medical imaging, directional wavelets, volume rendering, video/3D object classifications, high dimensional registration are also discussed in the final chapter. Finally, in the spirit of reproducible research we release the implementation of these algorithms to the public using Github

Performance characterization of long-distance digital microwave radio systems

Imperial Users onl

Research and Technology

Langley Research Center is engaged in the basic an applied research necessary for the advancement of aeronautics and space flight, generating advanced concepts for the accomplishment of related national goals, and provding research advice, technological support, and assistance to other NASA installations, other government agencies, and industry. Highlights of major accomplishments and applications are presented

MIMO Systems

In recent years, it was realized that the MIMO communication systems seems to be inevitable in accelerated evolution of high data rates applications due to their potential to dramatically increase the spectral efficiency and simultaneously sending individual information to the corresponding users in wireless systems. This book, intends to provide highlights of the current research topics in the field of MIMO system, to offer a snapshot of the recent advances and major issues faced today by the researchers in the MIMO related areas. The book is written by specialists working in universities and research centers all over the world to cover the fundamental principles and main advanced topics on high data rates wireless communications systems over MIMO channels. Moreover, the book has the advantage of providing a collection of applications that are completely independent and self-contained; thus, the interested reader can choose any chapter and skip to another without losing continuity

International Symposium on Magnetic Suspension Technology, Part 1

The goal of the symposium was to examine the state of technology of all areas of magnetic suspension and to review related recent developments in sensors and controls approaches, superconducting magnet technology, and design/implementation practices. The symposium included 17 technical sessions in which 55 papers were presented. The technical session covered the areas of bearings, sensors and controls, microgravity and vibration isolation, superconductivity, manufacturing applications, wind tunnel magnetic suspension systems, magnetically levitated trains (MAGLEV), space applications, and large gap magnetic suspension systems

Design and application of advanced disturbance rejection control for small fixed-wing UAVs

Small Unmanned Aerial Vehicles (UAVs) have seen continual growth in both research and commercial applications. Attractive features such as their small size, light weight and low cost are a strong driver of this growth. However, these factors also bring about some drawbacks. The light weight and small size means that small UAVs are far more susceptible to performance degradation from factors such as wind gusts. Due to the generally low cost, available sensors are somewhat limited in both quality and available measurements. For example, it is very unlikely that angle of attack is sensed by a small UAV. These aircraft are usually constructed by the end user, so a tangible amount of variation will exist between different aircraft of the same type. Depending on application, additional variation between flights from factors such as battery placement or additional sensors may exist. This makes the application of optimal model based control methods difficult. Research literature on the topic of small UAV control is very rich in regard to high level control, such as path planning in wind. A common assumption in such literature is the existence of a low level control method which is able to track demanded aircraft attitudes to complete a task. Design of such controllers in the presence of significant wind or modelling errors (factors collectively addressed as lumped disturbances herein) is rarely considered. Disturbance Observer Based Control (DOBC) is a means of improving the robustness of a baseline feedback control scheme in the presence of lumped disturbances. The method allows for the rejection of the influence of unmeasurable disturbances much more quickly than traditional integral control, while also enabling recovery of nominal feedback con- trol performance. The separation principle of DOBC allows for the design of a nominal feedback controller, which does not need to be robust against disturbances. A DOBC augmentation can then be applied to ensure this nominal performance is maintained even in the presence of disturbances. This method offers highly attractive properties for control design, and has seen a large rise in popularity in recent years. Current literature on this subject is very often conducted purely in simulation. Ad- ditionally, very advanced versions of DOBC control are now being researched. To make the method attractive to small UAV operators, it would be beneficial if a simple DOBC design could be used to realise the benefits of this method, as it would be more accessible and applicable by many. This thesis investigates the application of a linear state space disturbance observer to low level flight control of a small UAV, along with developments of the method needed to achieve good performance in flight testing. Had this work been conducted purely in simulation, it is likely many of the difficulties encountered would not have been addressed or discovered. This thesis presents four main contributions. An anti-windup method has been devel- oped which is able to alleviate the effect of control saturation on the disturbance observer dynamics. An observer is designed which explicitly considers actuator dynamics. This development was shown to enable faster observer estimation dynamics, yielding better disturbance rejection performance. During initial flight testing, a significant aeroelastic oscillation mode was discovered. This issue was studied in detail theoretically, with a pro- posed solution developed and applied. The solution was able to fully alleviate the effect in flight. Finally, design and development of an over-actuated DOBC method is presented. A method for design of DOBC for over actuated systems was developed and studied. The majority of results in this thesis are demonstrated with flight test data

Metamaterials and Metasurfaces

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