Electrical and Electronic Engineering - Theses

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    A Multifunctional Smart Field-Programmable Radio Frequency Surface
    Li, Tianzhi ( 2023-04)
    Wireless communication technology has completely transformed the way we communicate and access information. It operates on the principles of electromagnetic wave propagation, as described by Maxwell's equations. The scope of wireless communication is vast and includes satellite communication, handheld device communication, and Internet of Things (IoT), which have revolutionized fields of industry, healthcare, transportation, education, and entertainment. As demand for faster and more reliable communication continues to grow, a range of wireless communication standards has been developed, including WiFi, BLE, cellular networks, near-field communication (NFC), and ZigBee, each operating at a unique frequency range. Antennas that can operate across multiple communication standards have remained a challenge due to the interdependent factors of antenna geometry, size, and RF characteristics. As the number of devices with wireless connectivity increases dramatically, the spectrum resource is getting limited, which results in congestion and reduced performance. Reconfigurable antennas have been intensively studied in the last few decades to mitigate this challenge. Although reconfigurability in operating frequency, radiation pattern and polarization have been implemented, limitations including lack of programmability, pattern diversity, and self-adaptive capability against environmental interference exist. To address these limitations, we proposed a new concept called Field-programmable RF surface (FPRFS), which allows for the control of current flow on the surface to achieve desired antenna characteristics and impedance matching capabilities. This work starts with the theoretical analysis and creates the mathematical model for the FPRFS in antenna, impedance matching network, and filter applications. Our research demonstrated the reconfigurability of FPRFS antennas in operating frequency, radiation pattern, and polarization reconfigurability with radiation gain and efficiency levels that are comparable to those of conventional fixed patch antennas and enhanced immunity to surrounding obstacles. We developed a software algorithm for the FPRFS that enables it to automatically optimize its configuration in real-time, thereby adapting to changing load impedance or environmental interferences.
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    Biological learning mechanisms in spiking neuronal networks
    Gilson, Matthieu. (University of Melbourne, 2009)
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    Design and implementation of millimeter-wave transceivers on CMOS
    Ta, Chien Minh. (University of Melbourne, 2008)
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    Novel all-optical signal processing schemes and their applications in packet switching in core networks
    Gopalakrishna Pillai, Bipin Sankar. (University of Melbourne, 2007)
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    Resource allocation for multiuser OFDM systems
    Chen, Liang. (University of Melbourne, 2006)
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    Resource allocation for multiuser OFDM systems
    Chen, Liang. (University of Melbourne, 2006)
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    Steady-state multi-energy flow problem in coupled energy networks
    Mohammadi, Mohammad ( 2023-07)
    Energy systems worldwide are experiencing a rapid transition towards a low-carbon future, calling for greater energy efficiency and flexibility in utilising energy networks. This transition is accompanied by the growing adoption of multi-energy technologies like combined heat and power (CHP), power-to-heat, and power-to-gas units, leading to rising interdependencies between different energy networks, particularly in district and energy community applications. Hence, more effective utilisation of coupled energy networks (CEN) can bring several efficiency and flexibility benefits. Developing efficient energy flow models for CEN analysis is thus key to fully unlock these inherent benefits. The steady-state multi-energy flow (MEF) problem is the cornerstone of CEN analysis and lays the foundation for optimal operation and flexibility studies. This thesis presents a systematic evaluation of the MEF problem for steady-state analysis of CEN, exemplified in the case of coupled electricity, heat, and gas networks, by highlighting three main principles, namely formulations, coupling strategies, and solution techniques. Regarding formulations, a MEF framework is developed to incorporate various formulations for steady-state analysis of CEN, while demonstrating their impact on the convergence and computational properties of MEF models. With respect to coupling strategies, a systematic analysis is conducted on three essential coupling strategies, i.e., Decoupled, Decomposed, and Integrated, which may be associated with parallel, sequential, and simultaneous MEF computations, respectively. A set of fundamental underlying principles that characterise the coupling effectiveness in the MEF problem is introduced, namely, underlying formulations, problem size, interdependencies between networks, and calculation sequence, while highlighting their role in appraising different coupling strategies. In terms of solution techniques, besides classical Newtown-Raphson (NR), the performance of other potentially suitable algorithms, such as Quasi-NR, Levenberg-Marquardt, and Trust-Region, is extensively studied for solving MEF problems. A novel cross-over strategy is then proposed to utilise the synergistic benefits of studied algorithms for improving convergence properties without compromising computational efficiency. Building upon the insights gained from the MEF analysis, a fast decomposed algorithm is introduced for solving large-scale coupled electricity and gas networks with hydrogen injection modelling and gas composition tracking. Finally, this thesis provides novel insights and practical recommendations to identify the most suitable formulations, coupling strategies, and solution techniques for solving the steady-state MEF problem in a robust and computationally efficient way.
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    Communication Receivers with Low-Resolution Quantization: Fundamental Limits and Task-based Designs
    Bernardo, Neil Irwin ( 2023-08)
    The use of low-resolution analog-to-digital converters (ADCs) in communication receivers has gained significant interest in the research community since it addresses practical issues in 5G/6G deployment such as massive data processing, high power consumption, and high manufacturing cost. An ADC equipped in communication receivers is often designed such that its quantization thresholds are equally-spaced or the distortion between its input and output is minimized. These design approaches, however, may yield suboptimal performance as they neglect the underlying system task that the ADCs are intended to be used for. This presents an opportunity for us to explore receiver quantization designs that cater to specific communication tasks (e.g. symbol detection, channel estimation) and to understand how quantization impacts various aspects of receiver performance such as error rate, channel capacity, estimation error. In this thesis, we consider five independent research problems related to the communication receivers with low-resolution quantizers. Three of these research problems deal with capacity analysis of certain communication channels with quantized outputs. More precisely, we derive the capacity-achieving input distributions for four different channels with phase-quantized observations and the Gaussian channel with polar-quantized observations. For the channels with b-bit phase quantizer at the output, 2^b-phase shift keying modulation scheme can attain the channel capacity. Meanwhile, the capacity can be achieved in the Gaussian channel with polar quantization by an input distribution with amplitude phase shift keying structure. Capacity bounds for MIMO Gaussian channel with analog combiner and 1-bit sign quantizers are also established in this thesis. The remaining two research problems fall under the category of task-based quantizer design. The idea is to design the quantizer in accordance to the underlying system task rather than simply minimize its input-output distortion. Focusing on M-ary pulse amplitude modulation (PAM) receiver with symmetric scalar quantizer, the closed-form expression of the symbol error rate is derived as a function of quantizer structure and position of equiprobable PAM symbols. The derived expression is used to design the quantizer according to the symbol detection task. The high signal-to-noise ratio (SNR) behavior of the error rate of the quantized communication system is characterized. Our final work is a development of a new design and analysis framework for task-based quantizers with hybrid analog-to-digital architecture. In contrast to existing task-based quantization frameworks, the theoretical predictions of our proposed framework perfectly coincides with the simulated results. Moreover, the proposed frameworks can be used in data acquisition systems with non-uniform quantizers and observations with unbounded support.