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Doctoral Degrees (Electronic Engineering)

Permanent URI for this collectionhttps://hdl.handle.net/10413/6867

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Browsing Doctoral Degrees (Electronic Engineering) by Subject "Algorithms."

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    Application of cognitive radio based sensor network in smart grids for efficient, holistic monitoring and control.
    (2018) Ogbodo, Emmanuel Utochukwu.; Dorrell, David George.; Abu-Mahfouz, Adnan M.
    This thesis is directed towards the application of cognitive radio based sensor network (CRSN) in smart grid (SG) for efficient, holistic monitoring and control. The work involves enabling of sensor network and wireless communication devices for spectra utilization via the capability of Dynamic Spectrum Access (DSA) of a cognitive radio (CR) as well as end to end communication access technology for unified monitoring and control in smart grids. Smart Grid (SG) is a new power grid paradigm that can provide predictive information and recommendations to utilities, including their suppliers, and their customers on how best to manage power delivery and consumption. SG can greatly reduce air pollution from our surrounding by renewable power sources such as wind energy, solar plants and huge hydro stations. SG also reduces electricity blackouts and surges. Communication network is the foundation for modern SG. Implementing an improved communication solution will help in addressing the problems of the existing SG. Hence, this study proposed and implemented improved CRSN model which will help to ultimately evade the inherent problems of communication network in the SG such as: energy inefficiency, interference, spectrum inefficiencies, poor quality of service (QoS), latency and throughput. To overcome these problems, the existing approach which is more predominant is the use of wireless sensor network (WSNs) for communication needs in SG. However, WSNs have low battery power, low computational complexity, low bandwidth support, and high latency or delay due to multihop transmission in existing WSN topology. Consequently, solving these problems by addressing energy efficiency, bandwidth or throughput, and latency have not been fully realized due to the limitations in the WSN and the existing network topology. Therefore, existing approach has not fully addressed the communication needs in SG. SG can be fully realized by integrating communication network technologies infrastructures into the power grid. Cognitive Radio-based Sensor Network (CRSN) is considered a feasible solution to enhance various aspects of the electric power grid such as communication with end and remote devices in real-time manner for efficient monitoring and to realize maximum benefits of a smart grid system. CRSN in SG is aimed at addressing the problem of spectrum inefficiency and interference which wireless sensor network (WSN) could not. However, numerous challenges for CRSNs are due to the harsh environmental wireless condition in a smart grid system. As a result, latency, throughput and reliability become critical issues. To overcome these challenges, lots of approaches can be adopted ranging from integration of CRSNs into SGs; proper implementation design model for SG; reliable communication access devices for SG; key immunity requirements for communication infrastructure in SG; up to communication network protocol optimization and so on. To this end, this study utilized the National Institute of Standard (NIST) framework for SG interoperability in the design of unified communication network architecture including implementation model for guaranteed quality of service (QoS) of smart grid applications. This involves virtualized network in form of multi-homing comprising low power wide area network (LPWAN) devices such as LTE CAT1/LTE-M, and TV white space band device (TVBD). Simulation and analysis show that the performance of the developed modules architecture outperforms the legacy wireless systems in terms of latency, blocking probability, and throughput in SG harsh environmental condition. In addition, the problem of multi correlation fading channels due to multi antenna channels of the sensor nodes in CRSN based SG has been addressed by the performance analysis of a moment generating function (MGF) based M-QAM error probability over Nakagami-q dual correlated fading channels with maximum ratio combiner (MRC) receiver technique which includes derivation and novel algorithmic approach. The results of the MATLAB simulation are provided as a guide for sensor node deployment in order to avoid the problem of multi correlation in CRSN based SGs. SGs application requires reliable and efficient communication with low latency in timely manner as well as adequate topology of sensor nodes deployment for guaranteed QoS. Another important requirement is the need for an optimized protocol/algorithms for energy efficiency and cross layer spectrum aware made possible for opportunistic spectrum access in the CRSN nodes. Consequently, an optimized cross layer interaction of the physical and MAC layer protocols using various novel algorithms and techniques was developed. This includes a novel energy efficient distributed heterogeneous clustered spectrum aware (EDHC- SA) multichannel sensing signal model with novel algorithm called Equilateral triangulation algorithm for guaranteed network connectivity in CRSN based SG. The simulation results further obtained confirm that EDHC-SA CRSN model outperforms conventional ZigBee WSN in terms of bit error rate (BER), end-to-end delay (latency) and energy consumption. This no doubt validates the suitability of the developed model in SG.
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    Optimized digital signal processing algorithms applied to radio communications.
    (1992) Carter, Alan James Auchmuty.; Broadhurst, Anthony D.
    The application of digital signal processing to radio communications has come of age with the advent of low power, high speed microprocessors and over the past five years, various transceiver architectures, utilizing this new technology have been extensively researched. Due to the flexible nature of a software based transceiver, a myriad of possible applications exist and currently the emphasis is on the development of suitable algorithms. The principal aim of this research is the derivation of optimized digital signal processing algorithms applicable to three separate areas of radio communications. Optimized, as used by the author within this dissertation, implies a reasonable compromise between performance, complexity and numerical processing efficiency. This compromise is necessary since the algorithms are applied to a portable transceiver where power consumption, size and weight are limited. The digital signal processing algorithms described by this research is as follows:- 1. The derivation and assessment of a multirate speech amplitude modulation demodulator which exhibits low distortion (typically less than 2%) for a wide range of modulation indices, carrier frequency offsets and deviations. The demodulator is processing efficient and requires only five multiplications and five decisions for every output sample. 2. The derivation and assessment of a low sampling rate speech frequency modulation demodulator for signals whose bandwidth exceed quarter the sampling frequency. The demodulator exhibits low distortion (typically less than 2%) and is processing efficient requiring eighteen multiplications and three decisions for every output sample. 3. The derivation and assessment of a multirate single-sideband suppressed carrier automatic frequency control system which is a combination of a simple second order adaptive line enhancer and a digital phase-locked loop. The processing efficient automatic frequency control system is suited for low signal to noise power conditions, in both stationary and mobile communication channels.