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Title: Enhancing the degrees of freedom in array signal processing
Author: Sridhar, Vidhya
ISNI:       0000 0004 7969 8199
Awarding Body: Imperial College London
Current Institution: Imperial College London
Date of Award: 2017
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Future antenna array systems are expected to deliver extremely high data rates whilst combating challenges of exponential increase in user density, high interference levels and multipath dispersion effects. Towards this end, this thesis presents novel algorithms to enhance the degrees of freedom (DoF) of a multiple-input multiple-output (MIMO) antenna array system. Furthermore, arrays that possess time-varying array geometry, termed as flexible arrays, are investigated for the purpose of defence and internet of things (IoT) applications, such as unmanned aerial vehicle (UAV) clusters and multi-platform arrays. The parametric channel model, which provides a tractable mathematical model for wireless channels, lays the foundation for all the algorithms in this thesis. Based on this model, three systems are proposed, that extend the DoF progressively. Firstly, the spatial-only system is explored, in terms of the relationships between the array geometry and various array performance criteria, such as the thresholds of detection and resolution and the capacity loss. Secondly, the spatial-only system is extended to a spatiotemporal array system, to extend the DoF beyond the spatial domain, by employing a novel transmitter, a multi-parameter channel estimator and a spatiotemporal beamformer that suppresses interference in space and time jointly. Thirdly, the spatiotemporal system is extended to a spatiotemporal-virtual system, by extracting and exploiting the Tx array geometry. Finally, the concept of flexible array signal processing is introduced for sensor arrays with time-varying sensor positions, such as UAV clusters and towed arrays. Based on three underpinning models, namely, a parametric channel model, a physical mobility model of the flexible array and a mobility model of the targets, an arrayed-state space model is constructed that is utilised in conjunction with an extended Kalman fillter, to continually track the sensor positions and target parameters. All the algorithms presented in this thesis are evaluated using computer simulation studies.
Supervisor: Manikas, Athanassios Sponsor: Imperial College London
Qualification Name: Thesis (Ph.D.) Qualification Level: Doctoral