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Title: Uncertainties and array geometry selection
Author: Akindoyin, Akinbiyi Olaposi
ISNI:       0000 0004 7969 8068
Awarding Body: Imperial College London
Current Institution: Imperial College London
Date of Award: 2017
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This thesis investigates several issues associated with antenna array uncertainties, antenna array geometries and antenna selection approaches. In particular, initially this thesis is concerned with problem of using separate units of cheap SDR with independent local oscillator (LO) in a multi-antenna system. In such a system, each of these SDR boards which forms the receiving array elements has slightly different carrier frequency and phase uncertainties even if all the local oscillators are using similar hardware. In order to form a fully coherent array testbed, two synchronisation methods are proposed to remove these uncertainties/errors. The first is a hardware synchronisation approach while the second is based on a novel algorithm which operates on the non-synchronous data to transform them to a new set of synchronous data by removing the local oscillator uncertainties. Finally the problem of antenna array selection is studied. Initially, this is based on the selection metrics that are based on various performance criteria. Then a qualitative study of the impact of the array geometry on the overall system performance is investigated with emphasis given to the family of 2D grid antenna array. Antenna array selection is suitable for systems with large number of antenna array and limited number of processors and RF units where, there is a strong motivation to develop an efficient and optimal antenna subset selection algorithm. Antenna selection is a signal processing technique that can help to reduce the number of RF chains, while preserving the system performance at a certain required level. Then, a different antenna array selection approach is proposed which is based on the concept of sensor locator polynomial (SLP) in conjunction with two equivalent linear arrays (ELA) and sensitivity analysis of the array geometry and its associated manifold, thus selecting the best subset of antennas that satisfies a predefined criterion.
Supervisor: Manikas, Athanassios Sponsor: Not available
Qualification Name: Thesis (Ph.D.) Qualification Level: Doctoral