Use this URL to cite or link to this record in EThOS: https://ethos.bl.uk/OrderDetails.do?uin=uk.bl.ethos.806437
Title: Antenna arrays for co-channel interference mitigation in wireless communications
Author: Gabillard, Thibaud
Awarding Body: Imperial College London
Current Institution: Imperial College London
Date of Award: 2017
Availability of Full Text:
Access from EThOS:
Access from Institution:
Abstract:
In this thesis, the capability of antenna arrays to combat co-channel interference is investigated. Initially, a parametric channel model based on the array manifold is presented and then exploited in various parts of the thesis. An emphasis is given to the impact of the antenna array geometry on the overall system performance, even in the case of systems that employ large antenna arrays (massive MIMO). Furthermore, the worst-case scenario of an interfering signal being received within a small angular separation from a source is investigated. With this, the performance of a set of array geometries is ascertained for the tasks of detection, estimation and beamforming. Links between the performance metrics and the underlying array manifolds are made and it is demonstrated that some array manifold features are more desirable for certain tasks than others. This sets the ground for the design of novel antenna arrays that would be specialised for certain telecommunication tasks. Then the novel concept of capacity loss, that is the loss of channel capacity due to the presence of interference is introduced and expressed as a function of the antenna array geometry and the signals directions of arrival. It is demonstrated that large antenna arrays with very long manifold curves do not necessarily perform the best, and smaller antenna arrays with optimised geometry could be considered instead. Finally, the parametric channel model that the thesis is based upon is utilised to present a novel blind channel estimation and complete interference cancellation beamformer. Throughout the thesis, extensive computer simulations are presented to analyse and illustrate the performance of the proposed algorithms.
Supervisor: Manikas, Athanassios Sponsor: Not available
Qualification Name: Thesis (Ph.D.) Qualification Level: Doctoral
EThOS ID: uk.bl.ethos.806437  DOI:
Share: