<div class="csl-bib-body">
<div class="csl-entry">Salihu, A. (2024). <i>Wireless localization via learned channel features in massive MIMO systems</i> [Dissertation, Technische Universität Wien]. reposiTUm. https://doi.org/10.34726/hss.2024.80622</div>
</div>
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dc.identifier.uri
https://doi.org/10.34726/hss.2024.80622
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dc.identifier.uri
http://hdl.handle.net/20.500.12708/196709
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dc.description.abstract
In this dissertation, advanced ML algorithms for enhanced wireless localization are proposed. Motivated by the capabilities of deep neural networks (DNNs) and the advancements in massive multiple-input-multiple-output (MIMO) systems, the dissertation aims to address some of the fundamental limitations of ML-based localization approaches related to dependability, generalization, and data scarcity.The dissertation has three main parts, each dedicated to addressing specific challenges and introducing new algorithms.
en
dc.language
English
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dc.language.iso
en
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dc.rights.uri
http://rightsstatements.org/vocab/InC/1.0/
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dc.subject
mobile communications
en
dc.subject
wireless localization
en
dc.subject
machine learning
en
dc.title
Wireless localization via learned channel features in massive MIMO systems
