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AO-RMM: A Scalable Riemannian Optimization Framework for Joint IRS Phase and Precoding Design in mmWave Systems

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Bibliographic Details
Published in:IEEE Open Journal of the Communications Society
Format: Online Article RSS Article
Published: 2026
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container_title IEEE Open Journal of the Communications Society
description
discipline_display Computer Science
discipline_facet Computer Science
format Online Article
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genre Journal Article
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institution FRELIP
journal_source_facet IEEE Open Journal of the Communications Society
publishDate 2026
publishDateSort 2026
record_format rss_article
spellingShingle AO-RMM: A Scalable Riemannian Optimization Framework for Joint IRS Phase and Precoding Design in mmWave Systems
Computer Science
General
Computer Science
sub_discipline_display General
sub_discipline_facet General
subject_display Computer Science
General
Computer Science
Computer Science
General
Computer Science
subject_facet Computer Science
General
Computer Science
title AO-RMM: A Scalable Riemannian Optimization Framework for Joint IRS Phase and Precoding Design in mmWave Systems
title_auth AO-RMM: A Scalable Riemannian Optimization Framework for Joint IRS Phase and Precoding Design in mmWave Systems
title_full AO-RMM: A Scalable Riemannian Optimization Framework for Joint IRS Phase and Precoding Design in mmWave Systems
title_fullStr AO-RMM: A Scalable Riemannian Optimization Framework for Joint IRS Phase and Precoding Design in mmWave Systems
title_full_unstemmed AO-RMM: A Scalable Riemannian Optimization Framework for Joint IRS Phase and Precoding Design in mmWave Systems
title_short AO-RMM: A Scalable Riemannian Optimization Framework for Joint IRS Phase and Precoding Design in mmWave Systems
title_sort ao-rmm: a scalable riemannian optimization framework for joint irs phase and precoding design in mmwave systems
topic Computer Science
General
Computer Science
url http://ieeexplore.ieee.org/document/11505819