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Article: A Tutorial on Extremely Large-Scale MIMO for 6G: Fundamentals, Signal Processing, and Applications

TitleA Tutorial on Extremely Large-Scale MIMO for 6G: Fundamentals, Signal Processing, and Applications
Authors
Keywordschannel modeling
deep learning
near-field communications
signal processing
XL-MIMO
Issue Date2024
Citation
IEEE Communications Surveys and Tutorials, 2024, v. 26, n. 3, p. 1560-1605 How to Cite?
AbstractExtremely large-scale multiple-input-multiple-output (XL-MIMO), which offers vast spatial degrees of freedom, has emerged as a potentially pivotal enabling technology for the sixth generation (6G) of wireless mobile networks. With its growing significance, both opportunities and challenges are concurrently manifesting. This paper presents a comprehensive survey of research on XL-MIMO wireless systems. In particular, we introduce four XL-MIMO hardware architectures: uniform linear array (ULA)-based XL-MIMO, uniform planar array (UPA)-based XL-MIMO utilizing either patch antennas or point antennas, and continuous aperture (CAP)-based XL-MIMO. We comprehensively analyze and discuss their characteristics and interrelationships. Following this, we introduce several electromagnetic characteristics and general distance boundaries in XL-MIMO. Given the distinct electromagnetic properties of near-field communications, we present a range of channel models to demonstrate the benefits of XL-MIMO. We further discuss and summarize signal processing schemes for XL-MIMO. It is worth noting that the low-complexity signal processing schemes and deep learning empowered signal processing schemes are reviewed and highlighted to promote the practical implementation of XL-MIMO. Furthermore, we explore the interplay between XL-MIMO and other emergent 6G technologies. Finally, we outline several compelling research directions for future XL-MIMO wireless communication systems.
Persistent Identifierhttp://hdl.handle.net/10722/353132

 

DC FieldValueLanguage
dc.contributor.authorWang, Zhe-
dc.contributor.authorZhang, Jiayi-
dc.contributor.authorDu, Hongyang-
dc.contributor.authorNiyato, Dusit-
dc.contributor.authorCui, Shuguang-
dc.contributor.authorAi, Bo-
dc.contributor.authorDebbah, Merouane-
dc.contributor.authorLetaief, Khaled B.-
dc.contributor.authorPoor, H. Vincent-
dc.date.accessioned2025-01-13T03:02:14Z-
dc.date.available2025-01-13T03:02:14Z-
dc.date.issued2024-
dc.identifier.citationIEEE Communications Surveys and Tutorials, 2024, v. 26, n. 3, p. 1560-1605-
dc.identifier.urihttp://hdl.handle.net/10722/353132-
dc.description.abstractExtremely large-scale multiple-input-multiple-output (XL-MIMO), which offers vast spatial degrees of freedom, has emerged as a potentially pivotal enabling technology for the sixth generation (6G) of wireless mobile networks. With its growing significance, both opportunities and challenges are concurrently manifesting. This paper presents a comprehensive survey of research on XL-MIMO wireless systems. In particular, we introduce four XL-MIMO hardware architectures: uniform linear array (ULA)-based XL-MIMO, uniform planar array (UPA)-based XL-MIMO utilizing either patch antennas or point antennas, and continuous aperture (CAP)-based XL-MIMO. We comprehensively analyze and discuss their characteristics and interrelationships. Following this, we introduce several electromagnetic characteristics and general distance boundaries in XL-MIMO. Given the distinct electromagnetic properties of near-field communications, we present a range of channel models to demonstrate the benefits of XL-MIMO. We further discuss and summarize signal processing schemes for XL-MIMO. It is worth noting that the low-complexity signal processing schemes and deep learning empowered signal processing schemes are reviewed and highlighted to promote the practical implementation of XL-MIMO. Furthermore, we explore the interplay between XL-MIMO and other emergent 6G technologies. Finally, we outline several compelling research directions for future XL-MIMO wireless communication systems.-
dc.languageeng-
dc.relation.ispartofIEEE Communications Surveys and Tutorials-
dc.subjectchannel modeling-
dc.subjectdeep learning-
dc.subjectnear-field communications-
dc.subjectsignal processing-
dc.subjectXL-MIMO-
dc.titleA Tutorial on Extremely Large-Scale MIMO for 6G: Fundamentals, Signal Processing, and Applications-
dc.typeArticle-
dc.description.naturelink_to_subscribed_fulltext-
dc.identifier.doi10.1109/COMST.2023.3349276-
dc.identifier.scopuseid_2-s2.0-85181574991-
dc.identifier.volume26-
dc.identifier.issue3-
dc.identifier.spage1560-
dc.identifier.epage1605-
dc.identifier.eissn1553-877X-

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