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- Publisher Website: 10.1109/COMST.2023.3349276
- Scopus: eid_2-s2.0-85181574991
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Article: A Tutorial on Extremely Large-Scale MIMO for 6G: Fundamentals, Signal Processing, and Applications
Title | A Tutorial on Extremely Large-Scale MIMO for 6G: Fundamentals, Signal Processing, and Applications |
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Authors | |
Keywords | channel modeling deep learning near-field communications signal processing XL-MIMO |
Issue Date | 2024 |
Citation | IEEE Communications Surveys and Tutorials, 2024, v. 26, n. 3, p. 1560-1605 How to Cite? |
Abstract | Extremely 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 Identifier | http://hdl.handle.net/10722/353132 |
DC Field | Value | Language |
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dc.contributor.author | Wang, Zhe | - |
dc.contributor.author | Zhang, Jiayi | - |
dc.contributor.author | Du, Hongyang | - |
dc.contributor.author | Niyato, Dusit | - |
dc.contributor.author | Cui, Shuguang | - |
dc.contributor.author | Ai, Bo | - |
dc.contributor.author | Debbah, Merouane | - |
dc.contributor.author | Letaief, Khaled B. | - |
dc.contributor.author | Poor, H. Vincent | - |
dc.date.accessioned | 2025-01-13T03:02:14Z | - |
dc.date.available | 2025-01-13T03:02:14Z | - |
dc.date.issued | 2024 | - |
dc.identifier.citation | IEEE Communications Surveys and Tutorials, 2024, v. 26, n. 3, p. 1560-1605 | - |
dc.identifier.uri | http://hdl.handle.net/10722/353132 | - |
dc.description.abstract | Extremely 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.language | eng | - |
dc.relation.ispartof | IEEE Communications Surveys and Tutorials | - |
dc.subject | channel modeling | - |
dc.subject | deep learning | - |
dc.subject | near-field communications | - |
dc.subject | signal processing | - |
dc.subject | XL-MIMO | - |
dc.title | A Tutorial on Extremely Large-Scale MIMO for 6G: Fundamentals, Signal Processing, and Applications | - |
dc.type | Article | - |
dc.description.nature | link_to_subscribed_fulltext | - |
dc.identifier.doi | 10.1109/COMST.2023.3349276 | - |
dc.identifier.scopus | eid_2-s2.0-85181574991 | - |
dc.identifier.volume | 26 | - |
dc.identifier.issue | 3 | - |
dc.identifier.spage | 1560 | - |
dc.identifier.epage | 1605 | - |
dc.identifier.eissn | 1553-877X | - |