A Tutorial on Extremely Large-Scale MIMO for 6G: Fundamentals, Signal Processing, and Applications
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arXiv
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| Autori principali: | , , , , , , , , |
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| Natura: | Preprint |
| Pubblicazione: |
2023
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| _version_ | 1866911746053111808 |
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| author | Wang, Zhe Zhang, Jiayi Du, Hongyang Niyato, Dusit Cui, Shuguang Ai, Bo Debbah, Mérouane Letaief, Khaled B. Poor, H. Vincent |
| author_facet | Wang, Zhe Zhang, Jiayi Du, Hongyang Niyato, Dusit Cui, Shuguang Ai, Bo Debbah, Mérouane Letaief, Khaled B. Poor, H. Vincent |
| contents | 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. |
| format | Preprint |
| id |
arxiv_https___arxiv_org_abs_2307_07340 |
| institution | arXiv |
| publishDate | 2023 |
| record_format | arxiv |
| spellingShingle | A Tutorial on Extremely Large-Scale MIMO for 6G: Fundamentals, Signal Processing, and Applications Wang, Zhe Zhang, Jiayi Du, Hongyang Niyato, Dusit Cui, Shuguang Ai, Bo Debbah, Mérouane Letaief, Khaled B. Poor, H. Vincent Information Theory Signal Processing 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. |
| title | A Tutorial on Extremely Large-Scale MIMO for 6G: Fundamentals, Signal Processing, and Applications |
| topic | Information Theory Signal Processing |
| url | https://arxiv.org/abs/2307.07340 |