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Analog Versus Hybrid Precoding for Multiuser Massive MIMO with Quantized CSI Feedback
dc.contributor.author | Zhao, Yaqiong | |
dc.contributor.author | Xu, Wei | |
dc.contributor.author | Xu, Jindan | |
dc.contributor.author | Jin, Shi | |
dc.contributor.author | Wang, Kezhi | |
dc.contributor.author | Alouini, Mohamed-Slim | |
dc.date.accessioned | 2020-06-17T13:33:55Z | |
dc.date.available | 2020-06-17T13:33:55Z | |
dc.date.issued | 2020-06-01 | |
dc.identifier.uri | http://hdl.handle.net/10754/663650.1 | |
dc.description.abstract | In this letter, we study the performance of a downlink multiuser massive multiple-input multiple-output (MIMO) system with sub-connected structure over limited feedback channels. Tight rate approximations are theoretically analyzed for the system with pure analog precoding and hybrid precoding. The effect of quantized analog and digital precoding is characterized in the derived expressions. Furthermore, it is revealed that the pure analog precoding outperforms the hybrid precoding using maximal-ratio transmission (MRT) or zero forcing (ZF) under certain conditions, and we theoretically characterize the conditions in closed form with respect to signal-to-noise ratio (SNR), the number of users and the number of feedback bits. Numerical results verify the derived conclusions on both Rayleigh channels and mmWave channels. | |
dc.publisher | arXiv | |
dc.relation.url | https://arxiv.org/pdf/2006.00899 | |
dc.rights | Archived with thanks to arXiv | |
dc.title | Analog Versus Hybrid Precoding for Multiuser Massive MIMO with Quantized CSI Feedback | |
dc.type | Preprint | |
dc.contributor.department | Electrical Engineering Program | |
dc.contributor.department | Computer, Electrical and Mathematical Sciences and Engineering (CEMSE) Division | |
dc.eprint.version | Pre-print | |
dc.contributor.institution | National Mobile Communications Research Laboratory, Southeast University, Nanjing 210096, China. | |
dc.contributor.institution | National Mobile Communications Research Laboratory, Southeast University, Nanjing 210096, China, and is also with the Purple Mountain Laboratories, Nanjing 210000, China. | |
dc.contributor.institution | Department of Computer and Information Sciences, Northumbria University, Newcastle, UK. | |
dc.identifier.arxivid | 2006.00899 | |
kaust.person | Alouini, Mohamed-Slim | |
refterms.dateFOA | 2020-06-17T13:34:19Z |
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