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Deep Learning for Distributed Channel Feedback and Multiuser Precoding in FDD Massive MIMO
[article]
2021
arXiv
pre-print
This paper shows that deep neural network (DNN) can be used for efficient and distributed channel estimation, quantization, feedback, and downlink multiuser precoding for a frequency-division duplex massive multiple-input multiple-output system in which a base station (BS) serves multiple mobile users, but with rate-limited feedback from the users to the BS. A key observation is that the multiuser channel estimation and feedback problem can be thought of as a distributed source coding problem.
arXiv:2007.06512v2
fatcat:gtnq2adr4jeb5hg4prshc76ogq