Hybrid Precoding for Massive MIMO with Low Rank Channels: A Two-Stage User Scheduling Approach

Ahmed Almradi, Michalis Matthaiou, Pei Xiao, Vincent F. Fusco

Research output: Contribution to journalArticlepeer-review

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To fully reap the benefits of massive multiple-input multiple-output hybrid analog and digital precoding in frequency division duplexing single-cell systems, a two-stage precoder is developed utilizing the signal-to-leakage-plus-noise ratio metric. The main idea of this technique is to jointly design the analog precoder based only on the long-term channel statistics information at the transmitter, i.e., the channel mean and reconstructed reduced rank covariance statistics, while the digital precoder is designed based on the instantaneous channel state information of the reduced dimensionality effective reconstructed channel. Consequently, we can significantly reduce the downlink training and uplink feedback overhead analogously to the rank of the resultant effective channel. The two extremes of full channel state information at the transmitter (CSIT) and statistical CSIT are also investigated. The performance gap between the full and statistical CSIT corroborates the importance of the proposed two-stage CSIT approach. These precoders are then extended to multi-cell systems. It is shown that the digital baseband precoder design problem reduces to the generalized Rayleigh quotient problem, while the analog precoder design problem reduces to the quotient trace problem, also known as the ratio trace problem. These dimensionality reduction problems are solved via the generalized eigenvalue decomposition method. Finally, in the presence of multiuser diversity where only a subset of the users are scheduled, to considerably alleviate the channel estimation and feedback overhead burden, a low-complexity one-stage and two-stage CSIT joint user scheduler and precoder algorithms are developed.
Original languageEnglish
Pages (from-to)4816-4831
Number of pages6
JournalIEEE Transactions on Communications
Issue number8
Early online date06 May 2020
Publication statusPublished - Aug 2020


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