A Family of Hybrid Analog-Digital Beamforming Methods for Massive MIMO Systems

In massive MIMO systems, hybrid beamforming is an essential technique for exploiting the potential array gain without using a dedicated RF chain for each antenna. In this paper, we consider the data phase in massive MIMO communication, where the transmitter and receiver use fewer RF chains than ante...

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Published in:	IEEE transactions on signal processing Vol. 67; no. 12; pp. 3243 - 3257
Main Authors:	Ioushua, Shahar Stein, Eldar, Yonina C.
Format:	Journal Article
Language:	English
Published:	New York IEEE 15.06.2019 The Institute of Electrical and Electronics Engineers, Inc. (IEEE)
Subjects:	Algorithms alternating minimization Antenna arrays Antennas Approximation Array signal processing Beamforming cellular communication Chains combining Complexity Complexity theory Hardware hybrid beamforming Hybrid systems low-complexity Massive multiple-input multiple-output (MIMO) MIMO communication Optimization Performance enhancement Phase shifters precoding Radio frequency ratio-trace minimization
ISSN:	1053-587X, 1941-0476
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Abstract	In massive MIMO systems, hybrid beamforming is an essential technique for exploiting the potential array gain without using a dedicated RF chain for each antenna. In this paper, we consider the data phase in massive MIMO communication, where the transmitter and receiver use fewer RF chains than antennas. We examine several different fully and partially connected schemes and consider the design of hybrid beamformers that minimize the estimation error in the data. For the hybrid precoder, we introduce a framework for approximating the optimal fully digital precoder with a feasible hybrid one. We exploit the fact that the fully digital precoder is unique only up to a unitary matrix and optimize over this matrix and the hybrid precoder alternately. Our alternating minimization of approximation gap (Alt-MaG) framework improves the performance over state-of-the-art methods with no substantial increase in complexity. In addition, we present a special case of Alt-MaG, minimal gap iterative quantization (MaGiQ), that results in low complexity and lower mean squared error (MSE) than other common methods, in the case of very few RF chains. MaGiQ is also shown to coincide with the optimal fully digital solution in some scenarios. For combiner design, we exploit the structure of the MSE objective and develop a greedy ratio trace maximization technique that achieves low MSE under various settings. All of our algorithms can be used with multiple hardware architectures.
AbstractList	In massive MIMO systems, hybrid beamforming is an essential technique for exploiting the potential array gain without using a dedicated RF chain for each antenna. In this paper, we consider the data phase in massive MIMO communication, where the transmitter and receiver use fewer RF chains than antennas. We examine several different fully and partially connected schemes and consider the design of hybrid beamformers that minimize the estimation error in the data. For the hybrid precoder, we introduce a framework for approximating the optimal fully digital precoder with a feasible hybrid one. We exploit the fact that the fully digital precoder is unique only up to a unitary matrix and optimize over this matrix and the hybrid precoder alternately. Our alternating minimization of approximation gap (Alt-MaG) framework improves the performance over state-of-the-art methods with no substantial increase in complexity. In addition, we present a special case of Alt-MaG, minimal gap iterative quantization (MaGiQ), that results in low complexity and lower mean squared error (MSE) than other common methods, in the case of very few RF chains. MaGiQ is also shown to coincide with the optimal fully digital solution in some scenarios. For combiner design, we exploit the structure of the MSE objective and develop a greedy ratio trace maximization technique that achieves low MSE under various settings. All of our algorithms can be used with multiple hardware architectures.
Author	Ioushua, Shahar Stein Eldar, Yonina C.
Author_xml	– sequence: 1 givenname: Shahar Stein orcidid: 0000-0001-8865-3791 surname: Ioushua fullname: Ioushua, Shahar Stein email: steinioushua@mail.tau.ac.il organization: Dept. of Electrical Engineering, Tel Aviv University, Tel Aviv, Israel – sequence: 2 givenname: Yonina C. orcidid: 0000-0003-4358-5304 surname: Eldar fullname: Eldar, Yonina C. email: yonina.eldar@weizmann.ac.il organization: Department of Mathematics and Computer Science, Weizmann Institute of Science, Rehovot, Israel
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SubjectTerms	Algorithms alternating minimization Antenna arrays Antennas Approximation Array signal processing Beamforming cellular communication Chains combining Complexity Complexity theory Hardware hybrid beamforming Hybrid systems low-complexity Massive multiple-input multiple-output (MIMO) MIMO communication Optimization Performance enhancement Phase shifters precoding Radio frequency ratio-trace minimization
Title	A Family of Hybrid Analog-Digital Beamforming Methods for Massive MIMO Systems
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