Journal
IEEE TRANSACTIONS ON WIRELESS COMMUNICATIONS
Volume 22, Issue 5, Pages 3280-3295Publisher
IEEE-INST ELECTRICAL ELECTRONICS ENGINEERS INC
DOI: 10.1109/TWC.2022.3217145
Keywords
Radio frequency; Array signal processing; MIMO communication; Millimeter wave communication; Transmission line matrix methods; Optimization; Baseband; Multi-user multiple-input-multiple-output millimeter-wave communications; hybrid beamforming; analog beamforming with b-bit resolution; zero-forcing beamforming; regularized zero-forcing beamforming; Brunn-Minkowski geometry; mixed discrete continuous optimization; scalable complexity
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This paper focuses on hybrid beamforming for multi-user MIMO millimeter-wave communications, combining analog beamforming (ABF) and digital baseband beamforming (DBF). ABF reduces power consumption at the base station (BS) by using a limited number of radio frequency (RF) chains and finite-resolution phase-shifters, while DBF employs zero-forcing beamforming (ZFB) or regularized zero-forcing beamforming (RZFB) to mitigate multi-user interference. The joint design of ABF and DBF presents a computationally challenging optimization problem, and this paper develops efficient algorithms to solve it. Additionally, a new class of MU RZFB is proposed for achieving higher rates, and simulations confirm the effectiveness of the proposed algorithms and the advantages of the conceived RZFB.
This paper considers hybrid beamforming consisting of analog beamforming (ABF) coupled with digital baseband beamforming (DBF) which is designed for multi-user (MU) multiple input multiple output (MIMO) millimeter-wave (mmWave) communications. ABF uses a limited number of radio frequency (RF) chains and finite-resolution phase-shifters to alleviate the power consumption at the base station (BS), while DBF uses either zero-forcing beamforming (ZFB) or regularized zero forcing beamforming (RZFB) to restrain MU interference. The joint design of ABF and DBF constitutes a computationally challenging mixed discrete continuous optimization problem. The paper develops efficient algorithms for its solution, which iterate scalable-complex expressions. Furthermore, we conceive a new class of MU RZFB for attaining higher rates. Simulations are provided to demonstrate the viability of the proposed algorithms and the advantages of the conceived RZFB.
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