Alternating Minimization Algorithms for Hybrid Precoding in Millimeter Wave MIMO Systems

By Xianghao Yu, Juei-Chin Shen, Jun Zhang, Khaled Ben Letaief. IEEE Journal on Selected Topics in Signal Processing, 2016

1,344 citations recorded by the source corpus.

Millimeter wave (mmWave) communications has been regarded as a key enabling technology for 5G networks, as it offers orders of magnitude greater spectrum than current cellular bands. In contrast to conventional multiple-input-multiple-output (MIMO) systems, precoding in mmWave MIMO cannot be performed entirely at baseband using digital precoders, as only a limited number of signal mixers and analog-to-digital converters can be supported considering their cost and power consumption. As a cost-effective alternative, a hybrid precoding transceiver architecture, combining a digital precoder and an analog precoder, has recently received considerable attention. However, the optimal design of such hybrid precoders has not been fully understood. In this paper, treating the hybrid precoder design as a matrix factorization problem, effective alternating minimization (AltMin) algorithms will be proposed for two different hybrid precoding structures, i.e., the fully-connected and partially-connected structures. In particular, for the fully-connected structure, an AltMin algorithm based on manifold optimization is proposed to approach the performance of the fully digital precoder, which, however, has a high complexity. Thus, a low-complexity AltMin algorithm is then proposed, by enforcing an orthogonal constraint on the digital precoder. Furthermore, for the partially-connected structure, an AltMin algorithm is also developed with the help of semidefinite relaxation. For practical implementation, the proposed AltMin algorithms are further extended to the broadband setting with orthogonal frequency division multiplexing modulation. Simulation results will demonstrate significant performance gains of the proposed AltMin algorithms over existing hybrid precoding algorithms. Moreover, based on the proposed algorithms, simulation comparisons between the two hybrid precoding structures will provide valuable design insights.

Subfields: Electrical and Electronic Engineering

View Paper: https://www.semanticscholar.org/paper/f349e15eec9e5f2cf7462007ac8cb289f463abe9

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Citations in the corpus

Enabling Secure Wireless Communications via Intelligent Reflecting Surfaces (2019, background): “BCD has been shown to be a widely applicable and empirically successful approach in many applications [11], [12], and typically leads to a sub-optimal solution for nonconvex problems.”
A Survey on Hybrid Beamforming Techniques in 5G: Architecture and System Model Perspectives (2018, methodology): “In [104], the hybrid precoder design is considered as a matrix factorization problem.”
A Survey on Mobile Edge Computing: The Communication Perspective (2017, background): “exploiting new spectrum resources [65], [66], designing novel transceiver architectures [67]–[69] and network paradigms [70], [71] to improve the spectrum efficiency,”
Robust and Secure Wireless Communications via Intelligent Reflecting Surfaces (2019, methodology): “It has been successfully applied to several wireless communication design problems such as hybrid precoding [39], resource allocation [40], and IRS-enabled wireless communication [1].”
A Comprehensive Survey on Millimeter Wave Communications for Fifth-Generation Wireless Networks: Feasibility and Challenges (2020, methodology): “Some of the mmWave drawbacks include: 1) Manufacturing the small mmWave components requires more precision and hence, increased costs [2], [13], [14]; 2) It encounters low sensitivity in the receiving system resulting from the reduced energy managed by the small antenna size [15].”
Near-Field Communications: A Tutorial Review (2023, methodology): “In particular, several methods have been proposed to solve problem (68) through orthogonal matching pursuit (OMP) [47], manifold optimization [48], and block coordinate descent (BCD) [49].”
A Survey on Millimeter-Wave Beamforming Enabled UAV Communications and Networking (2021, background): “constraint due to the hardware limit [196], [197].”
Weighted Sum-Rate Maximization for Reconfigurable Intelligent Surface Aided Wireless Networks (2019, methodology): “The formulated problem looks mathematically similar to the WSR maximization problem in the hybrid digital/analog precoding [27]–[29] in massive MIMO systems.”
Millimeter Wave Communications for Future Mobile Networks (2017, neutral): “Using a similar idea, there are some other advanced schemes proposed for N1 [164], [166], [167].”
MISO Wireless Communication Systems via Intelligent Reflecting Surfaces : (Invited Paper) (2019, background): “There are some recent applications of manifold optimization in wireless communications [13], [14].”
Integrated Sensing and Communications: Toward Dual-Functional Wireless Networks for 6G and Beyond (2021, background): “These techniques include but are not limited to, beam training, beam alignment, beam tracking, and beam management, all of which can be based on an HAD structure [39].”
Deep-Learning-Based Millimeter-Wave Massive MIMO for Hybrid Precoding (2019, neutral): “Also, for the sake of realizing high spectrum efficiency with low complexity, an alternating minimization scheme for effectively designing hybrid precoder was provided [10].”
Hybrid Analog and Digital Beamforming for mmWave OFDM Large-Scale Antenna Arrays (2017, methodology): “The algorithm in [19] seeks to minimize the norm distance between the optimal fully-digital beamformers and the overall hybrid beamformers instead of tackling the original problem of spectral efﬁciency maximization directly.”
Modeling and Analyzing Millimeter Wave Cellular Systems (2016, methodology): “The solutions in [103], [113], [115], [116], and [130]–[133] showed that hybrid precoding can generally achieve very good spectral efficiencies compared to the fully-digital SVD solution in mmWave systems, specially when the number of RF chains is close to the number of dominant channel paths.”
Beam Focusing for Near-Field Multi-User MIMO Communications (2021, methodology): “This strategy is quite often used for optimizing hybrid analog/digital systems, see, e.g., [19], [21], [36], [37].”
Multicell MIMO Communications Relying on Intelligent Reflecting Surfaces (2019, methodology): “2) Riemannian gradients: Since we optimize over the manifold space, we have to find the Riemannian gradient [12].”