Channel-Statistics-Based Hybrid Precoding for Millimeter-Wave MIMO Systems With Dynamic Subarrays

This paper investigates the hybrid precoding design for millimeter wave (mmWave) multiple-input-multiple-output (MIMO) systems with finite-alphabet inputs. The mmWave MIMO system employs partially-connected hybrid precoding architecture with dynamic subarrays, where each radio frequency (RF) chain i...

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Vydané v:IEEE transactions on communications Ročník 67; číslo 6; s. 3991 - 4003
Hlavní autori: Jin, Juening, Xiao, Chengshan, Chen, Wen, Wu, Yongpeng
Médium: Journal Article
Jazyk:English
Vydavateľské údaje: New York IEEE 01.06.2019
The Institute of Electrical and Electronics Engineers, Inc. (IEEE)
Predmet:
Algorithms
Antenna accessories
Antennas
Approximation
Approximation algorithms
Ascent
Chains
Chemical partition
Codes
Combinatorial analysis
Complexity
Computation
finite-alphabet inputs
Hybrid precoding
Hybrid systems
Lower bounds
matrix factorization
Millimeter waves
MIMO (control systems)
MIMO communication
Mutual information
nonconvex optimization
Optimization
Partitions
Precoding
Radio frequency
ISSN:0090-6778, 1558-0857
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Shrnutí:This paper investigates the hybrid precoding design for millimeter wave (mmWave) multiple-input-multiple-output (MIMO) systems with finite-alphabet inputs. The mmWave MIMO system employs partially-connected hybrid precoding architecture with dynamic subarrays, where each radio frequency (RF) chain is connected to a dynamic subset of antennas. We consider the design of analog and digital precoders utilizing statistical and/or mixed channel state information (CSI), which involve solving an extremely difficult problem in theory: First, designing the optimal partition of antennas over RF chains is a combinatorial optimization problem, whose optimal solution requires an exhaustive search over all antenna partitioning solutions; Second, the average mutual information under mmWave MIMO channels lacks closed-form expression and involves prohibitive computational burden; and Third, the hybrid precoding problem with given partition of antennas is nonconvex with respect to the analog and digital precoders. To address these issues, this paper first presents a simple criterion and the corresponding low complexity algorithm to design the optimal partition of antennas using statistical CSI. Then, it derives the lower bound and its approximation for the average mutual information, in which the computational complexity is greatly reduced compared to calculating the average mutual information directly. In addition, it also shows that the lower bound with a constant shift offers a very accurate approximation to the average mutual information. This paper further proposes utilizing the lower bound approximation as a low-complexity and accurate alternative for developing a manifold-based gradient ascent algorithm to find near-optimal analog and digital precoders. Several numerical results are provided to show that our proposed algorithm outperforms the existing hybrid precoding algorithms.
Bibliografia:ObjectType-Article-1
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content type line 14
ISSN:0090-6778
1558-0857
DOI:10.1109/TCOMM.2019.2899628