Low Complexity Joint Hybrid Precoding Algorithm for Millimeter Wave MIMO Systems

Millimeter wave (mmWave) communications have been considered as a promising candidate for next generation network since it offers orders-of-magnitude wider underutilized spectrum than classical microwave bands. To combat the severe signal attenuation of the mmWave channel, hybrid precoding has recen...

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Bibliographic Details
Published in:IEEE access Vol. 6; pp. 56423 - 56432
Main Authors: Cui, Mingyang, Zou, Weixia, Wang, Ye, Zhang, Ran
Format: Journal Article
Language:English
Published: Piscataway IEEE 2018
The Institute of Electrical and Electronics Engineers, Inc. (IEEE)
Subjects:
Algorithms
Complexity
Complexity theory
coordinate descent method
equivalent channel
Iterative methods
joint hybrid precoding
Matching pursuit algorithms
Microwave attenuation
Millimeter waves
MIMO
MIMO (control systems)
MIMO communication
mmWave
Precoding
Radio frequency
Receivers
Transmission line matrix methods
ISSN:2169-3536, 2169-3536
Online Access:Get full text
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Summary:Millimeter wave (mmWave) communications have been considered as a promising candidate for next generation network since it offers orders-of-magnitude wider underutilized spectrum than classical microwave bands. To combat the severe signal attenuation of the mmWave channel, hybrid precoding has recently received extensive attention. In this paper, we transform the hybrid precoding problem and develop a low complexity joint hybrid precoding algorithm. First, the analog precoder and combiner are obtained by iterative updating using the coordinate descent method. Then, the joint design of the digital precoder and combiner are computed based on the obtained analog precoder and combiner. Simulation results demonstrate that the proposed algorithm approaches optimal unconstrained percoding performance with low complexity. Finally, we investigate the performance of the proposed algorithm for the practical setting, in which only the quantized analog components are available, and find that it is still effective even with coarse quantization.
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ISSN:2169-3536
2169-3536
DOI:10.1109/ACCESS.2018.2872771