Switch and Inverter Based Hybrid Precoding Algorithm for mmWave Massive MIMO System: Analysis on Sum-Rate and Energy-Efficiency

In millimeter-wave (mmWave)-based massive multiple-input-multiple-output (MIMO) systems, hybrid precoding is considered one of the indispensable techniques in the next generation wireless communication systems (5G) to reduce the number of radio-frequency (RF) chains. However, the existing hybrid pre...

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Bibliographic Details
Published in:IEEE access Vol. 7; pp. 49448 - 49455
Main Authors: Tian, Mengqian, Zhang, Jianing, Zhao, Yu, Yuan, Lianjun, Yang, Jie, Gui, Guan
Format: Journal Article
Language:English
Published: Piscataway IEEE 2019
The Institute of Electrical and Electronics Engineers, Inc. (IEEE)
Subjects:
Algorithms
Antennas
Computer architecture
energy-efficiency
Entropy (Information theory)
hybrid precoding
Hybrid systems
Inverters
Millimeter waves
MIMO (control systems)
MIMO communication
mmWave massive MIMO
Parameters
performance analysis
Precoding
Radio frequency
sum-rate
Switches
Wireless communication systems
Wireless communications
ISSN:2169-3536, 2169-3536
Online Access:Get full text
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Summary:In millimeter-wave (mmWave)-based massive multiple-input-multiple-output (MIMO) systems, hybrid precoding is considered one of the indispensable techniques in the next generation wireless communication systems (5G) to reduce the number of radio-frequency (RF) chains. However, the existing hybrid precoding techniques often cause performance loss. To solve this problem, the switch and inverter (SI)-based hybrid precoding architecture has been proposed recently as an energy-efficient solution for these challenges. In this paper, a detailed performance analysis on sum-rate as well as energy-efficiency is provided through simulation on the two-stage hybrid precoding, antenna selection (AS)-based hybrid precoding, and adaptive cross-entropy (ACE)-based hybrid precoding. It is aimed to prove that the performance of the ACE-based scheme is much superior to that of the others with the limited ranges of values of all parameters. At last, the suitable parameters are determined and we prove that they can lead to the optimal performance.
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ISSN:2169-3536
2169-3536
DOI:10.1109/ACCESS.2019.2910094