Low complexity joint hybrid precoding for millimeter wave MIMO systems

In millimeter wave (mmWave) multiple-input multiple-output (MIMO) systems, hybrid precoding has been widely used to overcome the severe propagation loss. In order to improve the spectrum efficiency with low complexity, we propose a joint hybrid precoding algorithm for single-user mmWave MIMO systems...

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Vydáno v:China communications Ročník 16; číslo 2; s. 49 - 58
Hlavní autoři: Cui, Mingyang, Zou, Weixia
Médium: Journal Article
Jazyk:angličtina
Vydáno: China Institute of Communications 01.02.2019
State Key Lab. of Millimeter Waves, Southeast University, Nanjing 210096, China
Key Lab of Universal Wireless Communications, MOE, Beijing University of Posts and Telecommunications, Beijing 100876, China%Key Lab of Universal Wireless Communications, MOE, Beijing University of Posts and Telecommunications, Beijing 100876, China
Témata:
Baseband
Complexity theory
Eigenvalues and eigenfunctions
joint hybrid precoding
low complexity
millimeter wave
MIMO
MIMO communication
Precoding
Radio frequency
Transmitters
low complexity
joint hybrid precoding
millimeter wave
5G
MIMO
ISSN:1673-5447
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Popis
Shrnutí:In millimeter wave (mmWave) multiple-input multiple-output (MIMO) systems, hybrid precoding has been widely used to overcome the severe propagation loss. In order to improve the spectrum efficiency with low complexity, we propose a joint hybrid precoding algorithm for single-user mmWave MIMO systems in this paper. By using the concept of equivalent channel, the proposed algorithm skillfully utilizes the idea of alternating optimization to complete the design of RF precoder and combiner. Then, the baseband precoder and combiner are computed by calculating the singular value decomposition of the equivalent channel. Simulation results demonstrate that the proposed algorithm can achieve satisfactory performance with quite low complexity. Moreover, we investigate the effects of quantization on the analog components and find that the proposed scheme is effective even with coarse quantization.
ISSN:1673-5447
DOI:10.12676/j.cc.2019.02.003