Hybrid Precoding Design for Adaptive Subconnected Structures in Millimeter-Wave MIMO Systems

Hybrid precoding design for an adaptive subconnected structure offers a compromise between hardware complexity and spectral efficiency in massive multiple-input multiple-output (MIMO) systems at millimeter-wave (mmWave) frequencies. This paper focuses on the impacts of the partial antenna connection...

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Vydáno v:IEEE systems journal Ročník 13; číslo 1; s. 137 - 146
Hlavní autoři: Hu, Chia-Chang, Zhang, Jia-Hua
Médium: Journal Article
Jazyk:angličtina
Vydáno: New York IEEE 01.03.2019
The Institute of Electrical and Electronics Engineers, Inc. (IEEE)
Témata:
Achievable sum-rate (ASR)
Adaptive systems
Algorithms
antenna selection (AS)
Antennas
Computer simulation
Hardware
hybrid precoding design
Hybrid systems
Mapping
Millimeter waves
millimeter-wave (mmWave) communication
MIMO (control systems)
MIMO communication
multiple-input multiple-output (MIMO)
Optimized production technology
Precoding
Radio frequency
Smart structures
ISSN:1932-8184, 1937-9234
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Shrnutí:Hybrid precoding design for an adaptive subconnected structure offers a compromise between hardware complexity and spectral efficiency in massive multiple-input multiple-output (MIMO) systems at millimeter-wave (mmWave) frequencies. This paper focuses on the impacts of the partial antenna connections on the achievable sum-rate (ASR) performance for the uniform linear array and uniform square planar array configurations in mmWave networks. The subarray architectures consist of the overlapped, interlaced, and dynamically selective subset schemes in mmWave MIMO systems. Notably, on the basis of the ASR maximization, the Gram-Schmidt (GS)-based antenna selection (AS) algorithm is used to acquire an appropriate antenna subset and magnificently simplifies the radio frequency chain-antenna mapping operation in the sequel. Finally, simulation results demonstrate that an adaptive subarray architecture in conjunction with the GS-based AS search strategy is able to accomplish the ASR performance approaching the fully connected architecture with an alleviated demand on both computation and hardware complexities.
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ISSN:1932-8184
1937-9234
DOI:10.1109/JSYST.2018.2816927