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An Efficient Nonlinear Quantized Constant Envelope Precoding for Massive MU-MIMO Systems

delete2024-01-01
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PRE
AI
R
Rui Liang
李辉 封面图
李辉 (Hui Li) *
张
张雯洁 (Wenjie Zhang)
C
Chenxi Liu
Y
Yunling Guo
DOI:10.1109/JSYST.2022.3165637delete
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摘要

摘要

En 中文
Massive multiuser multiple-input-multiple-output (MU-MIMO) systems are foreseen as the key technology in next-generation wireless communication systems. However, many radio-frequency (RF) chains will require high power consumption and lots of hardware cost. One of the practical solutions is using low-resolution discrete phase shifters (PSs) for each antenna and RF chain. This article designs a nonlinear quantized constant envelope precoding algorithm for MU-MIMO systems with low-resolution discrete PS at the base station. In this algorithm, the quantized constant envelope precoding problem is presented as a nonconvex optimization problem. The multiuser interference is minimized by solving the optimal precoded vector and the associated precoding factors. First, we consider relaxing the nonconvex constraint on the 1-bit quantized constant envelope precoding to a continuous set of convex constraints on the unit circle. Afterwards, the semidefinite relaxation method is used to tackle the equivalent 1-bit quantized precoding problem. We further extend the algorithm to provide multi-bit quantized constant envelop precoding. Finally, the simulations are carried out under various conditions and compared with the most advanced precoding methods. The results demonstrate that this algorithm achieves a comparable performance to the existing precoding methods. At the same time, the corresponding performance-complexity tradeoff is more conducive to the expansion of the proposed algorithm to the multibit case.
Keyword:
Precoding
Quantization (signal)
Downlink
Transmitting antennas
Symbols
Radio frequency
Power demand
Constant envelope
massive multiuser multiple-input-multiple-output (MU-MIMO)
precoding
quantization
semidefinite relaxation (SDR)

期刊

I
IEEE Open Journal of Circuits and Systems
IF:
2.4
论文数:
4.5K
被引数:
387

机构

S
shaanxi university of technology
学者数:
2.4K
论文数: 1.4K
被引数: 4
N
Northwestern Polytechnical University
学者数:
4.6W
论文数: 3.7W
被引数: 5.3W
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