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Lattice-Reduction-Aided Breadth-First Tree Searching Algorithm for MIMO Detection

delete2017-04-01
delete10
PRE
AI
J
Jinzhu Liu *
S
Song Xing
L
Lianfeng Shen
DOI:10.1109/LCOMM.2017.2648783delete
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摘要

摘要

En 中文
We propose a lattice-reduction (LR)-aided breadthfirst tree searching algorithm for MIMO detection achieving nearoptimal performance with very low complexity. At each level of the tree in the search, only the paths whose accumulated metrics satisfy a particular restriction condition will be kept as the candidates. Furthermore, the number of child nodes expanded on each parent node, and the maximum number of candidates preserved at each level, are also restricted, respectively. All these measures ensure the proposed algorithm reaching a preset near-optimal performance and achieving very low average and maximum computational complexity. Simulation results verify the proposed algorithm's higher efficiency in terms of the performance/complexity tradeoff than the existing LR-aided K-best detectors and LR-aided fixed-complexity sphere decoders.
Keyword:
Lattice reduction
MIMO
breadth-first tree searching
sphere decoding
K-best detector
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期刊

IEEE Communications Letters 封面图
IEEE Communications Letters
IF:
4.4
论文数:
1.3W
被引数:
2.2W

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California State University System 封面图
California State University System
学者数:
2.8W
论文数: 2.4W
被引数: 457
C
California State University Los Angeles
学者数:
1.0K
论文数: 718
被引数: 1.6K
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