arrow
Return

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
deleteOriginal
deleteOriginal request for help
deleteShare
deleteSave
Abstract

Abstract

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.
Keywords:
Lattice reduction
MIMO
breadth-first tree searching
sphere decoding
K-best detector
AI Summary

AI Summary

Key information extracted from the uploaded paper, including a brief overview, abstract, background, key highlights, visual analysis, and future outlook.

Journal

IEEE Communications Letters cover
IEEE Communications Letters
IF:
4.4
Papers:
1.3W
Citations:
2.2W

Organization

California State University System cover
California State University System
Scholars:
2.8W
Papers: 2.4W
Citations: 457
C
California State University Los Angeles
Scholars:
1.0K
Papers: 717
Citations: 1.6K