DocumentCode :
3607126
Title :
Lattice reduction-ordered successive interference cancellation detection algorithm for multiple-input–multiple-output system
Author :
Yunchao Song ; Chen Liu ; Feng Lu
Author_Institution :
Sch. of Electron. Sci. & Eng., Nanjing Univ. of Posts & Telecommun., Nanjing, China
Volume :
9
Issue :
7
fYear :
2015
Firstpage :
553
Lastpage :
561
Abstract :
Lattice reduction (LR) is a powerful technique for improving the performance of linear multiple-input-multiple-output detection methods. The efficient LR algorithms can largely improve the performance of the linear detectors (LDs). Note that the ordered successive interference cancellation (OSIC) system can decrease the interference between antennas and provide performance gain of the LDs. In this paper, a novel LR-aided algorithm called NLR-OSIC improving the performance of the OSIC system has been proposed. Most existing LR algorithms are designed to improve the orthogonality of channel matrices, which is not directly related to the error performance of the OSIC system. While the authors´ algorithm maximises the signal-to-interference-plus-noise ratio (SINR) of the detected symbol in each stage of the OSIC system, thus exhibiting improved error rate than the previous LR-aided LDs and their corresponding OSIC algorithms. In each stage, the authors verify that maximising the SINR of the detected symbol can be formulated as a shortest vector problem which is solved by a suboptimal algorithm in this study. In the end of this study, the error rate performance of the proposed algorithm as well as the required complexity has been demonstrated through extensive computer simulations.
Keywords :
MIMO communication; antenna radiation patterns; interference suppression; matrix algebra; radiofrequency interference; signal detection; wireless channels; LR-aided LD; NLR-OSIC system; SINR; channel matrix orthogonality; lattice reduction algorithm; linear detector; multiple input multiple output antenna system; rdered successive interference cancellation detection algorithm; shortest vector problem; signal-to-interference-plus-noise ratio; suboptimal algorithm;
fLanguage :
English
Journal_Title :
Signal Processing, IET
Publisher :
iet
ISSN :
1751-9675
Type :
jour
DOI :
10.1049/iet-spr.2014.0132
Filename :
7277328
Link To Document :
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