Modulation classification for MIMO systems: State of the art and research directions

被引：11

作者：

Bahloul, Mohammad Rida ^{[1
]}

Yusoff, Mohd Zuki ^{[1
]}

Abdel-Aty, Abdel-Haleem ^{[2
]}

Saad, M. Naufal M. ^{[1
]}

Al-Jemeli, Marwan ^{[3
]}

机构：

[1] Univ Teknol PETRONAS, Dept Elect & Elect Engn, Ctr Intelligent Signal & Imaging Res, Perak, Malaysia

[2] Al Azhar Univ, Fac Sci, Phys & Comp Dept, Assiut, Egypt

[3] Limkokwing Univ Creat Technol, Fac Informat & Commun Technol, Cyberjaya, Malaysia

来源：

CHAOS SOLITONS & FRACTALS | 2016年 / 89卷

关键词：

Modulation classification; Multiple-Input Multiple-Output; Statistical features; Pattern recognition; MAXIMUM-LIKELIHOOD; EXPECTATION MAXIMIZATION; WIRELESS SYSTEMS; NEURAL-NETWORKS; CHANNELS; IDENTIFICATION; INTERFERENCE; RECOGNITION; ALGORITHM; NOISE;

D O I：

10.1016/j.chaos.2016.02.029

中图分类号：

O1 [数学];

学科分类号：

0701 ; 070101 ;

摘要：

Blind techniques and algorithms for Multiple-Input Multiple-Output (MIMO) signals interception have recently attracted a great deal of research efforts. This is due to their important applications in the military and civil telecommunications domains. One essential step in the signal interception process is to blindly recognize the modulation scheme of the MIMO signals. This process is formally called Modulation Classification (MC). This paper discusses the modulation classification for MIMO systems and presents a comprehensive and critical literature review of the existing MC algorithms for MIMO systems; where possible, gaps in the knowledge base are identified and future directions for the research work are suggested. (C) 2016 Elsevier Ltd. All rights reserved.

引用

页码：497 / 505

页数：9

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