Denoising Higher-Order Moments for Blind Digital Modulation Identification in Multiple-Antenna Systems

被引：11

作者：

Kharbech, Sofiane ^{[1
,2
]}

Simon, Eric Pierre ^{[1
]}

Belazi, Akram ^{[3
]}

Xiang, Wei ^{[4
,5
]}

机构：

[1] Univ Lille, CNRS, Lab IEMN IRCICA, UMR 8520, F-59100 Lille, France

[2] Tunis El Manar Univ, Lab SysCom ENIT LR 99 ES21, Tunis 1002, Tunisia

[3] Tunis El Manar Univ, Lab RISC LR 16 ES07, Tunis 1002, Tunisia

[4] James Cook Univ, Coll Sci & Engn, Cairns, Qld 4870, Australia

[5] Beijing Informat Sci & Technol Univ, Beijing 100192, Peoples R China

来源：

IEEE WIRELESS COMMUNICATIONS LETTERS | 2020年 / 9卷 / 06期

基金：

北京市自然科学基金;

关键词：

Noise reduction; MIMO communication; Receiving antennas; Estimation; Digital modulation; Higher order statistics; Cognitive radio; modulation identification; higher-order statistics; multiple-antenna systems; denoising features; CLASSIFICATION;

D O I：

10.1109/LWC.2020.2969157

中图分类号：

TP [自动化技术、计算机技术];

学科分类号：

0812 ;

摘要：

This letter proposes a new technique that substantially improves blind digital modulation identification (DMI) algorithms that are based on higher-order statistics (HOS). The proposed technique takes advantage of noise power estimation to make an offset on higher-order moments (HOM), thus getting an estimate of noise-free HOM. When tested for multiple-antenna systems, the proposed method outperforms other DMI algorithms, in terms of identification accuracy, that are based only on cumulants or do not consider HOM denoising, even for a receiver with impairments. The improvement is achieved with the same order of complexity of the common HOS-based DMI algorithms in the same context.

引用

页码：765 / 769

页数：5

共 19 条

[1] Automatic Modulation Classification Using Deep Learning Based on Sparse Autoencoders With Nonnegativity Constraints [J].

Ali, Afan ;

Fan Yangyu .

IEEE SIGNAL PROCESSING LETTERS, 2017, 24 (11) :1626-1630

[2] Efficient and Reliable Modulation Classification for MIMO Systems [J].

Bahloul, Mohammad Rida ;

Yusoff, Mohd Zuki ;

Abdel-Aty, Abdel-Haleem ;

Saad, Mohd Naufal ;

Laouiti, Anis .

ARABIAN JOURNAL FOR SCIENCE AND ENGINEERING, 2017, 42 (12) :5201-5209

[3] DETECTION OF THE NUMBER OF SIGNALS - A PREDICTED EIGEN-THRESHOLD APPROACH [J].

CHEN, WG ;

WONG, KM ;

REILLY, JP .

IEEE TRANSACTIONS ON SIGNAL PROCESSING, 1991, 39 (05) :1088-1098

[4] Survey of automatic modulation classification techniques: classical approaches and new trends [J].

Dobre, O. A. ;

Abdi, A. ;

Bar-Ness, Y. ;

Su, W. .

IET COMMUNICATIONS, 2007, 1 (02) :137-156

[5] Signal Identification for Multiple-Antenna Wireless Systems: Achievements and Challenges [J].

Eldemerdash, Yahia A. ;

Dobre, Octavia A. ;

Oner, Menguc .

IEEE COMMUNICATIONS SURVEYS AND TUTORIALS, 2016, 18 (03) :1524-1551

[6] Blind Digital Modulation Identification for Spatially-Correlated MIMO Systems [J].

Hassan, Kais ;

Dayoub, Iyad ;

Hamouda, Walaa ;

Nzeza, Crepin Nsiala ;

Berbineau, Marion .

IEEE TRANSACTIONS ON WIRELESS COMMUNICATIONS, 2012, 11 (02) :683-693

[7] A simplified constant modulus algorithm for blind recovery of MIMO QAM and PSK signals: A criterion with convergence analysis [J].

Ikhlef, Aissa ;

Le Guennec, Daniel .

EURASIP JOURNAL ON WIRELESS COMMUNICATIONS AND NETWORKING, 2007,

[8] DISCRETE SIMULATION OF COLORED NOISE AND STOCHASTIC-PROCESSES AND 1/F(ALPHA) POWER-LAW NOISE GENERATION [J].

KASDIN, NJ .

PROCEEDINGS OF THE IEEE, 1995, 83 (05) :802-827

[9]

Kharbech Sofiane, 2013, Communication Technologies for Vehicles. 5th International Workshop, Nets4Cars/Nets4Trains 2013. Proceedings, P232, DOI 10.1007/978-3-642-37974-1_19

[10] On classifiers for blind feature-based automatic modulation classification over multiple-input-multiple-output channels [J].

Kharbech, Sofiane ;

Dayoub, Iyad ;

Zwingelstein-Colin, Marie ;

Simon, Eric Pierre .

IET COMMUNICATIONS, 2016, 10 (07) :790-795

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