Non-Gaussian Signal Detection: How Much Can Massive MIMO Help?

2018 IEEE International Conference on Communications (ICC) ◽

10.1109/icc.2018.8423049 ◽

2018 ◽

Author(s):

Ture Peken ◽

Ravi Tandon ◽

Tamal Bose

Keyword(s):

Signal Detection ◽

Massive Mimo ◽

Gaussian Signal ◽

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Two-channel tests for common non-gaussian signal detection

IEE Proceedings F Radar and Signal Processing ◽

10.1049/ip-f-2.1993.0051 ◽

1993 ◽

Vol 140 (6) ◽

pp. 343 ◽

Author(s):

J.K. Tugnait

Keyword(s):

Signal Detection ◽

Gaussian Signal ◽

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Two-channel tests for common non-Gaussian signal detection

Proceedings of 27th Asilomar Conference on Signals, Systems and Computers ◽

10.1109/acssc.1993.342508 ◽

2002 ◽

Author(s):

J.K. Tugnait

Keyword(s):

Signal Detection ◽

Gaussian Signal ◽

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Non-Gaussian signal detection from multiple sensors using the bootstrap

Proceedings of ICICS, 1997 International Conference on Information, Communications and Signal Processing. Theme: Trends in Information Systems Engineering and Wireless Multimedia Communications (Cat. No.97TH8237) ◽

10.1109/icics.1997.647116 ◽

2002 ◽

Author(s):

Hwa-Tung Ong ◽

A.M. Zoubir

Keyword(s):

Signal Detection ◽

Multiple Sensors ◽

Gaussian Signal ◽

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Approximate CFAR signal detection low rank non-Gaussian interference

2001 IEEE Aerospace Conference Proceedings (Cat. No.01TH8542) ◽

10.1109/aero.2001.931489 ◽

2002 ◽

Author(s):

I.P. Kirsteins ◽

M. Rangaswamy

Keyword(s):

Signal Detection ◽

Low Rank ◽

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A complex-domain adaptive order statistic filter and its application to signal detection in non-Gaussian noise and clutter

10.1117/12.848550 ◽

2010 ◽

Author(s):

Manuel Fernández ◽

Tom Aridgides

Keyword(s):

Signal Detection ◽

Order Statistic ◽

Gaussian Noise ◽

Complex Domain ◽

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Kassam, S. A., Signal Detection in Non-Gaussian Noise. New York etc., Springer-Verlag 1988. IX, 234 pp., 38 figs., DM 98,—. ISBN 3-540-96680-3 (Springer Texts in Electrical Engineering)

ZAMM ‐ Journal of Applied Mathematics and Mechanics / Zeitschrift für Angewandte Mathematik und Mechanik ◽

10.1002/zamm.19910710106 ◽

1991 ◽

Vol 71 (1) ◽

pp. 36-36

Author(s):

N. Ahlbehrendet

Keyword(s):

New York ◽

Signal Detection ◽

Gaussian Noise ◽

Electrical Engineering ◽

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Application of adaptive neuro-fuzzy inference systems for analyzing non-Gaussian signal

2009 International Conference on Multimedia Computing and Systems ◽

10.1109/mmcs.2009.5256668 ◽

2009 ◽

Author(s):

S. Chabaa ◽

A. Zeroual ◽

J. Antari

Keyword(s):

Fuzzy Inference ◽

Fuzzy Inference Systems ◽

Neuro Fuzzy ◽

Gaussian Signal ◽

Non Gaussian ◽

Inference Systems

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An Optimum RBF Network for Signal Detection in Non-Gaussian Noise

Lecture Notes in Computer Science - Pattern Recognition and Machine Intelligence ◽

10.1007/11590316_44 ◽

2005 ◽

pp. 306-309 ◽

Author(s):

D. G. Khairnar ◽

S. N. Merchant ◽

U. B. Desai

Keyword(s):

Signal Detection ◽

Gaussian Noise ◽

Rbf Network ◽

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Near optimal low complex signal detection in Massive MIMO

2019 International Conference on Vision Towards Emerging Trends in Communication and Networking (ViTECoN) ◽

10.1109/vitecon.2019.8899562 ◽

2019 ◽

Author(s):

Chandrika Mitra ◽

Keerthi S. ◽

Kalapraveen Bagadi

Keyword(s):

Signal Detection ◽

Massive Mimo ◽

Complex Signal ◽

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Blind Signal Detection for Sparse Massive MIMO: Degrees of Freedom and Achievable Rates

GLOBECOM 2017 - 2017 IEEE Global Communications Conference ◽

10.1109/glocom.2017.8254877 ◽

2017 ◽

Author(s):

Jianwen Zhang ◽

Xiaojun Yuan ◽

Ying Jun Zhang

Keyword(s):

Signal Detection ◽

Massive Mimo ◽

Degrees Of Freedom ◽

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