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Stefan cel Mare
University of Suceava
Faculty of Electrical Engineering and
Computer Science
13, Universitatii Street
Suceava - 720229
ROMANIA

Print ISSN: 1582-7445
Online ISSN: 1844-7600
WorldCat: 643243560
doi: 10.4316/AECE


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  4/2014 - 12

A Fractional Lower Order Statistics-Based MIMO Detection Method in Impulse Noise for Power Line Channel

CHEN, Z. See more information about CHEN, Z. on SCOPUS See more information about CHEN, Z. on IEEExplore See more information about CHEN, Z. on Web of Science, GENG, X. See more information about  GENG, X. on SCOPUS See more information about  GENG, X. on SCOPUS See more information about GENG, X. on Web of Science, YIN, F. See more information about YIN, F. on SCOPUS See more information about YIN, F. on SCOPUS See more information about YIN, F. on Web of Science
 
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Download PDF pdficon (882 KB) | Citation | Downloads: 691 | Views: 3,068

Author keywords
alpha stable distribution, fractional lower order statistics, impulse noise, MIMO, power line channel

References keywords
communications(12), mimo(11), power(10), line(7), analysis(6), signal(5), performance(5), channel(5), theory(4), processing(4)
Blue keywords are present in both the references section and the paper title.

About this article
Date of Publication: 2014-11-30
Volume 14, Issue 4, Year 2014, On page(s): 81 - 86
ISSN: 1582-7445, e-ISSN: 1844-7600
Digital Object Identifier: 10.4316/AECE.2014.04012
Web of Science Accession Number: 000348772500012
SCOPUS ID: 84921689238

Abstract
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Impulse noise in power line communication (PLC) channel seriously degrades the performance of Multiple-Input Multiple-Output (MIMO) system. To remedy this problem, a MIMO detection method based on fractional lower order statistics (FLOS) for PLC channel with impulse noise is proposed in this paper. The alpha stable distribution is used to model impulse noise, and FLOS is applied to construct the criteria of MIMO detection. Then the optimal detection solution is obtained by recursive least squares algorithm. Finally, the transmitted signals in PLC MIMO system are restored with the obtained detection matrix. The proposed method does not require channel estimation and has low computational complexity. The simulation results show that the proposed method has a better PLC MIMO detection performance than the existing ones under impulsive noise environment.


References | Cited By  «-- Click to see who has cited this paper

[1] L. Stadelmeier, D. Schill, A. Schwager, D. Schneider, J. Speidel, "MIMO for inhome powerline communications," The 7th Int. ITG Conference on Source and Channel Coding, Ulm, Germany, 2008.

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[3] R. Hashmat, P. Pagani, T. Chonavel, "MIMO communications for inhome PLC networks: measurements and results up to 100MHz," IEEE Int. Symposium on Power Line Communications, Rio de Janeiro, Brazil, 2010.
[CrossRef] [SCOPUS Times Cited 104]


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[6] J. Wang, B. Daneshrad, "A comparative study of MIMO detection algorithms for wideband spatial multiplexing systems," IEEE Wireless Communications and Networking Conference, New Orleans, Louisiana, USA, 2005, vol.1, pp.408-413.
[CrossRef]


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[8] C. Siriteanu, X. Shi, Y. Miyanaga, "Analysis and simulation of MIMO zero-forcing detection performance for correlated and estimated Rician-fading channel," IEEE Communications Theory Workshop, Melbourne, Australian, 2011, pp.182-187.
[CrossRef] [SCOPUS Times Cited 6]


[9] N. Kim, Y. Lee, H. Park, "Performance analysis of MIMO system with linear MMSE receiver," IEEE Trans. on Wireless Communications, vol.7, no. 11, pp.4474-4478, 2008.
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[16] A. A. Mustafa, D. Hakan, S. Bulent, A. Emin, "Subspace-based frequency estimation of sinusoidal signals in alpha-stable noise," Signal Processing, vol.82, no.12, pp.1807-1827, 2002.
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[20] K. R. Borisagar, G. R. Kulkarni, "Simulation and comparative analysis of LMS and RLS algorithm using real time speech input signal," Global Journal of Researches in Engineering, vol.10, no.5, pp.44-47, 2010.

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References Weight

Web of Science® Citations for all references: 4,322 TCR
SCOPUS® Citations for all references: 5,525 TCR

Web of Science® Average Citations per reference: 173 ACR
SCOPUS® Average Citations per reference: 221 ACR

TCR = Total Citations for References / ACR = Average Citations per Reference

We introduced in 2010 - for the first time in scientific publishing, the term "References Weight", as a quantitative indication of the quality ... Read more

Citations for references updated on 2024-06-12 01:29 in 118 seconds.




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Faculty of Electrical Engineering and Computer Science
Stefan cel Mare University of Suceava, Romania


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