skip to main content
10.1145/1582379.1582700acmconferencesArticle/Chapter ViewAbstractPublication PagesiwcmcConference Proceedingsconference-collections
research-article

Detection and separation in space time block coding using noisy compound PCA - ICA model

Published: 21 June 2009 Publication History

Abstract

For increasing the capacity of the wireless channel, the Space -- Time Block Coding (STBC) has been proposed in the literature. The problem with such scheme is that the accurate channel state information is required. The channel is then estimated by transmitting the training sequences. Such channel estimation causes the spectral efficiency problem, i.e. the useful data rate is reduced. Likewise, the noise presence in the data affects the STBC performances. In this paper, we try to overcome these drawbacks by detecting and separating the transmitted symbols without channel estimation and by including the noise in the global model. So, the noisy compound PCA - ICA model for STBC is proposed here. Using the Bit Error Rate (BER) and Signal to Noise Ration (SNR) as criteria, the obtained simulation results show that these methods are very suitable for transmitted symbols detection and separation in the STBC context.

References

[1]
G. J. Foschini and M. J. Gans, "On limits of wireless communications in a fading environment when using multiple antennas," Wireless Personal Communications, Vol. 6, No. 3, March 1998, pp. 311--335.
[2]
I. E. Telatar, "Capacity of multi -- antenna Gaussian channels", European Transactions on Telecommunications, Vol. 10, No. 6, 1999, pp. 585--595.
[3]
D. Gesbert and J. Akhtar, "Breaking the barriers of Shannon's capacity: An overview of MIMO wireless system," Telektronikk Telenor Journal, January 2002.
[4]
S. Kim, J. Park and Y. Park, "MIMO partial parallel interference cancellation for Space Time Block Coded MIMO -- CDMA System," Information and Communication Engineering, Yeungnam University, Korea, 2006.
[5]
S. M. Alamouti, "A simple transmit diversity technique for wireless communications," IEEE J. Select Areas Commun., vol. 16, no. 8, 1998, pp. 1451--1458.
[6]
V. Tarokh, N. Seshadri, and A. R. Calderbank, "Space -- time codes for high data rate wireless communication: performance criterion and code construction," IEEE Transactions on Information Theory, Vol. 44, No. 2, 1998, pp. 744--765.
[7]
J. Liu, B. Gu, H. Xu and J. Qiao. "Blind detection of orthogonal space -- time block coding based on ICA Schemes," Advances in Neural Networks, Lecture Note on Computer Science, Springer - Verlag, Berlin Heidelberg, 2005, pp. 309--314.
[8]
H. Xu, J. Liu and M. Luganas, http://www.cttc.es/en/people/direction/person/malagunas.jsp"Beam space -- time block coding communication system based on ICA blind detection," In Proc. of the 3rd IEEE Sensor Array and Multichannel Signal Processing Workshop (SAM'2004), Sitges, Spain, July 18--21, 2004.
[9]
Y. Hu, and J. Nenghwang, Handbook of Neural Network Signal Processing, CRC Press, 2001.
[10]
A. Hyvarinen, J. Karhunen, and E. Oja, Independent Component Analysis, John Wiley, 2001.
[11]
J. Joutsensalo and T. Ristaniemi, "Learning algorithms for blind multiuser detection in CDMA downlink," In Proc. of the 9th IEEE Int. Symp. on Personal, Indoor, and Mobile Radio Communications (PIMRC'98), Boston, U.S.A, Sept. 1998, pp. 1040--1044.
[12]
T. Ristaniemi, K. Raju, J. Karhunen, and E. Oja, "ICA -- assisted inter -- cell -- interference cancellation in CDMA array systems," In Proc. of the 4th Int. Symp. on Independent Component Analysis and Blind Signal Separation (ICA'03), Nara, Japan, Apr. 2003.
[13]
B. Vucetic and J. Yuan, Space -- Time Coding, John Wiley & Sons, New York, NY, USA, 2003.
[14]
A. F. Naguib and A. R. Calderbank, "Space -- time coding and signal processing for high data rate wireless communications," 2001, pp. 13--34.
[15]
A. Mansour, "Batch mutually referenced separation algorithm for MIMO convolutive mixtures," Lecture Notes in Computer Science, Editor A. Prieto, Granada, Spain, 2004, pp. 453--460.
[16]
D. Obradovic, N. Madhu, and A. Szabo, "Independent component analysis for semi -- blind signal separation in MIMO mobile frequency selective communication channels," In Proc of IEEE Int. Joint Conf. on Neural Networks, Vol. 1, July 2004, pp. 25--29.
[17]
D. Knezevic, Blind source separation for signal processing applications, PhD Thesis, School of Electrical, Electronic and Computer Engineering, University of Western Australia, 2004.
[18]
J. Liu, A. P. Iserte, and M. A. Lagunas, "Blind separation of OSTBC signals using ICA neural networks," In Proc. of IEEE Int. Symp. on Signal Processing and Information Technology (ISSPIT'03), Darmstadt, Germany, Decmber 2003, pp. 502--505.
[19]
W. Y. Leong and J. Holmer, "Implementing ICA in blind multiuser detection", In Proc. of IEEE Int. Symp. on Communications and Information Technologies, Vol. 2, Sapporo, Japan, October 2004, pp. 947--952.
[20]
S. Chitroub, A. Houacine, and B. Sansal, "A New PCA-based method for data compression and enhancement of multi-frequency polarimetric SAR imagery," Intelligent Data Analysis, International Journal, Vol. 6, No. 2, 2002, pp. 385--403.
[21]
G. H. Golub and C. F. Van Loan, Matrix Computations, 2nd edition, Baltimore, MD: Johns Hopkins University Press, 1989.
[22]
J. F. Cardoso and B. H. Laheld, "Equivariant adaptive source separation," IEEE Trans. Signal Processing, Vol. 44, 1996, pp. 3017--3030.
[23]
A. Hyvärinen, "Fast and robust fixed - point algorithms for independent component. Analysis," IEEE Trans. on Neural Networks, Vol. 10. No. 3, 1999, pp. 626--634.
[24]
A. Hyvärinen, "Gaussian moments for noisy independent component analysis, "IEEE Signal Process. Lett., Vol. 6, No. 6, 1999, pp. 145--147.
[25]
C. W. Reed, and K. Yao, "Performance of Blind beamforming algorithms," In Proc. of Ninth IEEE Signal Processing Workshop, Portland, OR, USA, 1998, pp. 256 --259.
[26]
Z. Shi and C. Zhang, "Gaussian moments for noisy complexity pursuit," Neurocomputing, Vol. 69, 2005, pp. 917--921.

Index Terms

  1. Detection and separation in space time block coding using noisy compound PCA - ICA model

    Recommendations

    Comments

    Information & Contributors

    Information

    Published In

    cover image ACM Conferences
    IWCMC '09: Proceedings of the 2009 International Conference on Wireless Communications and Mobile Computing: Connecting the World Wirelessly
    June 2009
    1561 pages
    ISBN:9781605585697
    DOI:10.1145/1582379
    Permission to make digital or hard copies of all or part of this work for personal or classroom use is granted without fee provided that copies are not made or distributed for profit or commercial advantage and that copies bear this notice and the full citation on the first page. Copyrights for components of this work owned by others than ACM must be honored. Abstracting with credit is permitted. To copy otherwise, or republish, to post on servers or to redistribute to lists, requires prior specific permission and/or a fee. Request permissions from [email protected]

    Sponsors

    In-Cooperation

    Publisher

    Association for Computing Machinery

    New York, NY, United States

    Publication History

    Published: 21 June 2009

    Permissions

    Request permissions for this article.

    Check for updates

    Author Tags

    1. Independent Component Analysis (ICA)
    2. Principal Component Analysis (PCA)
    3. channel estimation
    4. multiple access interference (MAI)
    5. space-time block coding

    Qualifiers

    • Research-article

    Conference

    IWCMC '09
    Sponsor:

    Contributors

    Other Metrics

    Bibliometrics & Citations

    Bibliometrics

    Article Metrics

    • 0
      Total Citations
    • 126
      Total Downloads
    • Downloads (Last 12 months)1
    • Downloads (Last 6 weeks)1
    Reflects downloads up to 05 Mar 2025

    Other Metrics

    Citations

    View Options

    Login options

    View options

    PDF

    View or Download as a PDF file.

    PDF

    eReader

    View online with eReader.

    eReader

    Figures

    Tables

    Media

    Share

    Share

    Share this Publication link

    Share on social media