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An Optimum ICA Based Multiuser Data Separation for Short Message Service

  • Mahdi Khosravy
  • Mohammad Reza Alsharif
  • Katsumi Yamashita
Part of the Lecture Notes in Computer Science book series (LNCS, volume 6059)

Abstract

This paper presents a new algorithm for efficient separation of short messages which are mixed in a multi user short message system. Separation of mixed random binary sequences of data is more difficult than mixed sequences of multivalued signals. The proposed algorithm applies Kullback leibler independent component analysis (ICA) over mixed binary sequences of received data. Normally, the length of binary codes of short messages are less than the required length that makes ICA algorithm sufficiently work. To overcome this problem, a random binary tail is inserted after each user short message at the transmitter side. The inserted tails for different users are acquired in a way to conclude the least correlation between them. The optimum choice of random binary tail not only increase the performance of separation by increasing the data length but also by minimizing the correlation between multiuser data.

Keywords

Short message service independent component analysis Kullback Leibler MIMO 

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Copyright information

© Springer-Verlag Berlin Heidelberg 2010

Authors and Affiliations

  • Mahdi Khosravy
    • 1
  • Mohammad Reza Alsharif
    • 1
  • Katsumi Yamashita
    • 2
  1. 1.Department of Information Engineering, Faculty of EngineeringUniversity of the RyukyusOkinawaJapan
  2. 2.Graduate School of EngineeringOsaka Prefecture UniversityOsakaJapan

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