Mixing vector estimation in single channel blind source separation of angle modulated signal sources based on cumulant system of equations

  • Authors:
  • Hao Cheng;Bin Tang;Jingjing Du;Xiaojun Chen;Gaoyi Zhang

  • Affiliations:
  • School of Electronic Engineering, University of Electronic Science and Technology of China, Chengdu 610054, China;School of Electronic Engineering, University of Electronic Science and Technology of China, Chengdu 610054, China;School of Electronic Engineering, University of Electronic Science and Technology of China, Chengdu 610054, China;School of Electronic Engineering, University of Electronic Science and Technology of China, Chengdu 610054, China;School of Electronic Engineering, University of Electronic Science and Technology of China, Chengdu 610054, China

  • Venue:
  • Signal Processing
  • Year:
  • 2009

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Abstract

Unlike the traditional overdetermined or determined blind source separation (BSS), mixing matrix estimation and source recovery are not always coincident in underdetermined BSS. Aimed at the problem of single channel BSS, which is the extreme situation and most difficult case in underdetermined BSS, this paper proposes a mixing vector estimation algorithm for angle modulated signal sources based on a cumulant system of equations. The principle is that the mixing vector can be estimated by solving a cumulant system of equations derived from the probability density functions of the sources. This algorithm does not require specific information about the sources' modulation types or parameters and can be theoretically applied in conditions with any number of sources, even if their frequencies overlap. Experimental results show the estimation performance.