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A Gradient-Based Optimum Block Adaptation ICA Technique for Interference Suppression in Highly Dynamic Communication Channels

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Abstract

The fast fixed-point independent component analysis (ICA) algorithm has been widely used in various applications because of its fast convergence and superior performance. However, in a highly dynamic environment, real-time adaptation is necessary to track the variations of the mixing matrix. In this scenario, the gradient-based online learning algorithm performs better, but its convergence is slow, and depends on a proper choice of convergence factor. This paper develops a gradient-based optimum block adaptive ICA algorithm (OBA/ICA) that combines the advantages of the two algorithms. Simulation results for telecommunication applications indicate that the resulting performance is superior under time-varying conditions, which is particularly useful in mobile communications.

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Correspondence to Wasfy B. Mikhael.

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Keywords

  • Independent Component Analysis
  • Mobile Communication
  • Fast Convergence
  • Online Learning
  • Dynamic Communication