A stabilized multichannel fast RLS algorithm for adaptive transmultiplexer receivers

Dah Chung Chang, Hsien Cheng Chiu

Research output: Contribution to journalArticlepeer-review

5 Scopus citations


The transmultiplexer (TMUX) system has been studied for its application to multicarrier communications. The channel impairments including noise, interference, and distortion draw the need for adaptive reconstruction at the TMUX receiver. Among possible adaptive methods, the recursive least squares (RLS) algorithm is appealing for its good convergence rate and steady state performance. However, higher computational complexity due to the matrix operation is the drawback of utilizing RLS. A fast RLS algorithm used for adaptive signal reconstruction in the TMUX system is developed in this paper. By using the polyphase decomposition method, the adaptive receiver in the TMUX system can be formulated as a multichannel filtering problem, and the fast algorithm is obtained through the block Toeplitz matrix structure of received signals. In addition to the reduction of complexity, simulation results show that the adaptive TMUX receiver has a convergence rate close to that of the standard RLS algorithm and the performance approaches the minimum mean square error solution.

Original languageEnglish
Pages (from-to)845-867
Number of pages23
JournalCircuits, Systems, and Signal Processing
Issue number6
StatePublished - Dec 2009


  • Adaptive signal processing
  • Fast recursive least squares (FRLS)
  • Minimum mean square error
  • Multicarrier communications
  • Polyphase decomposition
  • Toeplitz matrix
  • Transmultiplexer


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