Skip to main content

Performance of Post-Demodulator Adaptive Filters for FSK Signals in a Multipath Environment


FSK continues to be an important component of modern communication systems, and discoveries of lower impact methods for mitigating performance degradation due to multipath propagation are needed in many application areas. Previous work suggested the benefit of a simple post-demodulator LMS filter but the focus was narrow and analysis was hindered by the nonlinearity of the demodulation process and the nonstationary signal environment. This paper significantly extends understanding of the post-demodulator filter and demonstrates that the statistical assumptions that align BER performance with MSE performance do not apply in this context, and that simply decreasing the MSE might increase the BER rather than decrease it. An alternative post-demodulator adaptive filter with similar complexity to the LMS filter is proposed which shows improved BER performance. Analysis provides a simplified interpretation of the interaction of system and channel model parameters which may form the basis for more general use of a post-demodulator adaptive filter.

Publisher note

To access the full article, please see PDF.

Author information

Authors and Affiliations


Corresponding author

Correspondence to Shu-Ting Lee.

Rights and permissions

Open Access This article is distributed under the terms of the Creative Commons Attribution 2.0 International License (, which permits unrestricted use, distribution, and reproduction in any medium, provided the original work is properly cited.

Reprints and Permissions

About this article

Cite this article

Lee, ST., Wood, S.L., Ready, M.J. et al. Performance of Post-Demodulator Adaptive Filters for FSK Signals in a Multipath Environment. EURASIP J. Adv. Signal Process. 2011, 412036 (2011).

Download citation

  • Received:

  • Revised:

  • Accepted:

  • Published:

  • DOI:


  • Channel Model
  • Performance Degradation
  • Signal Environment
  • Statistical Assumption
  • Similar Complexity