A Unique Low Complexity Parameter Independent Adaptive Design for Echo Reduction

  • Pranab Das
  • Abhishek Deb
  • Asutosh Kar
  • Mahesh Chandra
Part of the Smart Innovation, Systems and Technologies book series (SIST, volume 27)

Abstract

Acoustic echo is one of the most important issues in full duplex communication. The original speech signal is distorted due to echo. For this adaptive filtering is used for echo suppression. In this paper our objective is to cancel out the acoustic echo in a sparse transmission channel. For this purpose many algorithms have been developed over the period of time, such as Least Mean Square (LMS), Normalized LMS (NLMS), Proportionate NLMS (PNLMS) and Improved PNLMS (IPNLMS) algorithm. Of all these algorithms we carry out a comparative analysis based on various performance parameters such as Echo Return Loss Enhancement, Mean Square Error and Normalized Projection Misalignment and find that for the sparse transmission channel all these algorithm are inefficient. Hence we propose a new algorithm modified -μ- PNLMS, which has the fastest steady state convergence and is the most stable among all the existing algorithms, this we show based on the simulation results obtained.

Keywords

Acoustic Echo Adaptive Filter Echo Return Loss Enhancement LMS Mean Square Error Sparse Transmission Channel 

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References

  1. 1.
    Verhoeckx, N.A.M.: Digital echo cancellation for base-band data transmission. IEEE Trans. Acoustic, Speech, Signal Processing 27(6), 768–781 (1979)CrossRefGoogle Scholar
  2. 2.
    Haykin, S.: Adaptive Filter Theory, 2nd edn. Prentice-Hall Inc., New Jersey (1991)MATHGoogle Scholar
  3. 3.
    Khong, A.W.H., Naylor, P.A., Benesty, J.: A low delay and fast converging improved proportionate algorithm for sparse system identification. EURASIP Journal of Audio Speech Music Processing 2007(1) (2007)Google Scholar
  4. 4.
    Diniz, P.S.R.: Adaptive Filtering, Algorithms and Practical Implementation. Kluwer Academic Publishers, Boston (1997)MATHGoogle Scholar
  5. 5.
    Wang, X., Shen, T., Wang, W.: An Approach for Echo Cancellation System Based on Improved NLMS Algorithm. School of Information Science and Technology, pp. 2853–2856. Beijing Institute of Technology, China (2007)Google Scholar
  6. 6.
    Paleologu, C., Benesty, J., Ciochin, S.: An Improved Proportionate NLMS Algorithm based on the Norm. In: International Conference on Acoustics, Speech and Signal Processing, pp. 309–312 (2010)Google Scholar
  7. 7.
    Deng, H., Doroslovachi, M.: Proportionate adaptive algorithms for network echo cancellation. IEEE Trans. Signal Processing 54(5), 1794–1803 (2006)CrossRefGoogle Scholar

Copyright information

© Springer International Publishing Switzerland 2014

Authors and Affiliations

  • Pranab Das
    • 1
  • Abhishek Deb
    • 1
  • Asutosh Kar
    • 1
  • Mahesh Chandra
    • 2
  1. 1.Department. of Electronics and Telecommunication EngineeringIndian Institute of Information TechnologyBhubaneswarIndia
  2. 2.Department of Electronics and Communication EngineeringBirla Institute of TechnologyMesraIndia

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