The Study and Simulation of Adaptive Algorithms in Echo Cancellation of an Acoustic Signal

Mahnaz Namdaran; Masoud Masomei; Hamid Chegini

doi:doi:10.11648/j.ajnc.20160505.13

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The Study and Simulation of Adaptive Algorithms in Echo Cancellation of an Acoustic Signal

Mahnaz Namdaran, Masoud Masomei, Hamid Chegini

Published in American Journal of Networks and Communications (Volume 5, Issue 5)

Received: 5 September 2016 Accepted: 19 September 2016 Published: 11 October 2016

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Abstract

Echo signal is the delayed form of an electrical or acoustic signal and it occurs when it returns to its source, in other words when acoustic signal finds its way from sending route through receiving one. One of the important parameters in discussing echo is delay time. In practical applications, if round trip time exceeds 30 milliseconds and echo power also exceeds 30 decibels, echo cancellation should be done. Today given the developments in utilizing communication system and transmitting acoustic information, echo cancellation becomes very important. There are different algorithms for cancelling echo of acoustic signals and each of them has both advantages and disadvantages. Adaptive filters are appropriate for echo cancellation. In such filters, minimization of the computational complexity and quick convergence of adapting is done within frequency domain owing to long impact response. In this study, different adaptive algorithms such as LMS, NLMS, VSLMS, VSNLMS and RLS have been suggested which can be used for echo cancellation and finally, a combination of them as an optimal algorithm was simulated for echo cancellation. In this paper, the stages of determining filter coefficients and the level of computational work in terms of convergence behavior, simulation results and other methods’ results were compared and it was found that using NLMS and MAX-E algorithms would offer best results in different situations. Innovative aspects of this paper include using adaptive algorithms in their real time and we can minimize the computational work of these algorithms and maximize the convergence speed by selecting accurate filter coefficients and the window used in computations. Also, we can use it in current applications and even in sound conversations on some communication networks like internet. Other aspects include using adaptive algorithms in implementing echo cancellation that have better function and convergence compared to blind methods of echo cancellation and they contribute to quality improvement of sent signals in conversations.

Published in	American Journal of Networks and Communications (Volume 5, Issue 5)
DOI	10.11648/j.ajnc.20160505.13
Page(s)	97-106
Creative Commons	This is an Open Access article, distributed under the terms of the Creative Commons Attribution 4.0 International License (http://creativecommons.org/licenses/by/4.0/), which permits unrestricted use, distribution and reproduction in any medium or format, provided the original work is properly cited.
Copyright	Copyright © The Author(s), 2016. Published by Science Publishing Group

Keywords

Echo Cancellation, Adaptive Algorithms, LMS Filters, Double Talk Detection, Noise

References

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[2]	Seng Lu, Y. Echo Cancellation and application, of IEEE, Vol 15, No 4, MAY 1990
[3]	Homer, J. Detection Guided NLMS Estimation of Parametrized Channel, of IEEE, Vol 47, No 12, DECEMBER 2000.
[4]	Seng Lu, Y. Performance Of Adaptive Filtering Algorithm, of IEEE, VOL 15, No 4, MAY 2000.
[5]	Benvensite, A. Goursat, M. Blind Equalizers, of IEEE, vol 6, pp.871-883, Agus 1994.
[6]	Tony, L. Channel Surfing Reinitalazation for the Contrast Moduls Algorithms. IEEE signal processing letters, Vol 4, NO3, pp. 85-87, Mar 1990.
[7]	Ding, et al. Local Convergence at The Sato Blind Equalizer and Generalization under Practical Constraints, of IEEE, Vol 39, pp. 302-306, Jan 1998.
[8]	Scalart, P. Convergence Analysis Of the Nlms Algoritm with M-Independent Inputs, of IEEE, Vol 35, No 4, MAY 2001.
[9]	Louis, A. Convergence Behavior of Affine Projection Algorithm, of IEEE, Vol 48, No 4, April 2000.
[10]	Kim, J. Performance Analysis of the Self –Correcting Adaptive Filter of IEEE, Vol 15, No 4, MAY 2005.
[11]	Lindstrom, F. An Improvement of the Two-Path Algorithm Transfer Logic for Acoustic Echo Cancellation of IEEE,Vol 15, No 4, MAY 2007.
[12]	Wakasa, Y. Design of a Rbust LMS Algorithm, of IEEE, NOVEMBER 2000.
[13]	Christian sc, Fredric lin. Low-complexity Adaptive Filtering Implementation For Acoustic Echo Cancellation of IEEE, Vol 5, No 5, jul 2006.
[14]	Linebarger, A. A New Method for Low Rank Transform Domain Adaptive filtering. Of IEEE, Vol 5, No14, MAY 2000.
[15]	Jung, Y. A New Adaptive Algorithm for Stereophonic Acoustic Echo Cancellation, of IEEE, Vol 35, No 4, DECEMBER 2000.

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APA Style

Mahnaz Namdaran, Masoud Masomei, Hamid Chegini. (2016). The Study and Simulation of Adaptive Algorithms in Echo Cancellation of an Acoustic Signal. American Journal of Networks and Communications, 5(5), 97-106. https://doi.org/10.11648/j.ajnc.20160505.13

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ACS Style

Mahnaz Namdaran; Masoud Masomei; Hamid Chegini. The Study and Simulation of Adaptive Algorithms in Echo Cancellation of an Acoustic Signal. Am. J. Netw. Commun. 2016, 5(5), 97-106. doi: 10.11648/j.ajnc.20160505.13

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AMA Style

Mahnaz Namdaran, Masoud Masomei, Hamid Chegini. The Study and Simulation of Adaptive Algorithms in Echo Cancellation of an Acoustic Signal. Am J Netw Commun. 2016;5(5):97-106. doi: 10.11648/j.ajnc.20160505.13

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@article{10.11648/j.ajnc.20160505.13,
  author = {Mahnaz Namdaran and Masoud Masomei and Hamid Chegini},
  title = {The Study and Simulation of Adaptive Algorithms in Echo Cancellation of an Acoustic Signal},
  journal = {American Journal of Networks and Communications},
  volume = {5},
  number = {5},
  pages = {97-106},
  doi = {10.11648/j.ajnc.20160505.13},
  url = {https://doi.org/10.11648/j.ajnc.20160505.13},
  eprint = {https://article.sciencepublishinggroup.com/pdf/10.11648.j.ajnc.20160505.13},
  abstract = {Echo signal is the delayed form of an electrical or acoustic signal and it occurs when it returns to its source, in other words when acoustic signal finds its way from sending route through receiving one. One of the important parameters in discussing echo is delay time. In practical applications, if round trip time exceeds 30 milliseconds and echo power also exceeds 30 decibels, echo cancellation should be done. Today given the developments in utilizing communication system and transmitting acoustic information, echo cancellation becomes very important. There are different algorithms for cancelling echo of acoustic signals and each of them has both advantages and disadvantages. Adaptive filters are appropriate for echo cancellation. In such filters, minimization of the computational complexity and quick convergence of adapting is done within frequency domain owing to long impact response. In this study, different adaptive algorithms such as LMS, NLMS, VSLMS, VSNLMS and RLS have been suggested which can be used for echo cancellation and finally, a combination of them as an optimal algorithm was simulated for echo cancellation. In this paper, the stages of determining filter coefficients and the level of computational work in terms of convergence behavior, simulation results and other methods’ results were compared and it was found that using NLMS and MAX-E algorithms would offer best results in different situations. Innovative aspects of this paper include using adaptive algorithms in their real time and we can minimize the computational work of these algorithms and maximize the convergence speed by selecting accurate filter coefficients and the window used in computations. Also, we can use it in current applications and even in sound conversations on some communication networks like internet. Other aspects include using adaptive algorithms in implementing echo cancellation that have better function and convergence compared to blind methods of echo cancellation and they contribute to quality improvement of sent signals in conversations.},
 year = {2016}
}

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TY  - JOUR
T1  - The Study and Simulation of Adaptive Algorithms in Echo Cancellation of an Acoustic Signal
AU  - Mahnaz Namdaran
AU  - Masoud Masomei
AU  - Hamid Chegini
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DO  - 10.11648/j.ajnc.20160505.13
T2  - American Journal of Networks and Communications
JF  - American Journal of Networks and Communications
JO  - American Journal of Networks and Communications
SP  - 97
EP  - 106
PB  - Science Publishing Group
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UR  - https://doi.org/10.11648/j.ajnc.20160505.13
AB  - Echo signal is the delayed form of an electrical or acoustic signal and it occurs when it returns to its source, in other words when acoustic signal finds its way from sending route through receiving one. One of the important parameters in discussing echo is delay time. In practical applications, if round trip time exceeds 30 milliseconds and echo power also exceeds 30 decibels, echo cancellation should be done. Today given the developments in utilizing communication system and transmitting acoustic information, echo cancellation becomes very important. There are different algorithms for cancelling echo of acoustic signals and each of them has both advantages and disadvantages. Adaptive filters are appropriate for echo cancellation. In such filters, minimization of the computational complexity and quick convergence of adapting is done within frequency domain owing to long impact response. In this study, different adaptive algorithms such as LMS, NLMS, VSLMS, VSNLMS and RLS have been suggested which can be used for echo cancellation and finally, a combination of them as an optimal algorithm was simulated for echo cancellation. In this paper, the stages of determining filter coefficients and the level of computational work in terms of convergence behavior, simulation results and other methods’ results were compared and it was found that using NLMS and MAX-E algorithms would offer best results in different situations. Innovative aspects of this paper include using adaptive algorithms in their real time and we can minimize the computational work of these algorithms and maximize the convergence speed by selecting accurate filter coefficients and the window used in computations. Also, we can use it in current applications and even in sound conversations on some communication networks like internet. Other aspects include using adaptive algorithms in implementing echo cancellation that have better function and convergence compared to blind methods of echo cancellation and they contribute to quality improvement of sent signals in conversations.
VL  - 5
IS  - 5
ER  -

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Author Information

Mahnaz Namdaran

Telecommunication, of Non-profit Institution of Higher Education, Aba, Abyek, Iran
Masoud Masomei

Non-profit Institution of Higher Education, Aba, Abyek, Iran
Hamid Chegini

Non-profit Institution of Higher Education, Aba, Abyek, Iran

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APA Style

Mahnaz Namdaran, Masoud Masomei, Hamid Chegini. (2016). The Study and Simulation of Adaptive Algorithms in Echo Cancellation of an Acoustic Signal. American Journal of Networks and Communications, 5(5), 97-106. https://doi.org/10.11648/j.ajnc.20160505.13

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ACS Style

Mahnaz Namdaran; Masoud Masomei; Hamid Chegini. The Study and Simulation of Adaptive Algorithms in Echo Cancellation of an Acoustic Signal. Am. J. Netw. Commun. 2016, 5(5), 97-106. doi: 10.11648/j.ajnc.20160505.13

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AMA Style

Mahnaz Namdaran, Masoud Masomei, Hamid Chegini. The Study and Simulation of Adaptive Algorithms in Echo Cancellation of an Acoustic Signal. Am J Netw Commun. 2016;5(5):97-106. doi: 10.11648/j.ajnc.20160505.13

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@article{10.11648/j.ajnc.20160505.13,
  author = {Mahnaz Namdaran and Masoud Masomei and Hamid Chegini},
  title = {The Study and Simulation of Adaptive Algorithms in Echo Cancellation of an Acoustic Signal},
  journal = {American Journal of Networks and Communications},
  volume = {5},
  number = {5},
  pages = {97-106},
  doi = {10.11648/j.ajnc.20160505.13},
  url = {https://doi.org/10.11648/j.ajnc.20160505.13},
  eprint = {https://article.sciencepublishinggroup.com/pdf/10.11648.j.ajnc.20160505.13},
  abstract = {Echo signal is the delayed form of an electrical or acoustic signal and it occurs when it returns to its source, in other words when acoustic signal finds its way from sending route through receiving one. One of the important parameters in discussing echo is delay time. In practical applications, if round trip time exceeds 30 milliseconds and echo power also exceeds 30 decibels, echo cancellation should be done. Today given the developments in utilizing communication system and transmitting acoustic information, echo cancellation becomes very important. There are different algorithms for cancelling echo of acoustic signals and each of them has both advantages and disadvantages. Adaptive filters are appropriate for echo cancellation. In such filters, minimization of the computational complexity and quick convergence of adapting is done within frequency domain owing to long impact response. In this study, different adaptive algorithms such as LMS, NLMS, VSLMS, VSNLMS and RLS have been suggested which can be used for echo cancellation and finally, a combination of them as an optimal algorithm was simulated for echo cancellation. In this paper, the stages of determining filter coefficients and the level of computational work in terms of convergence behavior, simulation results and other methods’ results were compared and it was found that using NLMS and MAX-E algorithms would offer best results in different situations. Innovative aspects of this paper include using adaptive algorithms in their real time and we can minimize the computational work of these algorithms and maximize the convergence speed by selecting accurate filter coefficients and the window used in computations. Also, we can use it in current applications and even in sound conversations on some communication networks like internet. Other aspects include using adaptive algorithms in implementing echo cancellation that have better function and convergence compared to blind methods of echo cancellation and they contribute to quality improvement of sent signals in conversations.},
 year = {2016}
}

Copy | Download

TY  - JOUR
T1  - The Study and Simulation of Adaptive Algorithms in Echo Cancellation of an Acoustic Signal
AU  - Mahnaz Namdaran
AU  - Masoud Masomei
AU  - Hamid Chegini
Y1  - 2016/10/11
PY  - 2016
N1  - https://doi.org/10.11648/j.ajnc.20160505.13
DO  - 10.11648/j.ajnc.20160505.13
T2  - American Journal of Networks and Communications
JF  - American Journal of Networks and Communications
JO  - American Journal of Networks and Communications
SP  - 97
EP  - 106
PB  - Science Publishing Group
SN  - 2326-8964
UR  - https://doi.org/10.11648/j.ajnc.20160505.13
AB  - Echo signal is the delayed form of an electrical or acoustic signal and it occurs when it returns to its source, in other words when acoustic signal finds its way from sending route through receiving one. One of the important parameters in discussing echo is delay time. In practical applications, if round trip time exceeds 30 milliseconds and echo power also exceeds 30 decibels, echo cancellation should be done. Today given the developments in utilizing communication system and transmitting acoustic information, echo cancellation becomes very important. There are different algorithms for cancelling echo of acoustic signals and each of them has both advantages and disadvantages. Adaptive filters are appropriate for echo cancellation. In such filters, minimization of the computational complexity and quick convergence of adapting is done within frequency domain owing to long impact response. In this study, different adaptive algorithms such as LMS, NLMS, VSLMS, VSNLMS and RLS have been suggested which can be used for echo cancellation and finally, a combination of them as an optimal algorithm was simulated for echo cancellation. In this paper, the stages of determining filter coefficients and the level of computational work in terms of convergence behavior, simulation results and other methods’ results were compared and it was found that using NLMS and MAX-E algorithms would offer best results in different situations. Innovative aspects of this paper include using adaptive algorithms in their real time and we can minimize the computational work of these algorithms and maximize the convergence speed by selecting accurate filter coefficients and the window used in computations. Also, we can use it in current applications and even in sound conversations on some communication networks like internet. Other aspects include using adaptive algorithms in implementing echo cancellation that have better function and convergence compared to blind methods of echo cancellation and they contribute to quality improvement of sent signals in conversations.
VL  - 5
IS  - 5
ER  -

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