Family of Parallel LMS-based Adaptive Algorithms of Echo Cancellation
Dobrucki Andrzej 1, Walczyński Maciej 2, Bożejko Wojciech 3
1 Wrocław University of Technology
Faculty of Electronics, Department of Acoustics and Multimedia Wyb. Wyspian ́skiego 27, 50-370 Wrocław, Poland2 General Tadeusz Kościuszko Military Academy of Land Forces Faculty of Management, Department of System Engineering ul. Czajkowskiego 109, 51-150 Wrocław, Poland
3 Wrocław University of Technology
Institute of Computer Engineering, Control and Robotics Wyb. Wyspian ́skiego 27, 50-370 Wrocław, Poland
Received:
Received: 22 September 2014; revised: 29 June 2015; accepted: 08 July 2015; published online: 01 December 2015
DOI: 10.12921/cmst.2015.21.04.003
Abstract:
In this paper we propose a number of new, genuine parallel LMS-based adaptive algorithms in the context of their use in the acoustic echo cancellation. The most complex parts of the LMS-based algorithms were determined and parallelized. A number of genuine parallelization methods were proposed taking into consideration varied types of architectures of modern concurrent computing environment, such as GPUs, clusters of workstations and cloud computing.
Key words:
adaptive algorithms, DSP, echo cancellation, GPU, parallel algorithms
References:
[1] H.Yusukawa, S.Shimada, An acoustic echo canceller using subband sampling and decorrelation methods, IEEE Trans. Signal Processing, 41, 926-930 (1993).
[2] J.Chen, H.Bes, J.Vandewalle, P. Janssens, A new structure for sub-band acoustic echo canceler, Proc. IEEE ICASSP, 2574-2577 (1988).
[3] W.Kellermann, Some aspects of the frequency subband approach to the cancellation of acoustical echoes, Proc. IEEE ICASSP, 2570-2573 (1988).
[4] B.Hatty, Block Recursive Least Squares Adaptive Filters Using Multirate Systems for Cancellation of Acoustical Echoes, Proc. IEEE ASSP Workshop on Application of Signal Pro- cessing to Audio and Acoustics, 1989.
[5] A.Gilliore, M.Vetterli, Adaptive filtering in subband with critical sampling: analysis, experiments, and application to acoustic echo cancellation, IEEE Trans. Signal Processing, 40, 1862-1875 (1992).
[6] A.Herikstad, Gpu sound processing, December 2008.Specialization Project TDT4590, Complex Computer Systems, NTNU. 33, 36, 39, 47.
[7] A. Dobrucki, W. Bożejko, M. Walczyński, Parallelizing of digital signal processing with using GPU, Signal processing, algorithms, architectures, arrangements, and (2012) applica- tions, SPA 2010 : conference proceedings, Poznan, 23-25th September 2010. [Poznan ́ : Chapter Circuits and Systems Chapter Signal Processing Poland Section, Institute of Elec- trical and Electronics Engineers, 2010], 29-33.
[8] W.Bożejko, M.Walczyński, Noise reduction with using parallel algorithms, Noise Control ’10 [electronic document]: 15th International Conference on Noise Control, 6-9 June 2010, Wałbrzych. Warszawa : Centralny Instytut Ochrony Pracy – Pan ́stwowy Instytut Badawczy, 2010, 1-8.
[9] M. Walczyński, Zastosowanie algorytmów równoległych w problemie odszumiania sygnałów dźwiękowych i wizyjnych na przykładzie algorytmu LMS w mechatronice, Mechatronika. Nauka dla gospodarki. Rzeszów 2011. ISBN 978-83- 63151-01-0 (in polish).
[10] A. Dobrucki, S.Brachmański, P.Pruchnicki, P.Staroniewicz, P. Plaskota, M. Walczyński, Subvocal speech recognition based on electromyography : Package WP7:Source codes of software for parameterization of recorded SVR signals and for management of files with signals. Technical documenta- tion of SVR sensor. Package WP8: Test of the realized SVR sensor Results of subvocal speech recognition using sensor. Summary of results achived in project, Report SPR series, 2012.
[11] A.Dobrucki, S.Brachmański, P.Pruchnicki, P.Staroniewicz, P. Plaskota, M. Walczyński, Subvocal speech recognition based on electromyography : Package WP4: Purchased equipment and its running EMG-SVR parametrization al- gorithms; Database of test signals; Experiments with EMG signals for vocal and subvocal speech, Report SPR series, 2011.
[12] A.Dobrucki, W.Bożejko, M.Walczyński,LMSalgorithms parallelization in GPGPU environment, Elektronika (War- saw), 52(5), 49-53 (2011).
[13] M.M. Sondhi, An adaptive echo canceller, Bell Syst. Tech. J., 46(3), 497-511 (1967).
[14] M.M.Sondhiand, A.J.Presti, A self-adaptive echo canceller, Bell Syst. Tech. J., 45(12), 1851-1854 (1966).
[15] W.Bożejko,Onsingle-walkparallelizationofthejobshop problem solving algorithms, Computers & Operations Re- search 39, 2258-2264 (2012).
[16] T.H.Cormen,C.E.Leiserson,R.L.Rivest,C.Stein,Introduction to algorithms, MIT Press, 2009.
[17] T. Gansler, J. Benesty, D. R. Morgan, M. M. Sondhi, S. L. Gay, Advances in Network and Acoustic Echo Cancellation,
In this paper we propose a number of new, genuine parallel LMS-based adaptive algorithms in the context of their use in the acoustic echo cancellation. The most complex parts of the LMS-based algorithms were determined and parallelized. A number of genuine parallelization methods were proposed taking into consideration varied types of architectures of modern concurrent computing environment, such as GPUs, clusters of workstations and cloud computing.
Key words:
adaptive algorithms, DSP, echo cancellation, GPU, parallel algorithms
References:
[1] H.Yusukawa, S.Shimada, An acoustic echo canceller using subband sampling and decorrelation methods, IEEE Trans. Signal Processing, 41, 926-930 (1993).
[2] J.Chen, H.Bes, J.Vandewalle, P. Janssens, A new structure for sub-band acoustic echo canceler, Proc. IEEE ICASSP, 2574-2577 (1988).
[3] W.Kellermann, Some aspects of the frequency subband approach to the cancellation of acoustical echoes, Proc. IEEE ICASSP, 2570-2573 (1988).
[4] B.Hatty, Block Recursive Least Squares Adaptive Filters Using Multirate Systems for Cancellation of Acoustical Echoes, Proc. IEEE ASSP Workshop on Application of Signal Pro- cessing to Audio and Acoustics, 1989.
[5] A.Gilliore, M.Vetterli, Adaptive filtering in subband with critical sampling: analysis, experiments, and application to acoustic echo cancellation, IEEE Trans. Signal Processing, 40, 1862-1875 (1992).
[6] A.Herikstad, Gpu sound processing, December 2008.Specialization Project TDT4590, Complex Computer Systems, NTNU. 33, 36, 39, 47.
[7] A. Dobrucki, W. Bożejko, M. Walczyński, Parallelizing of digital signal processing with using GPU, Signal processing, algorithms, architectures, arrangements, and (2012) applica- tions, SPA 2010 : conference proceedings, Poznan, 23-25th September 2010. [Poznan ́ : Chapter Circuits and Systems Chapter Signal Processing Poland Section, Institute of Elec- trical and Electronics Engineers, 2010], 29-33.
[8] W.Bożejko, M.Walczyński, Noise reduction with using parallel algorithms, Noise Control ’10 [electronic document]: 15th International Conference on Noise Control, 6-9 June 2010, Wałbrzych. Warszawa : Centralny Instytut Ochrony Pracy – Pan ́stwowy Instytut Badawczy, 2010, 1-8.
[9] M. Walczyński, Zastosowanie algorytmów równoległych w problemie odszumiania sygnałów dźwiękowych i wizyjnych na przykładzie algorytmu LMS w mechatronice, Mechatronika. Nauka dla gospodarki. Rzeszów 2011. ISBN 978-83- 63151-01-0 (in polish).
[10] A. Dobrucki, S.Brachmański, P.Pruchnicki, P.Staroniewicz, P. Plaskota, M. Walczyński, Subvocal speech recognition based on electromyography : Package WP7:Source codes of software for parameterization of recorded SVR signals and for management of files with signals. Technical documenta- tion of SVR sensor. Package WP8: Test of the realized SVR sensor Results of subvocal speech recognition using sensor. Summary of results achived in project, Report SPR series, 2012.
[11] A.Dobrucki, S.Brachmański, P.Pruchnicki, P.Staroniewicz, P. Plaskota, M. Walczyński, Subvocal speech recognition based on electromyography : Package WP4: Purchased equipment and its running EMG-SVR parametrization al- gorithms; Database of test signals; Experiments with EMG signals for vocal and subvocal speech, Report SPR series, 2011.
[12] A.Dobrucki, W.Bożejko, M.Walczyński,LMSalgorithms parallelization in GPGPU environment, Elektronika (War- saw), 52(5), 49-53 (2011).
[13] M.M. Sondhi, An adaptive echo canceller, Bell Syst. Tech. J., 46(3), 497-511 (1967).
[14] M.M.Sondhiand, A.J.Presti, A self-adaptive echo canceller, Bell Syst. Tech. J., 45(12), 1851-1854 (1966).
[15] W.Bożejko,Onsingle-walkparallelizationofthejobshop problem solving algorithms, Computers & Operations Re- search 39, 2258-2264 (2012).
[16] T.H.Cormen,C.E.Leiserson,R.L.Rivest,C.Stein,Introduction to algorithms, MIT Press, 2009.
[17] T. Gansler, J. Benesty, D. R. Morgan, M. M. Sondhi, S. L. Gay, Advances in Network and Acoustic Echo Cancellation,
