- Research Article
- Open Access
Efficient Multichannel NLMS Implementation for Acoustic Echo Cancellation
EURASIP Journal on Audio, Speech, and Music Processing volume 2007, Article number: 078439 (2007)
An acoustic echo cancellation structure with a single loudspeaker and multiple microphones is, from a system identification perspective, generally modelled as a single-input multiple-output system. Such a system thus implies specific echo-path models (adaptive filter) for every loudspeaker to microphone path. Due to the often large dimensionality of the filters, which is required to model rooms with standard reverberation time, the adaptation process can be computationally demanding. This paper presents a selective updating normalized least mean square (NLMS)-based method which reduces complexity to nearly half in practical situations, while showing superior convergence speed performance as compared to conventional complexity reduction schemes. Moreover, the method concentrates the filter adaptation to the filter which is most misadjusted, which is a typically desired feature.
Hänsler E, Schmidt G: Acoustic Echo and Noise Control: A Practical Approach. John Wiley & Sons, New York, NY, USA; 2004.
Sondhi MM: An adaptive echo canceler. Bell System Technical Journal 1967,46(3):497-510.
Widrow B, Stearns SD: Adaptive Signal Processing. Prentice-Hall, Englewood Cliffs, NJ, USA; 1985.
Haykin S: Adaptive Filter Theory. 4th edition. Prentice-Hall, Englewood Cliffs, NJ, USA; 2002.
Douglas SC: Adaptive filters employing partial updates. IEEE Transactions on Circuits and Systems II: Analog and Digital Signal Processing 1997,44(3):209-216. 10.1109/82.558455
Aboulnasr T, Mayyas K: Complexity reduction of the NLMS algorithm via selective coefficient update. IEEE Transactions on Signal Processing 1999,47(5):1421-1424. 10.1109/78.757235
Naylor PA, Sherliker W: A short-sort M-Max NLMS partial-update adaptive filter with applications to echo cancellation. Proceedings of IEEE International Conference on Acoustics, Speech, and Signal Processing (ICASSP '03), April 2003, Hong Kong 5: 373-376.
Dogançay K, Tanrikulu O: Adaptive filtering algorithms with selective partial updates. IEEE Transactions on Circuits and Systems II: Analog and Digital Signal Processing 2001,48(8):762-769. 10.1109/82.959866
Schertler T: Selective block update of NLMS type algorithms. Proceedings of IEEE International Conference on Acoustics, Speech, and Signal Processing (ICASSP '98), May 1998, Seattle, Wash, USA 3: 1717-1720.
Godavarti M, Hero AO III: Partial update LMS algorithms. IEEE Transactions on Signal Processing 2005,53(7):2382-2399.
Hänsler E, Schmidt G: Single-channel acoustic echo cancellation. In Adaptive Signal Processing. Edited by: Benesty J, Huang Y. Springer, New York, NY, USA; 2003.
Kuo SM, Chen J: Multiple-microphone acoustic echo cancellation system with the partial adaptive process. Digital Signal Processing 1993,3(1):54-63. 10.1006/dspr.1993.1007
Gollamudi S, Kapoor S, Nagaraj S, Huang Y-F: Set-membership adaptive equalization and an updator-shared implementation for multiple channel communications systems. IEEE Transactions on Signal Processing 1998,46(9):2372-2385. 10.1109/78.709523
Werner S, Apolinario JA Jr., de Campos MLR, Diniz PSR: Low-complexity constrained affine-projection algorithms. IEEE Transactions on Signal Processing 2005,53(12):4545-4555.
Gardner WA: Learning characteristics of stochastic-gradient-descent algorithms: a general study, analysis, and critique. Signal Processing 1984,6(2):113-133. 10.1016/0165-1684(84)90013-6
ADSP-BF533 Blackfin processor hardware reference, Analog Devices, Norwood, Mass, USA, 2005