System Identification of Equalized Room Impulse Responses by an Acoustic Echo Canceller Using Proportionate LMS Algorithms

Goetze S, Xiong F, Jungmann JO, Kallinger M, Kammeyer KD, Mertins A. System Identification of Equalized Room Impulse Responses by an Acoustic Echo Canceller Using Proportionate LMS Algorithms. In: AES Convention 130. Audio Engineering Society; 2011. Paper 8437. Available from: https://aes.org/publications/elibrary-page/?id=15904

@inproceedings{Goetze2011_15904,
  author = {Goetze, Stefan and Xiong, Feifei and Jungmann, Jan Ole and Kallinger, Markus and Kammeyer, Karl-Dirk and Mertins, Alfred},
  title = {{System Identification of Equalized Room Impulse Responses by an Acoustic Echo Canceller Using Proportionate LMS Algorithms}},
  booktitle = {AES Convention 130},
  note = {Paper 8437},
  year = {2011},
  month = may,
  publisher = {Audio Engineering Society},
  url = {https://aes.org/publications/elibrary-page/?id=15904}
}

TY  - CPAPER
TI  - System Identification of Equalized Room Impulse Responses by an Acoustic Echo Canceller Using Proportionate LMS Algorithms
AU  - Goetze, Stefan
AU  - Xiong, Feifei
AU  - Jungmann, Jan Ole
AU  - Kallinger, Markus
AU  - Kammeyer, Karl-Dirk
AU  - Mertins, Alfred
T2  - AES Convention 130
M1  - Paper 8437
PY  - 2011
DA  - 2011/05/06
UR  - https://aes.org/publications/elibrary-page/?id=15904
PB  - Audio Engineering Society
LA  - en
AB  - Hands-free telecommunication systems usually employ subsystems for acoustic echo cancellation (AEC), listening-room compensation (LRC) and noise reduction in combination. This contribution discusses a combined system of a two-stage AEC filter and an LRC filter to remove reverberation introduced by the listening room. An inner AEC is used to achieve initial echo reduction and to perform system identification needed for the LRC filter. An additional outer AEC is used to further reduce the acoustic echoes. The performance of proportionate filter update schemes such as the so-called proportionate normalized least mean squares algorithm (PNLMS) or the improved PNLMS (IPNLMS) for system identification of equalized impulse response (IR) are shown and the mutual influences of the subsystems are analyzed. If the LRC filter succeeds in shaping a sparse overall IR for the concatenated system of LRC filter and room impulse response (RIR), the PNLMS performs best since it is optimized for the identification of sparse IRs. However, the equalization may be imperfect due to channel estimation errors in periods of convergence and due to the so-called tail-effect of AEC, i.e. the fact that only the first part of an RIR is identified in practical systems. The IPNLMS is more appropriate in this case to identify the equalized IR.
ER  -