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

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.

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