TY - JOUR
T1 - Analysis of Acoustic Feedback/Echo Cancellation in Multiple-Microphone and Single-Loudspeaker Systems Using a Power Transfer Function Method
AU - Guo, Meng
AU - Bo Elmedyb, Thomas
AU - Jensen, Søren Holdt
AU - Jensen, Jesper
PY - 2011/9/19
Y1 - 2011/9/19
N2 - In this work, we analyze a general multiple-microphone and single-loudspeaker audio processing system, where a multichannel adaptive system is used to cancel the effect of acoustic feedback/echo, and a beamformer processes the feedback/echo canceled signals. We introduce and derive an accurate approximation of a frequency domain measure - the power transfer function - and show how it can be used to predict the convergence rate, system stability bound and the steady-state behavior of the entire cancellation system across frequency and time. We consider three example adaptive algorithms in the cancellation system: the least mean square, normalized least mean square, and the recursive least squares algorithms. Furthermore, we derive expressions to determine the step size parameter in the adaptive algorithms to achieve a desired system behavior, e.g., convergence rate at a specific frequency. Finally, we compare and discuss the performance of all three adaptive algorithms, and we verify the derived expressions through simulation experiments.
AB - In this work, we analyze a general multiple-microphone and single-loudspeaker audio processing system, where a multichannel adaptive system is used to cancel the effect of acoustic feedback/echo, and a beamformer processes the feedback/echo canceled signals. We introduce and derive an accurate approximation of a frequency domain measure - the power transfer function - and show how it can be used to predict the convergence rate, system stability bound and the steady-state behavior of the entire cancellation system across frequency and time. We consider three example adaptive algorithms in the cancellation system: the least mean square, normalized least mean square, and the recursive least squares algorithms. Furthermore, we derive expressions to determine the step size parameter in the adaptive algorithms to achieve a desired system behavior, e.g., convergence rate at a specific frequency. Finally, we compare and discuss the performance of all three adaptive algorithms, and we verify the derived expressions through simulation experiments.
U2 - 10.1109/TSP.2011.2168523
DO - 10.1109/TSP.2011.2168523
M3 - Journal article
SN - 1053-587X
VL - 59
SP - 5774
EP - 5788
JO - I E E E Transactions on Signal Processing
JF - I E E E Transactions on Signal Processing
IS - 12
ER -