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A new approach for acoustic feedback cancellation is presented. The challenge in acoustic feedback cancellation is a strong correlation between the local speech and the loudspeaker signal. Due to this correlation, the convergence rate of adaptive algorithms is limited. Therefore, a novel stepsize control of the adaptive filter is presented. The stepsize control exploits reverberant signal periods to update the adaptive filter. As soon as local speech stops, the reverberation energy of the system decays exponentially. This means that during reverberation there is only excitation of the filter but no local speech. Thus, signals are not correlated and the filter can converge without correlation problems. Consequently, the stepsize control accelerates the adaption process during reverberation and slows it down at the beginning of speech activity. It is shown, that with a particular gain control, the reverb-based stepsize control can be interpreted as the theoretical optimum stepsize. However, for this purpose a precise estimation of the system distance is required. One estimation method is presented. The proposed estimator has a rescue mechanism to detect enclosure dislocations. Both, simulations and real world testing show that the acoustic feedback canceler is capable of improving stability and convergence rate, even at high system gains.