The satellite transponder is a widely used module in satellite missions, and the most concerned issue is to reduce the noise of the transferred signal. Otherwise, the telemetry signal will be polluted by the noise contained in the transferred signal, and the additional power will be consumed. Therefore, a method based on wavelet packet de-noising(WPD) is introduced. Compared with other techniques, there are two features making WPD more suitable to be applied to satellite transponders: one is the capability to deal with time-varying signals without any priori information of the input signals; the other is the capability to reduce the noise in band, even if the noise overlaps with signals in the frequency domain, which provides a great de-noising performance especially for wideband signals. Besides, an oscillation detector and an averaging filter are added to decrease the partial oscillation caused by the thresholding process of WPD. Simulation results show that the proposed algorithm can reduce more noises and make less distortions of the signals than other techniques. In addition, up to12 d B additional power consumption can be reduced at –10 d B signal-to-noise ratio(SNR). The satellite transponder is a widely used module in satellite missions, and the most concerned issue is to reduce the noise of the transferred signal. Otherwise, the telemetry signal will be polluted by the noise contained in the transferred signal, and the additional power will be Compared with other techniques, there are two features making WPD more suitable to be applied to satellite transponders: one is the capability to deal with time-varying signals without any priori information of the input signals; the other is the capability to reduce the noise in band, even if the noise overlaps with signals in the frequency domain, which provides a great de-noising performance especially for wideband signals. detector and an averaging filter were added to decrease the partial oscillation caused by the thresholding process of WPD. Simulation results show that the proposed algorithm ca n addition more noises and make less distortions of the signals than other techniques. In addition, up to 12 d B additional power consumption can be reduced at -10 d B signal-to-noise ratio (SNR).