Application of wavelet de-noising to signal demodulation

We present the application of wavelet-based de-noising techniques to the demodulation of digital communication signals. These techniques are related to those originally devised by Donoho and Johnstone (see Biometrika, v.81, p.455, 1994, and IEEE Trans. Info. Theory, vol.41, p.613, 1995) for minimum L/sub 2/-risk signal reconstruction. The important minimax property of wavelet de-noising filters yields significant noise reduction while retaining the essential signal features. However, the two problems are quite different, i.e., the objective is not signal reconstruction but rather minimizing bit error rate. This generally results in different design rules for optimizing performance. We show that wavelet de-noising can be effectively used for data demodulation and we propose simple design rules for its implementation.