The application of wavelet-domain adaptive filtering to spread spectrum communications

Frequency domain signal processing has been used for some time to suppress narrowband interference in spread spectrum signals. Essentially, narrowband interference energy appears in only a few of the transform bins whereas the wideband spread spectrum signal energy appears in most, if not all, of the bins. A simple exciser, which sets bins that are primarily interference to zero, can then remove most of the interference energy while removing only a small portion of the spread spectrum signal energy. Recently, this concept has been extended to include wavelet transform domain excision where the time-frequency localization properties of the wavelet transform are utilized to improve the effectiveness of the excision process. This paper generalizes this work by considering wavelet-based linear transforms and multirate filterbanks and replacing the simple exciser with continuously-variable adaptive tap weights on each transform bin. These tap weights can be derived using a transform domain adaptive filter structure wherein the weights are adapted to optimize the detection performance in the mean-square sense, effectively producing a transform domain decision-directed equalizer. The paper presents an analytical result for bit-error-rate (BER) performance that is applicable for arbitrary linear transforms and generic multirate filterbank analysis/synthesis structures. Both adaptive weighting and simple exciser schemes are considered. Through both analytical and Monte-Carlo simulation results, the adaptive filter is shown to provide significantly better performance than the simple exciser for tone interference.