A Novel Narrow-band Interference Suppression Technique in Spread Spectrum Systems

The conventional approaches to enhance the narrow-band interference of spread spectrum systems mostly use the adaptive LMS filter to predict the narrow-band interference and subtract the predicted interfering signal from the polluted received signal before de-spreading. However, since these approaches take no account of complexity control and have no guarantee of global minimum, they often suffer from unsteadiness in performance. In this paper, we proposed a novel approach to narrow-band interference suppression, in which − ε support vector regression method is used to predict the narrow-band interference instead of adaptive LMS filter. With the help of practical parameter selection rules, it is not only effective but also easy to handle. Computer simulations show that it outperforms the conventional approaches in most cases and thus is a desirable choice for narrow-band interference suppression