Interference rejection using the time-dependent constant modulusalgorithm (CMA) and the hybrid CMA/spectral correlation discriminator

Two new blind adaptive filtering algorithms for interference rejection using time-dependent filtering structures are presented. The time-dependent structure allows the adaptive filter to outperform the conventional adaptive filter implemented with a time-independent structure for filtering of cyclostationary communication signals. At the same time, the blind adaption algorithms allow the filters to operate without the use of an external training signal. The first algorithm applies the CMA to an unconstrained time-dependent filtering structure. The second algorithm applies the CMA to a spectral correlation discriminator, which is constrained to select signals with unique spectral correlation characteristics. Using computer simulations, it is shown that the blind time-dependent filtering algorithms can provide mean-square errors (MSEs) and bit error rates (BERs) that are significantly lower than the MSEs and BERs provided using conventional time-independent adaptive filters. It is also shown that these processors can outperform the nonblind training-sequence directed time-independent adaptive filter