Adaptive robust spread-spectrum receivers

We consider the problem of robust detection of a spread-spectrum (SS) signa l in the presence of unknown correlated SS interference and additive non-Ga ussian noise. The proposed general SS receiver structure is comprised by a vector of adaptive chip-based nonlinearities followed by an adaptive linear tap-weight filter and combines the relative merits of both nonlinear and l inear signal processing. The novel characteristics of our approach are as f ollows. First, the nonlinear receiver front-end adapts itself to the unknow n prevailing noise environment providing robust performance for a wide rang e of underlying noise distributions. Second, the adaptive linear tap-weight filter that follows the nonlinearly processed chip samples results in a re ceiver that is proven to be effective in combating SS interference as well, To determine the receiver parameters, me propose, develop, and study three adaptive schemes under a joint mean-square-error (MSE), or a joint bit-err or-rate (BER), or a joint MSE-BER optimization criterion. As a side result, we derive the optimum decision fusion filter for receivers that utilize ha rd-limiting (sign) chip nonlinearities, Numerical and simulation results de monstrate the performance of the proposed schemes and offer comparisons wit h the conventional matched-filter (MF), the decorrelator, the conventional minimum-variance-distortionless-response (MVDR) filter, and the sign-majori ty-vote receiver.