Type-based detection for spread spectrum

The universal classifier using empirically observed statistics, developed by Gutman (1989), is applied to the spread-spectrum communications problem. We call the resulting classifier a type-based detector and show that it has close to optimal performance over a wide range of unknown channel environments, including static and multipath fading channels in additive Gaussian and non-Gaussian noise. In a multiple-access system, the type-based detector is capable of rejecting high levels of multiple-access interference. The type-based detector uses a training sequence to form its knowledge about the bit hypotheses, and in a communications system, the training sequence corresponds to a periodically transmitted preamble or “sync” sequence