Type-based detection for unknown channels

A type is the histogram estimate of a stationary sequence´s amplitude distribution. From training data, types are computed and use to determine which training data best describe subsequently obtained observations. Such type-based detectors are asymptotically optimal in the sense that the maximal exponential error rate is achieved. For digital communication systems using direct-sequence signaling, type-based detectors are shown to be effective. Training data are obtained from preambles, and then used to make individual bit decisions. Simulations show that in this communications scenario, type-based detectors yield nearly optimal performance without any a priori channel information