Memoryless quantizer- detectors for constant signals in m-dependent noise

The performance and design of data quantizers for use in memoryless discrete-time detection systems operating with dependent samples is considered. This problem is approached on a large-sample-size small-signal basis, and -dependence is used to model the dependence structure among data samples. By considering the particular situation of detecting known constant signals in additive noise, previous results for memoryless detector analysis are applied to derive expressions for the evaluation of quantizer-detector performance for this situation. Design criteria are established for the optimum selection of quantizer parameters, and these are seen to be generalizations of earlier designs for the corresponding independent sampling case.