Signal Detection in Weakly-Dependent Noise

Abstract

By viewing the weak signal detection problem as a problem of binary hypothesis testing in statistical inference, we get a convenient mathematical framework. When we consider the signal detection problem in this way, we often assume that the observations are independent. The assumption of statistically independent sampling is frequently violated, however, in discrete-time signal detection applications, and the optimum detectors designed under this assumption are no longer optimum in practice. Such a situation becomes more crucial as the sampling rate gets higher. It is also known that dependent noise models are quite useful in modeling the inter-user interference which arises frequently in the multiple access communication systems. Thus, investigations on signal detections in dependent noise should be considered. In several recent studies, the solutions under some dependent observation models have been considered for designing signal detection systems, which are then implemented with or without memory unit.