Abstract
The detection of weak signals is addressed in additive noise described by the first order moving average of a Gaussian process. We derive decision regions of the maximum likelihood (ML) and suboptimum ML (SML) detectors, and obtain specific examples of the ML and SML decision regions. The ML and SML detectors are employed in the antipodal signaling system, and compared in terms of the bit-error-rate in the dependent Gaussian noise environment. Numerical results show that the SML detector, despite its reduced complexity and simpler structure, exhibits practically the same performance as the optimum ML detector.
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