Canonical Non-Gaussian Noise Models: Their Implications for Measurement and for Prediction of Receiver Performance

Abstract
The chief aim of this paper is to provide a short technical summary of the principal noise-model results (11-[11], developed by the author to date, and to consider their major implications for 1) measurement, and 2) performance prediction and evaluation. The discussion is illustrated by a concise review of model statistics, methods of estimating the model parameters, including the effects on accuracy of finite data samples. A variety of signal detection problems are similarly used to illustrate the very large potential improvement possible when optimum algorithms are employed, vis-a-vis most of the currently used systems, which are conventionally optimized for Gaussian interference. Conditions for realizing such gains are also given, and the principal key properties of these new, general models are discussed. These models make possible, for the first time, a systematic treatment of real-world EMI environments, both for measurement and assessment, and for receiver performance therein.

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