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In addition to ever-present thermal noise, communication and sensor systemscan contain significant amounts of interference with outlier (e.g. impulsive)characteristics. Such outlier interference (including that caused by nonlinearsignal distortions, e.g. clipping) can be efficiently mitigated in real-timeusing intermittently nonlinear filters. Depending on the interference natureand composition, improvements in the quality of the signal of interest achievedby such filtering will vary from "no harm" to substantial. In this tutorial, weexplain in detail why the underlying outlier nature of interference oftenremains obscured, discussing the many challenges and misconceptions associatedwith state-of-art analog and/or digital nonlinear mitigation techniques,especially when addressing complex practical interference scenarios. We thenfocus on the methodology and tools for real-time outlier noise mitigation,demonstrating how the "excess band" observation of outlier noise enables itsefficient in-band mitigation. We introduce the basic real-time nonlinearcomponents that are used for outlier noise filtering and provide examples oftheir implementation. We further describe complementary nonlinear filteringarrangements for wide- and narrow-band outlier noise reduction, providingillustrations of their performance and the effect on channel capacity. Finally,we outline "effectively analog" digital implementations of these filteringstructures, discuss their broader applications, and comment on the ongoingdevelopment of the platform for their demonstration and testing. To emphasizethe effectiveness and versatility of this approach, in our examples we useparticularly challenging waveforms that severely obscure low-amplitude outliernoise, such as broadband chirp signals (e.g. used in radar, sonar, andspread-spectrum communications) and "bursty," high crest factor signals (e.g.OFDM).

Bandwidth Is Not Enough: "Hidden" Outlier Noise and Its Mitigation