Modulation classification of signals in unknown ISI environments

Modulation classification is an important component of non-cooperative communication theory in which the received signal type is unknown but may be restricted to a finite set of possibilities. We develop two classification techniques for digitally modulated signals affected by intersymbol interference (ISI). The initial development of the classification tests is derived assuming a known-channel impulse response. In order to address signal classification in an unknown ISI environment, we employ per-survivor processing (PSP), a technique for estimating both the data sequence and the unknown parameters of a communications signal which exhibits memory