Abstract: A RF Environment Learning Module includes a machine learning/artificial intelligence sensing controller process that schedules feature vector extractors and one or more machine learning (ML) signal classifiers in order to classify received radio signals and a ML-based validation process that reasons over the classification results to determine if they are valid or reasonable.

Abstract: In a simulcast communication session, at least one condition is monitored that is indicative of the potential occurrence of time domain interference at a plurality of mobile subscriber units. In response to such monitoring at least one simulcast operating parameter (SOP) is dynamically modified to reduce time domain interference experienced by one or more of the mobile subscriber units. The SOP is modified to minimize time domain interference within at least a portion of an overlap area defined between a first base transceiver station and a second base transceiver station.