Automatic Modulation Classification for adaptive Power Control in cognitive satellite communications

Spectrum Sensing (SS) and Power Control (PC) have been two important concepts of Cognitive Radio (CR). In this paper, a mechanism combining these two topics is proposed to allow a cognitive user, also called Secondary User (SU), to access the frequency band of a Primary User (PU) operating based on an Adaptive Coding and Modulation (ACM) protocol. The suggested SS technique considers Higher Order Statistical (HOS) features of the signal and an efficient Machine Learning (ML) detector, the Support Vector Machine (SVM), in order to constantly monitor the modulation scheme of the PU. Once the Automatic Modulation Classification (AMC) is ensured, the SU can attempt to access the frequency band of the PU and increase its transmitting power until it causes a change of the PU's modulation scheme due to interference. When the SU detects the change of the PU's modulation scheme, then it reduces its transmitting power to a lower level so as to regulate the induced interference. This Adaptive Power Control (APC) algorithm converges to the aforementioned interference limit and guarantees preservation of the PU link QoS.