OFDM blending modulation systems in practical cognitive radio application

The cyclic spectral analysis of empirical signals from blending modulation systems which is based on orthogonal frequency division multiplexing (OFDM) is analyzed and exploited in cognitive radio applications in this paper. Four kinds of channel states, that is, spectrum vacancy, primary signal transmitting, secondary signal transmitting, and mix signals transmitting, can be distinguished agilely using their distinct cyclic spectrum feature, which help to access to or remove from channels agilely and reliably. The position of inserting modulation as a feature, which cognitive radio nodes can detect as an unique identifier in network identification. The design of transmitter and receiver are simple and need not a static common control channel with the proposed model of cognitive radio, which promise greater spectral-usage efficiency. Simulation results show that the proposed model can improve spectral-usage efficiency and performance in cognitive radio networks.