Multi-sensor data fusion in cognitive radio from its perspective

In recent days, the intelligent transportation system (ITS) become one of the major thrust areas in the field of electronics and communication engineering. Here an architecture of multi-channel cognitive radio (CR) has been proposed to encounter the challenges in ITS. Spectrum sensing, decision and data fusion are the three major activities performed by the CR. A novel model, using dynamic Bayesian network (DBN), for data fusion is developed and presented in this paper. Three types of sensor data, GPS, local radar and gyroscopic data are considered for fusion to provide accurate online measurements to avoid collision in road traffic scenarios.