Data and decision fusion for distributed spectrum sensing in cognitive radio networks

With dynamic spectrum access coming into focus for future mobile applications, Cognitive Radio technologies have emerged as a promising area for further research. As spectrum sensing forms an important functionality for these systems, the following areas were investigated into in this paper. Firstly, the basic spectrum sensing schemes were integrated with data and decision fusion techniques to improve performance in the presence of multiple secondary users. Further analysis of Ad Hoc sensing schemes was done with emphasis on distributed sensing schemes. The effects of varying the number of participating neighbours on fusion values were studied in detail. It was seen that varying the sensing time and the number of participating neighbours produces changes in the throughput and detection probabilities. The changes produced by varying these parameters were discussed in detail.