Cooperative cognitive spectrum sensing using optimized DFT filter banks

Spectrum sensing is used in cognitive radio to detect the free portions of spectrum in a licensed frequency band. In this paper, we consider a cooperative spectrum sensing scenario in which the decisions from the secondary users are combined for better sensing accuracy. Each secondary user sends its decision or data to a central node which combines all individual data or decisions. A DFT filter bank based architecture is used by each secondary user for efficient detection of a primary user signal in a desired time-frequency slot. The prototype filters underlying the DFT filter banks are optimized to provide maximum time-frequency resolution. The optimization is done using the concepts of time-frequency analysis and convex optimization. We formulate an objective function to represent the time-frequency distribution of signal energy and use numerical methods to obtain optimized prototypes. The simulation results show that the use of optimized DFT filter banks and cooperation between the sensing nodes give us better performance as compared to other sensing techniques.