Overhead Reduction in Cooperative Spectrum Sensing Via Sequential Detection in Cognitive Radio Networks Under Bandwidth Constraint

Reliable and efficient spectrum sensing plays an important role in cognitive radio networks. On the other hand, accurate and fast sensing of spectrum is the main function of a cognitive radio for cognitive users to avoid harmful interference in licensed users. However, detection performance issues are often shadowing, fading and receiver uncertainty. To mitigate the impact of these issues, cooperative spectrum sensing as an effective method is presented to improve the detection performance with help of spatial diversity. Cooperative spectrum sensing leads to CR detection performance improvement. In order to execute the cooperative spectrum sensing among cognitive radio users, data fusion schemes are superior to that of decision fusion ones in terms of the detection performance but suffer from the disadvantage of huge traffic overhead when bandwidth constraint of communication channels is taken into account. The overhead contains additional sensing time, delay, energy and sensing actions dedicated to cooperative sequential sensing any also contains any performance degradation that is caused by cooperative sensing. The purpose of this paper is reviewing of the cooperative sensing techniques with sequential methods. The simulation results show that with reducing the number of examined samples, the sensing time and the energy will be reduced and as the result, the overhead will be reduced.