Sequential detection based cooperative spectrum sensing algorithms in cognitive radio

This paper considers the problem of Spectrum Sensing in Cognitive Radio Networks. For this we use a recently developed distributed cooperative algorithm DualCUSUM. The algorithm is based on sequential change detection techniques which optimally use the past observations. But DualCUSUM requires the knowledge of the channel gains for each of the secondary users. In this work we modify DualCUSUM to develop GLR-CUSUM which can work with imprecise estimates of the channel gains. Next we extend the algorithm to the case where the receiver noise power is also not known exactly. We show that the SNR wall problem encountered in this scenario is not experienced by our algorithm.