Distributed cooperative spectrum sensing with selective updating

This paper investigates the use of adaptive filtering with selective updating in a distributed spectrum sensing network. Through a structure similar to a set-membership filter, coefficient updating is not performed at every single input data, reducing misadjustment, computational complexity and power requirements at each sensing node. Results, presented in terms of convergence behavior and complementary receiver operating characteristic curves, show a substantial reduction in the number of updates performed by the adaptive filter without degrading the detection performance.