Blind cooperative parametric spectrum sensing with distributed sensors using local average power passing
This work deals with the issue of blind cooperative spectrum sensing using distributed sensors with large-scale fading. We first investigate the Friedman-test-based nonparametric detector and analyze its performance. Due to the operations of instantaneous power passing and ranking, the nonparametric detector has relatively high-sensing overhead and computational complexity. To overcome these drawbacks, we then propose a blind cooperative parametric detector for which only local average power passing is needed and instantaneous power ranking is avoided. Compared with the nonparametric detector, the parametricdetectordeliversbetterperformancewithmuch lower overhead and complexity. The detection probability and false alarm probability of the parametric detector are analyzed, and its decision threshold is derived. Simulation results demonstrate the superior performance of the parametric detector, compared with the energy detector and the eigenvalue-based detectors in the literature.
M. Jin, Q. Guo, Y. Li, J. Xi, G. Wang & D. Huang, "Blind cooperative parametric spectrum sensing with distributed sensors using local average power passing," IEEE Transactions on Vehicular Technology, vol. 65, (12) pp. 9703-9714, 2016.