Analysis of collaborative spectrum sensing with binary phase shift keying signal power estimation errors

Novel iterative and non-iterative blind estimation methods for binary phase shift keying modulated primary user signal power are proposed using the maximum-likelihood principle for collaborative spectrum sensing. Using these estimators, the performance of three different existing collaborative spectrum sensing methods is compared under realistic scenarios. The effect of the primary user traffic on these methods is also explored. Numerical results show that, unlike the case of no estimation error as examined in this literature, the performance gains of the weighted linear combining and optimal combining methods over the conventional equal gain combining method decrease or even become negative when there is estimation error. They also show that the proposed blind estimation methods offer an excellent trade-off between reliability and complexity.