Power Gain Estimation and Its Impact on Binary Power Control in Underlay Cognitive Radio

We propose a novel minimum mean square error estimator that estimates the channel power gain of the link from the secondary transmitter to the primary receiver (PRx). It lowers the root mean square error compared to several other estimators used in the underlay cognitive radio literature that first estimate the channel amplitude. We then analyze its system impact for two types of interference constraints. To this end, for the optimal binary transmit power control policy, we derive closed-form expressions for the average interference and the probability that the interference at the PRx violates a peak interference constraint with the proposed estimator. We show that the proposed estimator performs closer to the perfect channel state information scenario compared to the other estimators.