Chance-constraint optimization of power control in cognitive radio networks

In this paper, to minimize the transmission power of cognitive users in underlay cognitive radio networks, a robust power control algorithm is proposed considering the uncertain channel gains. To deal with the uncertainty, we present an opportunistic power control strategy, i.e., the outage probability of all cognitive users and primary users should be reduced below their predefined thresholds. The strategy is the joint design of primary users’ communication protection and cognitive users’ optimal power allocation. A chance constraint robust optimization approach is applied, which can transform the uncertain problem into a deterministic problem. Then, a distributed probabilistic power algorithm is introduced, which ensures the optimization of cognitive users’ power allocation based on the standard interference function and restricts the interference at primary receivers by adjusting the maximum transmission power of cognitive users. Moreover, the admission control is introduced to exploit the network resources more effectively. Numerical results show the convergence and effectiveness of the proposed robust distributed power control algorithm.