Hierarchical Power Control in Cognitive Networks

We investigate the interactive behavior and strategic decision-making between multiple secondary users (SUs) and primary users (PUs), both of which are end-to-end performance aware in cognitive networks. A Stackelberg game is utilized to formulate the spectrum utilization maximization problem after the complex interference situation is analyzed. Especially, an interference power cap (IPC) function predefined by PUs as a pricing function is introduced into the utility function design of SUs to guarantee QoS of PUs, as well as to decouple constraints. Further, an asymmetric information situation can be formed by considering PUs as leaders who employ the optimal water-filling algorithm, and the closed-form power strategy of SUs can be derived. And accordingly, SUs as followers can observe the available information to do more foresighted decision by learning. What is more, we prove the optimality and existence of the deceived solutions. Numerical results demonstrate that the proposed distributed algorithm provides more spectrum revenue and better QoS guarantees to PUs with limited iterations.