Optimal Relay Selection and Cooperative Power Allocation in Cognitive Radio Networks

It can greatly improve the system performance by introducing cooperative communication into Cognitive Radio Networks (CRNs), but it has also increased the complexity of the CRNs. As is known to all, the average throughput of the CRNs will decrease as the number of relay nodes increases. In order to solve this problem, we used a selection amplify-and-forward scheme to relay. In order to maximize the system throughput of the CRNs, based on maximizing the received SNR, we proposed an optimal power allocation algorithm combined with best relay selection and cooperative communication. First, by best relay selection algorithm, we can find the best relay link. Then, an optimal power allocation algorithm was proposed to maximize the system capacity of the CRNs under the constraints of limited interference to the primary users and limited total transmission power of the secondary users. Using the convex optimization theory and Kuhn - Tucker conditions, we obtain closed-form expressions for solving the optimal solution. Finally, Mat lab based simulation experiments are used to verify the superiority of the proposed algorithms. It shows that these algorithms can effectively reduce power consumption, fully use space diversity gain, increase system capacity, and improve QoS and system reliability.