UAV-Enabled Jamming Noise for Achieving Secure Communications in Cognitive Radio Networks

In this paper, physical layer security is considered for cognitive radio networks using an unmanned aerial vehicle (UAV)-enabled jamming noise. In the studied model, a secondary transmitter sends confidential messages to a secondary receiver in the presence of an external eavesdropper (Eve), and the UAV acts as a friendly jammer that degrades the decoding capability of Eve. Therefore, resource allocation in such a network must jointly optimize the transmission power and UAV's trajectory to maximize the secrecy rate, while satisfying a given interference threshold at the primary receiver. The design problem is non convex, and thus, global optimality is difficult to obtain. Aiming to solve this problem, we first transform it into a more tractable form, and then propose a successive convex approximation-based algorithm for its solutions. The proposed algorithm has a low computational complexity and is guaranteed to obtain at least a locally optimal solution of the original problem. Numerical results are provided to demonstrate the effectiveness of the proposed design, compared to the existing ones.