Abstract:

To address the problem that it is difficult for the secondary unmanned aerial vehicle （UAV） to acquire the accurate channel state information （CSI） of the eavesdropping channel in UAV cognitive radio systems， which reduces the security performance of the secondary system， this paper proposes a robust method to enhance the security transmit performance of the secondary user （SU） by using intelligent reflecting surface （IRS） to assist UAV cognitive communication. Under the constraints of the interference temperature of the primary user （PU）， a deterministic model is established to describe the uncertainty of the CSI of the eavesdropping channel， and the phase shift matrix of IRS， the flight trajectory and transmit power of the UAV are jointly optimized to maximize the average worst‑case secrecy rate of the SU. To tackle the non‑convexity of the formulated optimization problem， an effective three‑stage iterative algorithm is presented based on alternating optimization， successive convex approximation， S-Procedure， and semi‑definite relaxation methods. The simulation results show that compared to non‑robust scheme， the proposed robust scheme can significantly improve the secure performance of the SU.

Key words: cognitive UAV network, secure communication, intelligent reflecting surface, alternating optimization, successive convex approximation