Joint Trajectory and Primary-Secondary Transmission Design for UAV-Carried-IRS Assisted Underlay CR Networks

A novel unmanned aerial vehicle-carried-intelligent reflecting surface (UAV-carried-IRS)-assisted underlay cognitive radio network (UAV-IRS-UCRN) is investigated, where dynamic UAV-carried-IRS inherits the advantages of IRS and adds a new motion dimension to flexibly assist the primary user (PU)-secondary user (SU) transmission, and both the PU and the SU enjoy seamless connectivity at all the times. A SU's average rate-maximized optimization problem is constructed under fully satisfying the service quality of PU. Since the strong coupling of the optimization variables makes solving this problem very tricky, the original problem is divided into the SU's transmitted power sub-problem, the phase shift matrix and the trajectory of UAV-carried-IRS sub-problems. Then, the sub-problems are solved by deriving the closed-form solution and exploiting semi-definite relaxation, charnes-cooper transformation and successive convex approximation techniques. Finally, a joint optimization algorithm based on alternating iterative framework is proposed to solve the original problem. Numerical results show that the performances of both PU and SU transmissions are significantly improved in contrast to only UAV-carried-IRS-assisted SU and fixed trajectory algorithms.