For the transmission design problem in an IRS (intelligent reflecting surface)-enabled network, by jointly designing the transmit beamforming and IRS reflecting coefficient, the goal of this paper was to maximize the weighted sum rate for multiply ground users, subject to the transmit power and the unit modulus constraint. To solve the non-convex objective, we developed an alternating optimization method, where the phase shifter optimization was solved by the RMG (Riemannian manifold gradient) method, and the beamforming was obtained by the bisection search method. Furthermore, an element-wise block coordinate descent-based method was proposed to reduce the complexity of the RMG method. Simulation results verify the effectiveness of the proposed algorithm, and demonstrate that IRS can significantly improve the spectrum efficiency, when the reflecting coefficients are properly optimized.

This work investigates the potential of the aerial intelligent reflecting surface (AIRS) in secure communication, where an intelligent reflecting surface (IRS) carried by an unmanned aerial vehicle (UAV) is utilized to help the communication between the ground nodes. Specifically, we formulate the joint design of the AIRS’s deployment and the phase shift to maximize the secrecy rate. To solve the non-convex objective, we develop an alternating optimization (AO) approach, where the phase shift optimization is solved by the Riemannian manifold optimization (RMO) method, while the deployment optimization is handled by the successive convex approximation (SCA) technique. Furthermore, to reduce the computational complexity of the RMO method, an element-wise block coordinate descent (EBCD) based method is employed. Simulation results verify the effect of AIRS in improving the communication security, as well as the importance of designing the deployment and phase shift properly.