Intelligent Reflecting Surface-Aided Integrated Terrestrial-Satellite Networks

Abstract

Intelligent reflecting surface (IRS) is a novel technology to manipulate wireless propagation channels via smart and controllable signal reflection. In this paper, we investigate an IRS-aided integrated terrestrial-satellite network (ITSN) system, where the IRS is deployed to assist the co-existing transmissions of the terrestrial small base stations (SBSs) and the satellite. Because of the spectrum sharing in the ITSN, the interference between the two systems should be carefully mitigated. Our objective is to maximize the weighted sum rate (WSR) of all users by jointly optimizing the frame-based coordinated transmit beamforming vectors at the SBSs, the phase shift matrix at the IRS, and the frame user scheduling, subject to SBSs’ individual power constraints and unit modulus constraints of phase shifters. To this end, we first adopt the agglomerative hierarchical clustering (AHC) method to schedule the satellite users to different frames. Then the block coordinate descent (BCD) algorithm is proposed, which alternately optimizes the transmit beamforming vectors and the reflective phase shift matrix. In particular, the optimal transmit beamforming vectors are obtained via the fractional programming (FP) technique. Meanwhile, two efficient algorithms, i.e., the Riemannian manifold (RM) and the successive convex approximation (SCA), are proposed for the phase shift optimization. Finally, simulation results are provided to demonstrate the performance gain of our schemes over other benchmark schemes.