Towards Integrated Terrestrial-Satellite Network via Intelligent Reflecting Surface
Hao Dong, Cunqing Hua, Lingya Liu, Wenchao Xu
Abstract
This paper investigates an intelligent reflecting surface (IRS)-aided integrated terrestrial-satellite network (ITSN) system for the low channel gain users, where an 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 two systems should be carefully mitigated. We aim for maximizing the weighted sum rate (WSR) of all users through jointly optimizing the frame based coordinated transmit beamforming vectors at the SBSs and the phase shift matrix at the IRS, and the frame user scheduling subject to each SBS's power and unit modulus. To this end, we propose efficient algorithms based on alternating optimization, in which the transmit beamforming vectors and reflective phase shifts matrix are optimized in an alternating manner. In particular, we develop the second-order-cone programming (SOCP) for optimizing the coordinated transmit beamforming and propose the Riemannian conjugate gradient (RCG) for updating the reflecting shifts. For frame user scheduling, we propose the chordal distance measure method to improve the intra-fame correlation. Simulation results verify the effectiveness of the proposed algorithm compared with different benchmark schemes.