Robust Beamforming for Reconfigurable Intelligent Surface Aided Coordinated Multipoint Transmission

This paper studies the robust beamforming design for reconfigurable intelligent surface (RIS) assisted multicell wireless networks, where a RIS is deployed at the edge of cells to assist the joint processing coordinated multipoint transmission from multiple base stations (BSs) to multiple cell-edge users. Considering the imperfect cascade channel state information, we aim to minimize the total transmit power by jointly optimizing the transmit beamforming at the BSs and the phase shifts at the RIS, while satisfying the BSs' individual power constraints and users' worst case target rate constraint. To solve this nonconvex problem of complex coupling of variables, we decouple it into two sub-problems and introduce an alternating optimization framework. The transmit beamforming sub-problem can be recast in a convex form by using the S-Procedure and semidefinite relaxation techniques, when fixing the phase shifts. Subsequently, we transform the phase shifts sub-problem into an object-specific optimization problem, and then an iterative algorithm based on bisection method is proposed to obtain the solution. Simulation results show that the proposed robust beamforming design can converge rapidly and outperforms the reference scheme.