This is a code package related to the following scientific article:
P. Zhang, J. Zhang, H. Xiao, H. Du, D. Niyato and B. Ai, "RIS-Aided 6G Communication System With Accurate Traceable User Mobility," in IEEE Trans. Veh. Tech., 2022.
P. Zhang, J. Zhang, H. Xiao, X. Zhang, D. W. K. Ng and B. Ai, "Joint Distributed Precoding and Beamforming for RIS-Aided Cell-Free Massive MIMO Systems," in IEEE Trans. Veh. Tech., 2023.
The package contains a simulation environment, based on Matlab, that reproduces some of the numerical results and figures in the article. We encourage you to also perform reproducible research!
The amalgamation of cell-free networks and reconfigurable intelligent surface (RIS) has become a prospective technique for future sixth-generation wireless communication systems. In this paper, we focus on the precoding and beamforming design for a downlink RIS-aided cell-free network. The design is formulated as a non-convex optimization problem by jointly optimizing the combining vector, active precoding, and passive RIS beamforming for minimizing the weighted sum of users' mean square error. A novel joint distributed precoding and beamforming framework is proposed to decentralize the alternating optimization method for acquiring a suboptimal solution to the design problem. Finally, numerical results validate the effectiveness of the proposed distributed precoding and beamforming framework, showing its low-complexity and improved scalability compared with the centralized method.
This code package is licensed under the GPLv2 license. If you in any way use this code for research that results in publications, please cite our original article listed above.