Abstract
The design of Internet of Thing (IoT) system over space-air-ground integrated network (SAGIN) is still in its infancy. It is critical to get 6G technology involved, in order to address the current problems in the combined SAGIN and IoT ecosystem. This work utilizes reconfigurable intelligent surface (RIS) to enhance the existing SAGIN infrastructure. We highlight channel modeling and estimate as a major component of RIS beam control and present a sparse Bayesian superresolution estimation approach to achieve a good balance of accuracy and computing complexity. Our numerical results justify that, with our proposed models and algorithms, RIS will become a cost-effective and spectral-efficient solution for SAGINbased 6G networks.
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