Uplink Multi-Beam Jointly Processing With the Regional Statistical CSI for Satellite IoT Networks

The situations (e.g., light control and Global Navigation Satellite System unavailable for terminals), as well as the long propagation delay and the high mobility in Low-Earth-Orbit (LEO) satellite Internet of Things networks, may result in that the perfect instantaneous channel state information (CSI) becomes hard to be acquired at satellites. To address this issue, we construct a unified regional statistical CSI (RsCSI) model for different scenarios (e.g., dense urban, urban, suburban and rural), without requiring the perfect positions of terminals and instantaneous CSI (iCSI). Our RsCSI model of a specific region is characterized by the channel power and the channel direction vector of the center point in this subregion, as well as the large-scale parameters. There parameters are fitted as a function of the varying elevation angle as the LEO satellite moves. Furthermore, our constructed model is also utilized for assisting the multi-beam jointly processing (MBJP), to optimize the user capacity. Performance evaluations show that our RsCSI aided MBJP obviously outperforms the conventional seven-color fequency reuse scheme in terms of a higher user capacity, whist the user capacity of RsCSI aided MBJP is a bit lower than that of the iCSI aided MBJP. The lifetime of the beamforming vectors generated by the RsCSI increases with a decreasing elevation angle, and the lifetime is more than 5 seconds when the elevation angle is 40°.