Multibeam Jointly Processing in Dense LEO Constellations: Antennas Installed Centrally on a Single Satellite or Distributed Across Multiple Satellites?

In this paper, we consider a communication internet of things network where multiple low-Earth-orbit (LEO) satellites provide services to massive terminals under grant free-random access (GF-RA) mode. Due to the high mobility of LEO satellites and the uncoordinated access characteristics of GF-RA, acquiring instantaneous channel state information (CSI) becomes particularly challenging and the spatial configuration among satellites varies rapidly, which all severely restricts the implementation of multi-beam jointly processing (MBJP) in uplink. To overcome these challenges, we establish a unified multi-satellite cooperative MBJP (MSC-MBJP) framework, through leveraging the regional statistical CSI (RsCSI) and the specially designed satellite selection scheme. Specifically, we firstly construct a set consisting of the specially selected satellites in real time, to meet the requirements of maximizing the resources-utilization efficiency, reducing handover frequency among satellites as well as upgrading the performance of MBJP. Then, we propose the distributed MSC-MBJP and centralized MSC-MBJP schemes. Different from the distributed scheme, the centralized scheme relies on collecting the data from all cooperative satellites. Subsequently, considering the intrinsic relationship between MBJP and user scheduling, we jointly optimize the beamforming vectors and the link matrix to address the optimization problems associated with the proposed two schemes. Extensive simulations demonstrate that the proposed centralized MSC-MBJP scheme outperform the conventional single-satellite MBJP scheme. Moreover, the proposed distributed MSC-MBJP scheme can achieve the comparable user capacity when the transmit power of terminals is 35 dBmW. Especially, the proposed distributed MSC-MBJP scheme exists the superiority of the access success rate for terminals located near the area boundary, in terms of nearby 27% increment.