Energy-Efficient Beamforming Based on Statistical CSI for Multicast LEO Satellite Communications

Low Earth Orbit (LEO) satellites have recently attracted attention as solutions for enabling global connectivity because of the low propagation latency and low path loss compared to other satellite systems. In the meantime, however, the high orbital speed as well as the low production cost have rendered power consumption minimization as one of the most critical issues for performance optimization in LEO satellite communications. In this paper, we investigate energy-efficient beamforming design for LEO satellites that support multigroup multicast downlink communications. Different from related work that assumes availability of instantaneous channel state information (CSI), our design relies only on the slow-varying statistical CSI (sCSI). The formulated problem aims to maximize energy efficiency while meeting the target data rate requirements. To solve the problem, we first approximate the average rate function by applying a closed-form tight upper bound. We then use the Dinkelbach's algorithm to transform the fractional function for energy efficiency into a concave function. We finally adopt the Convex-Concave Procedure (CCCP) to solve the problem. Numerical results show that the proposed algorithm is able to achieve higher energy efficiency than existing approaches for multicast LEO satellite communications.