Optimizing Time Slot Allocation in LEO Satellite Beam Hopping for Uneven Traffic Demands

This paper investigates beam hopping (BH) in a multibeam low Earth orbit (LEO) satellite system, addressing the challenges posed by uneven traffic demand (TD) distributions across different cells. Traditional approaches, such as the largest queue policy (LQP)-based greedy algorithm, often fail to adequately serve cells with lower traffic demands, leading to inefficiencies and potential service failure. In response, we propose a modified BH algorithm that prioritizes cells without assigned time slots before applying the LQP-based greedy approach, ensuring more equitable time slot allocation. The proposed method enhances the adaptability of the system to varying TD distributions while maintaining computational efficiency. Through simulation, we demonstrate that our approach achieves a 100% time slot allocation success rate across all cells, significantly improving system performance compared to the conventional LQP-based algorithm. This research provides a foundation for future work aimed at developing low-complexity methods for optimizing resource allocation in LEO satellite systems.