低轨通信卫星可以突破地形限制，与6G共同搭建天地一体化信息网络。由于其面对的全球用户需求分布不均，针对卫星关于地面固定终端的波束调度问题，提出一种能够实现时延和干扰双重优化的波束调度策略。结合发射功率、载噪比等约束，建立以排队时延和同频干扰最小化为优化目标的模型。通过分步优化，设计了需求分簇、时隙分配和波位匹配的波束跳变方案。其中针对波位匹配过程中的干扰优化问题，提出基于遗传算法的“簇内波位自交叉”的染色体交叉机制。仿真结果表明，与其他算法相比，改进遗传算法的同频干扰降低约32%~58%，且所提策略能够在资源分配周期内完成波束调度，同时实现时延和干扰的双重优化。
张盼盼
,
常家超
,
邹诚
,
李国通
. 基于改进遗传算法的低轨通信卫星跳波束调度策略[J]. 中国科学院大学学报, 2025
, 42(3)
: 382
-391
.
DOI: 10.7523/j.ucas.2023.054
Low earth orbit (LEO) communication satellites can break through terrain constraints and work with 6G to build an integrated space-ground information network. In terms of the beam scheduling problem of satellites for fixed terminals on the ground, a beam scheduling strategy that can achieve dual optimization of interference and delay is proposed, considering that the uneven distribution of global user demands exists. The model with the optimization goal of minimizing the queuing delay and co-channel interference is constructed, combining with constraints such as transmit power as well as carrier-to-noise ratio. By means of step-by-step optimization, a beam-hopping scheme including demand clustering, time slot allocation and beam position matching is designed. When it comes to the interference optimization problem in the beam position matching process, a genetic algorithm-based chromosome crossover mechanism of “beam position self-crossover within a cluster” is proposed. The simulation results show that the improved genetic algorithm can reduce the co-channel interference by 32% to 58% compared with the other algorithms. Besides, the proposed strategy can schedule the beam within the resource allocation period while achieving dual optimization of delay and interference.
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