Cost Function Optimization-Based Beam Scheduling and Resource Allocation Algorithm for Multibeam Satellite Communication Systems

ZHANG Si-ya; CHAI Rong; LIANG Cheng-chao; CHEN Qian-bin

doi:10.12263/DZXB.20240116

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Cost Function Optimization-Based Beam Scheduling and Resource Allocation Algorithm for Multibeam Satellite Communication Systems

PAPERS | 更新时间：2025-07-24

- Cost Function Optimization-Based Beam Scheduling and Resource Allocation Algorithm for Multibeam Satellite Communication Systems
  增强出版
- ACTA ELECTRONICA SINICA Vol. 53, Issue 4, Pages: 1232-1240(2025)
- 作者机构：
  
  1.重庆邮电大学通信与信息工程学院，重庆 400065
  2.重庆市移动通信技术重点实验室，重庆 400065
- 作者简介：
- 基金信息：
  
  National Natural Science Foundation of China(62271097)
- DOI：10.12263/DZXB.20240116
  CLC： TN927+.2
- Received：30 January 2024，
  
  Revised：2024-09-24，
  
  Published：25 April 2025
- 稿件说明：
移动端阅览
张思雅, 柴蓉, 梁承超, 等. 基于成本函数优化的多波束卫星通信系统波束调度及资源分配算法[J]. 电子学报, 2025, 53(04): 1232-1240.

ZHANG Si-ya, CHAI Rong, LIANG Cheng-chao, et al. Cost Function Optimization-Based Beam Scheduling and Resource Allocation Algorithm for Multibeam Satellite Communication Systems[J]. Acta Electronica Sinica, 2025, 53(04): 1232-1240.
张思雅, 柴蓉, 梁承超, 等. 基于成本函数优化的多波束卫星通信系统波束调度及资源分配算法[J]. 电子学报, 2025, 53(04): 1232-1240. DOI：10.12263/DZXB.20240116

ZHANG Si-ya, CHAI Rong, LIANG Cheng-chao, et al. Cost Function Optimization-Based Beam Scheduling and Resource Allocation Algorithm for Multibeam Satellite Communication Systems[J]. Acta Electronica Sinica, 2025, 53(04): 1232-1240. DOI：10.12263/DZXB.20240116

摘要

多波束卫星通信系统由于其可实现高吞吐量及高效资源利用而受到广泛关注.本文研究多波束卫星通信系统的波束调度及资源分配问题，综合考虑用户地理位置及业务特性，提出基于Optics的用户初始分组算法.为提升波束覆盖性能，设计基于最小圆的卫星波位点及覆盖半径优化方案.基于所确定的用户分组策略，定义系统成本函数，并将联合波束调度、子信道选择及功率分配问题建模为系统成本函数最小化问题.为求解所建模型的优化问题，首先引入聚合节点描述各用户组特性，并提出基于参数化深度

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网络的联合波束调度及功率分配算法；然后基于所确定的用户组波束调度及功率分配策略，提出基于双深度

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学习算法及基于近端策略优化算法的联合子信道及功率分配策略.仿真结果验证了所提算法的

有效性.

Abstract

Multibeam satellite communication systems have received widespread attentions due to their high throughput and efficient resource utilization. This paper investigates the beam scheduling and resource allocation problem in multibeam satellite communication system. By jointly considering user position and service characteristics

an optics-based initial user grouping algorithm is proposed. To enhance beam coverage performance

a minimum circle algorithm is proposed to optimally design satellite beam positions and coverage radius. Given the determined user grouping strategy

system cost function is defined and the joint beam scheduling

sub-channel allocation and power allocation problem is formulated as a system cost function minimization problem. To solve the formulated optimization problem

aggregate nodes are introduced to describe the characteristics of user groups

and a parameterized deep

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-network-based joint beam scheduling and power allocation algorithm is proposed. Based on the obtained user group beam scheduling and power allocation strategy

a double deep

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-network algorithm and a proximal policy optimization-based joint subchannel and power allocation strategies are proposed. Simulation results validate the effectiveness of the proposed algorithms.

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references

CENTENARO M , COSTA C E , GRANELLI F , et al . A survey on technologies, standards and open challenges in satellite IoT [J ] . IEEE Communications Surveys & Tutorials , 2021 , 23 ( 3 ): 1693 - 1720 .

XIAO A L , WANG X C , WU S , et al . Mobility-aware resource management for integrated satellite-maritime mobile networks [J ] . IEEE Network , 2022 , 36 ( 1 ): 121 - 127 .

CHEN H J , QI C H . User grouping for sum-rate maximization in multiuser multibeam satellite communications [C ] // ICC 2019-2019 IEEE International Conference on Communications (ICC) . Piscataway : IEEE , 2019 : 1 - 6 .

HONNAIAH P J , MATURO N , CHATZINOTAS S , et al . Demand-based adaptive multi-beam pattern and footprint planning for high throughput GEO satellite systems [J ] . IEEE Open Journal of the Communications Society , 2021 , 2 ( 1 ): 1526 - 1540 .

EFREM C N , PANAGOPOULOS A D . Dynamic energy-efficient power allocation in multibeam satellite systems [J ] . IEEE Wireless Communications Letters , 2020 , 9 ( 2 ): 228 - 231 .

ABDU T S , KISSELEFF S , LAGUNAS E , et al . Flexible resource optimization for GEO multibeam satellite communication system [J ] . IEEE Transactions on Wireless Communications , 2021 , 20 ( 12 ): 7888 - 7902 .

ZHAO B , DONG X D , REN G L , et al . Optimal user pairing and power allocation in 5G satellite random access networks [J ] . IEEE Transactions on Wireless Communications , 2022 , 21 ( 6 ): 4085 - 4097 .

VAN CHIEN T , LAGUNAS E , TA T H , et al . User scheduling and power allocation for precoded multi-beam high throughput satellite systems with individual quality of service constraints [J ] . IEEE Transactions on Vehicular Technology , 2023 , 72 ( 1 ): 907 - 923 .

WANG A Y , LEI L , LAGUNAS E , et al . Joint optimization of beam-hopping design and NOMA-assisted transmission for flexible satellite systems [J ] . IEEE Transactions on Wireless Communications , 2022 , 21 ( 10 ): 8846 - 8858 .

ZHAO D , QIN H , XIN N , et al . Flexible resource management in high-throughput satellite communication systems: A two-stage machine learning framework [J ] . IEEE Transactions on Communications , 2023 , 71 ( 5 ): 2724 - 2739 .

PENG D Y , BANDI A , LI Y , et al . Hybrid beamforming, user scheduling, and resource allocation for integrated terrestrial-satellite communication [J ] . IEEE Transactions on Vehicular Technology , 2021 , 70 ( 9 ): 8868 - 8882 .

LIAO X L , HU X , LIU Z J , et al . Distributed intelligence: A verification for multi-agent DRL-based multibeam satellite resource allocation [J ] . IEEE Communications Letters , 2020 , 24 ( 12 ): 2785 - 2789 .

DENG D H , WANG C W , PANG M L , et al . Dynamic resource allocation with deep reinforcement learning in multibeam satellite communication [J ] . IEEE Wireless Communications Letters , 2023 , 12 ( 1 ): 75 - 79 .

LI X N , ZHANG H J , ZHOU H , et al . Multi-agent DRL for resource allocation and cache design in terrestrial-satellite networks [J ] . IEEE Transactions on Wireless Communications , 2023 , 22 ( 8 ): 5031 - 5042 .

LIN Z Y , NI Z Y , KUANG L L , et al . Dynamic beam pattern and bandwidth allocation based on multi-agent deep reinforcement learning for beam hopping satellite systems [J ] . IEEE Transactions on Vehicular Technology , 2022 , 71 ( 4 ): 3917 - 3930 .

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