基于AoI的低轨卫星网络动态用户调度与资源分配算法

戴叶玲; 郭焱; 刘笑宇; 韩略; 林敏

doi:10.12263/DZXB.20250996

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基于AoI的低轨卫星网络动态用户调度与资源分配算法

学术论文 | 更新时间：2026-06-22

- 基于AoI的低轨卫星网络动态用户调度与资源分配算法
- AoI-Based Dynamic User Scheduling and Resource Allocation Algorithm in LEO Satellite Networks
- 电子学报 2026年54卷第1期页码：318-328
- 作者机构：
  
  南京邮电大学通信与信息工程学院，江苏南京 210003
- 作者简介：
  
  戴叶玲女，2001年2月出生于江苏省南通市。现为南京邮电大学通信与信息工程学院博士研究生。主要研究方向为卫星通信、无线通信等。E-mail： dyl424123@163.com
  郭焱女，2000年1月出生于山西省晋中市。现为南京邮电大学通信与信息工程学院博士研究生。主要研究方向为卫星通信、移动通信等。E-mail： gy005311@163.com
  刘笑宇男，1996年3月出生于江苏省淮安市。现为南京邮电大学预聘副教授。主要研究方向为空天地一体化信息网络等。E-mail： xiaoyu.liu@njupt.edu.cn
  韩略男，1992年4月出生于江苏省淮安市。现为南京邮电大学讲师。主要研究方向为空天地一体化、性能分析等。中国电子学会会员编号：E190184285M。E-mail： 20220085@njupt.edu.cn
  林敏男，1972年10月出生于浙江省台州市。现为南京邮电大学教授、博士生导师。主要研究方向为无线通信系统、智能信号处理、天线新技术。E-mail： linmin@njupt.edu.cn
- 基金信息：
  
  国家自然科学基金(62471255;62501310);南京邮电大学引进人才自然科学研究启动基金(NY222114;NY224068);江苏省高等学校自然科学研究项目(24KJB510029);江苏省研究生科研与实践创新计划（No.KYCX25_1106,No.KYCX24_1178）
- DOI：10.12263/DZXB.20250996
  中图分类号： TN92;
- 收稿：2025-12-05，
  
  录用：2026-01-13，
  
  纸质出版：2026-01-25
- 稿件说明：
移动端阅览
戴叶玲, 郭焱, 刘笑宇, 等. 基于AoI的低轨卫星网络动态用户调度与资源分配算法[J]. 电子学报, 2026, 54(01): 318-328.

DAI Yeling, GUO Yan, LIU Xiaoyu, et al. AoI-Based Dynamic User Scheduling and Resource Allocation Algorithm in LEO Satellite Networks[J]. Acta Electronica Sinica, 2026, 54(01): 318-328.
戴叶玲, 郭焱, 刘笑宇, 等. 基于AoI的低轨卫星网络动态用户调度与资源分配算法[J]. 电子学报, 2026, 54(01): 318-328. DOI：10.12263/DZXB.20250996

DAI Yeling, GUO Yan, LIU Xiaoyu, et al. AoI-Based Dynamic User Scheduling and Resource Allocation Algorithm in LEO Satellite Networks[J]. Acta Electronica Sinica, 2026, 54(01): 318-328. DOI：10.12263/DZXB.20250996

摘要

针对低轨（Low Earth Orbit，LEO）卫星网络上行接入场景中用户规模庞大、业务产生随机、信息时效需求差异显著以及卫星载荷受限等问题，本文提出一种基于信息年龄（Age of Information，AoI）的动态用户调度与资源分配算法。具体来说，在考虑用户数据包随机产生的情况下，以最小化系统长时平均发射功率为优化目标，在满足用户最大长时平均AoI、每时隙受调用户数和服务质量（Quality of Service，QoS）需求的多重约束下，构建包含用户调度、波束成形与功率分配的长时联合优化问题，旨在保障用户信息时效性的同时有效降低系统长时平均功耗。鉴于该问题同时包含长时目标与约束，且优化变量相互耦合，难以直接求解，首先基于用户数据包产生的伯努利分布特性，引入李雅普诺夫优化理论，将原长时优化问题转化为逐时隙可解的漂移加惩罚上界最小化问题，从而实现在线动态决策并保证AoI约束的长期可满足性。接着，针对大规模用户接入场景下调度复杂度随用户数指数增长的问题，进一步基于用户角度信息设计谱聚类分组方法，将空间相关性低的用户划分至同组，从而降低组内干扰并提高传输可靠性。在此基础上，构造融合用户AoI状态、数据包产生特性及预估功耗的调度代价函数，实现兼顾信息时效性与功耗的低复杂度动态用户调度策略。在资源分配阶段，针对受调用户集相关波束成形与发射功率非凸耦合的问题，结合S-procedure与泰勒展开方法，将原非凸约束逐步转化为凸约束，从而设计满足QoS与功率约束的最优资源分配算法。最后，通过计算机对所提算法进行仿真验证。结果表明，相比于固定数量调度算法、贪婪AoI调度算法以及最小均方误差算法，所提算法在不同用户规模和AoI约束条件下均能有效保证用户信息时效性需求，并显著降低系统长时平均功耗，验证了所提算法在LEO卫星网络多用户接入场景中的有效性与优越性。

Abstract

For the multi-user uplink access scenario in low-earth orbit (LEO) satellite networks

the system faces significant challenges arising from large-scale user populations

stochastic traffic arrivals

heterogeneous information timeliness requirements

and stringent onboard constraints. To address these issues

this paper proposes an age of information(AoI)-based dynamic user scheduling and resource allocation algorithm

aiming to guarantee information timeliness while effectively reducing the long-term average transmit power. Specifically

under random packet arrivals modeled as Bernoulli processes

the long-term average transmit power minimization problem is formulated subject to constraints on users’ maximum long-term average AoI

the per-slot number of scheduled users

and quality-of-service (QoS) requirements. The resulting optimization problem jointly considers user scheduling

beamforming

and power allocation

and is characterized by long-term objectives and constraints as well as coupling among optimization variables

which renders it intractable for direct solution. To overcome this challenge

Lyapunov optimization theory is employed to transform the original long-term problem into a per-slot drift-plus-penalty minimization problem

enabling online decision-making while ensuring the long-term satisfaction of AoI constraints. Furthermore

to mitigate the exponential growth in scheduling complexity with respect to the number of users

a spectral clustering-based grouping method is developed based on users’ angular information

which groups spatially weakly correlated users together to reduce intra-group interference and enhance transmission reliability. On this basis

a low-complexity dynamic scheduling policy is designed via a scheduling cost function that jointly incorporates users’ AoI states

packet arrival characteristics

and estimated power consumption

achieving a balanced tradeoff between information freshness and power consumption. For the resource allocation stage

the non-convex coupling between beamforming and transmit power of pertinent scheduled user set is addressed by leveraging the S-procedure and Taylor series expansion

whereby the original non-convex constraints are transformed into convex forms

yielding an optimal QoS-satisfied and power-constrained resource allocation algorithm. Simulation results demonstrate that

compared with fixed-size scheduling

greedy AoI-based scheduling

and minimum mean square error-based schemes

the proposed algorithm effectively satisfies information timeliness requirements while significantly reducing the long-term average transmit power under various user scales and AoI constraints

establishing the proposed algorithm as an effective and superior solution for multi-user LEO satellite access.

关键词

Keywords

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