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
[ "柴蓉 女,1974年7月出生于青海省西宁市。现为重庆邮电大学教授、博士生导师。主要研究方向为空天地一体化网络架构及关键技术等。E-mail: chairong@cqupt.edu.cn" ]
[ "刘瑾 女,1996年11月出生于河北省唐山市。现为重庆邮电大学硕士研究生。主要研究方向为卫星通信、无线资源分配等。E-mail: s230131065@stu.cqupt.edu.cn" ]
[ "梁承超 男,1988年4月出生于贵州省贵阳市。现为重庆邮电大学教授、博士生导师。主要研究方向为移动通信、无线网络、卫星互联网及优化理论等。E-mail: liangcc@cqupt.edu.cn" ]
[ "陈前斌 男,1967年4月出生于四川省营山县。现为重庆邮电大学教授。主要研究方向为无线通信等。中国电子学会会员编号:E190000713S。E-mail: chenqb@cqupt.edu.cn" ]
收稿:2025-02-14,
录用:2026-01-04,
纸质出版:2026-01-25
移动端阅览
柴蓉, 刘瑾, 梁承超, 等. 基于RSMA的LEO卫星通信系统宽点波束调度及预编码算法[J]. 电子学报, 2026, 54(01): 308-317.
CHAI Rong, LIU Jin, LIANG Chengchao, et al. Wide-Spot Beam Scheduling and Precoding Algorithm for RSMA-Based LEO Satellite Communication Systems[J]. Acta Electronica Sinica, 2026, 54(01): 308-317.
柴蓉, 刘瑾, 梁承超, 等. 基于RSMA的LEO卫星通信系统宽点波束调度及预编码算法[J]. 电子学报, 2026, 54(01): 308-317. DOI:10.12263/DZXB.20250114
CHAI Rong, LIU Jin, LIANG Chengchao, et al. Wide-Spot Beam Scheduling and Precoding Algorithm for RSMA-Based LEO Satellite Communication Systems[J]. Acta Electronica Sinica, 2026, 54(01): 308-317. DOI:10.12263/DZXB.20250114
多波束低地球轨道(Low Earth Orbit,LEO)卫星通信系统因具有广覆盖、高吞吐量、低时延及部署成本低等特性而受到广泛关注。本文研究基于速率分割多址接入(Rate Splitting Multiple Access,RSMA)机制的多波束LEO卫星通信系统的用户分簇、混合宽点波束调度及预编码问题。综合考虑簇内及簇间相似度,提出一种基于改进均值漂移算法的用户分簇策略。首先根据用户地理位置分布及卫星点波束覆盖范围确定初始分簇结果,进而引入簇内分散度及簇间距离等指标构建成簇评估函数,并设计基于高斯核函数的调参机制,根据成簇评估结果动态调整参数,以实现簇内用户聚合性与簇间区分度的协同优化。基于所确定的用户分簇策略,进而设计一种双空间尺度资源分配策略。具体地,在较大空间尺度,研究面向多个用户簇的宽波束覆盖问题。综合考虑星间传输性能差异及用户接入性能,建模系统成本函数,将宽波束覆盖问题建模为满足约束条件的系统成本函数最小化问题。采用分支定界法求解所建模问题,通过系统性地分解搜索空间,并结合上下界剪枝策略,逐步缩小可行解范围,从而确定宽波束覆盖的用户簇集合。基于给定的宽波束覆盖策略,在较小空间尺度,设计面向单用户簇的点波束调度及预编码方案,将点波束调度及预编码问题建模为长期卫星缓存队列长度最小化问题,并将所建模问题拆分为预编码子问题及点波束调度子问题依次进行求解。针对预编码子问题,首先引入松弛变量将目标函数转换为凸函数,进而针对非凸约束条件,采用一阶泰勒展开方法对其进行转换,并将包含非线性乘积项的凸约束转换为二阶锥约束,从而得到凸优化问题,可采用工具包进行高效求解。针对点波束调度子问题,将其建模为马尔可夫决策过程,并基于近端策略优化(Proximal Policy Optimization,PPO)算法确定点波束调度策略。仿真结果验证了所提算法的有效性。
Multi-beam low earth orbit (LEO) satellite communication systems have attracted significant attention due to their wide coverage
high throughput
low latency and low deployment cost. In this paper
user clustering
hybrid wide-spot beam scheduling and precoding issues are investigated for rate splitting multiple access (RSMA)-based multi-beam LEO satellite communication systems. Considering intra- and inter-cluster similarities
a user clustering strategy based on an improved mean shift algorithm is proposed. Initial clustering results are firstly obtained according to the geographic distribution of users and the coverage area of satellite spot beams
and a clustering evaluation function is constructed by incorporating intra-cluster dispersion and inter-cluster distance
a Gaussian kernel-based parameter adjustment mechanism is designed to dynamically tune parameters according to the evaluation results
thereby achieving a synergistic optimization of intra-cluster user compactness and inter-cluster separability. Then
a dual spatial-scale resource allocation strategy is further developed based on the determined user clustering strategy. Specifically
at a large spatial scale
the problem of wide-beam coverage for multiple user clusters is studied. Taking both the inter-satellite transmission performance differences and user access performance into account
the system cost function is modeled
and the wide-beam coverage problem is formulated as a system cost function minimization problem
which is solved using the branch-and-bound method. By systematically decomposing the search space and exploiting upper- and lower-bound pruning strategies
the feasible solution space is progressively reduced to obtain the set of user clusters for wide-beam coverage. At a small spatial scale
based on the wide-beam coverage strategy
spot beam scheduling and precoding schemes are designed for individual user cluster. The spot beam scheduling and precoding problem is formulated as a long-term satellite cache queue length minimization problem and decomposed into a precoding subproblem and a spot beam scheduling subproblem
solving them in sequence. For the precoding subproblem
the objective function is initially transformed into a convex form by introducing relaxation variables. For the non-convex constraints
we apply the first order Taylor expansion method to transform the constraints into convex ones
and the convex constraints involving nonlinear product terms are further transformed into second-order cone constraints
leading to a convex problem that can be efficiently solved using toolkits. Regarding the spot beam scheduling subproblem
it is modeled as a Markov decision process and the spot beam scheduling strategy is determined using the proximal policy optimization (PPO) algorithm. Simulation results validate the effectiveness of the proposed algorithm.
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