天地一体化信息网络2026，Vol.7Issue(2)：22-34,13.DOI:10.11959/j.issn.2096-8930.2026014
低轨多波束卫星下行业务强度时空预测方法
Spatio-temporal prediction method for the downlink service intensity of low-orbit multi-beam satellites
摘要
Abstract
LEO mega-constellations are revolutionizing global broadband connectivity landscape.However,constrained by the multidi-mensional scarcity of on-board power,spectrum bandwidth,and beam hopping time slots,efficient resource scheduling critically de-pends on prior knowledge of future traffic demands.Consequently,achieving robust multi-step forecasting of downlink traffic intensity at the logical beam level is indispensable for enabling proactive resource provisioning.To address the long-term periodicity and local burstiness of satellite traffic,a decoupled spatio-temporal forecasting framework is proposed.Specifically,this method utilizes data-adaptive orthogonal complex-valued bases to extract dominant temporal evolution patterns,achieving trend prediction via low-dimensional subspace projection and basis extension.Subsequently,a sparse vector autoregression model is introduced to model predic-tion residuals,explicitly capturing transient spatial couplings among beams.Experimental results demonstrate that,leveraging its com-pact representation and sparse structure,the proposed framework achieves superior prediction accuracy with significantly reduced com-putational overhead compared to existing baselines algorithms.关键词
卫星网络/流量分析/时空预测Key words
satellite networks/traffic analysis/spatio-temporal prediction分类
信息技术与安全科学引用本文复制引用
郑弘毅,张婷婷..低轨多波束卫星下行业务强度时空预测方法[J].天地一体化信息网络,2026,7(2):22-34,13.基金项目
国家自然科学基金资助项目(No.62401047) The Nationl Natural Science Foundation of China(No.62401047) （No.62401047）
