Temporal-frequency-spatial spectrum situation prediction: from the perspective of deep feature learning

Pan Guangliang; Zhang Ying; Zhao Haitao; Wu Qihui

doi:10.11959/j.issn.1000-436x.TXXB250612

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Temporal-frequency-spatial spectrum situation prediction: from the perspective of deep feature learning

Papers | 更新时间：2026-06-10

- Temporal-frequency-spatial spectrum situation prediction: from the perspective of deep feature learning
- Journal on Communications Vol. 47, Issue 5, Pages: 208-222(2026)
- 作者机构：
  
  1.南京邮电大学物联网学院，江苏南京 210003
  2.电子科技大学长三角研究院（湖州），浙江湖州 313000
  3.南京邮电大学通信与信息工程学院，江苏南京 210003
  4.南京航空航天大学电子信息工程学院，江苏南京 211106
- 作者简介：
- 基金信息：
  
  The National Natural Science Foundation of China(62501300);The Basic Science Research Higher Education Institutions in Jiangsu Province (Natural Science)(25KJB510023);The Open Research Project Fund of Zhejiang Provincial Engineering Research Center for Green Communications
- DOI：10.11959/j.issn.1000-436x.TXXB250612
  CLC： TN92
- Received：27 December 2025，
  
  Revised：2026-03-28，
  
  Accepted：30 March 2026，
  
  Published：25 May 2026
- 稿件说明：
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潘光良,张颖,赵海涛等.时频空频谱态势预测：深度特征学习视角[J].通信学报,2026,47(05):208-222.

Pan Guangliang,Zhang Ying,Zhao Haitao,et al.Temporal-frequency-spatial spectrum situation prediction: from the perspective of deep feature learning[J].Journal on Communications,2026,47(05):208-222.
潘光良,张颖,赵海涛等.时频空频谱态势预测：深度特征学习视角[J].通信学报,2026,47(05):208-222. DOI： 10.11959/j.issn.1000-436x.TXXB250612.

Pan Guangliang,Zhang Ying,Zhao Haitao,et al.Temporal-frequency-spatial spectrum situation prediction: from the perspective of deep feature learning[J].Journal on Communications,2026,47(05):208-222. DOI： 10.11959/j.issn.1000-436x.TXXB250612.

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Temporal-frequency-spatial spectrum situation prediction: from the perspective of deep feature learning

DOI：10.11959/j.issn.1000-436x.TXXB250612