机器人 / 具身智能 - arXivDaily 专题

2509.06968 2025-09-10 eess.SP cs.AI 57%

Deep Learning-based Techniques for Integrated Sensing and Communication Systems: State-of-the-Art, Challenges, and Opportunities

Murat Temiz, Yongwei Zhang, Yanwei Fu, Chi Zhang, Chenfeng Meng, Orhan Kaplan, Christos Masouros

机构 * Department of Electronic and Electrical Engineering, Faculty of Engineering Sciences, University College London（伦敦大学学院电子与电气工程系）； Department of Electrical and Electronics Engineering, Faculty of Engineering, Middle East Technical University（中东技术大学电气与电子工程系）； School of Transportation and Civil Engineering, Nantong University（南通大学交通与土木工程学院）； Department of Electrical and Electronics Engineering, Faculty of Technology, Gazi University（加齐大学电气与电子工程系）

专题命中其他机器人：robotics(abstract)；分类 cs.AI

Comments 35 Pages, 13 Figures, 11 Tables, corrected version of the published journal article in IEEE Open Journal of the Communications Society

Journal ref in IEEE Open Journal of the Communications Society, vol. 6, pp. 5940-5968, 2025

1. 其他机器人 1 篇

Deep Learning-based Techniques for Integrated Sensing and Communication Systems: State-of-the-Art, Challenges, and Opportunities