Multi-Task Learning Resource Allocation in Federated Integrated Sensing and Communication Networks-Reference-Cited by-同舟云学术

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Multi-Task Learning Resource Allocation in Federated Integrated Sensing and Communication Networks

Published:2024-09 Issue:9 Volume:23 Page:11612-11623
ISSN:1536-1276
Container-title:IEEE Transactions on Wireless Communications
language:
Short-container-title:IEEE Trans. Wireless Commun.

Author:

Liu Xiangnan¹^ORCID,Zhang Haijun¹^ORCID,Ren Chao¹^ORCID,Li Haojin²^ORCID,Sun Chen²^ORCID,Leung Victor C. M.³^ORCID

Affiliation:

1. Beijing Engineering and Technology Research Center for Convergence Networks and Ubiquitous Services, University of Science and Technology Beijing, Beijing, China

2. Sony China Research Laboratory, Beijing, China

3. College of Computer Science and Software Engineering, Shenzhen University, Shenzhen, China

Funder

Beijing Natural Science Foundation

National Natural Science Foundation of China

China University Industry-University-Research Collaborative Innovation Fund

Publisher

Institute of Electrical and Electronics Engineers (IEEE)

Link

http://xplorestaging.ieee.org/ielx7/7693/10678756/10506079.pdf?arnumber=10506079

Reference37 articles.

1. The Potential of Digital Twins

2. Reliable Distributed Computing for Metaverse: A Hierarchical Game-Theoretic Approach

3. Integrated Sensing and Communications: Toward Dual-Functional Wireless Networks for 6G and Beyond

4. Joint MIMO Precoding and Computation Resource Allocation for Dual-Function Radar and Communication Systems With Mobile Edge Computing

5. Integrating Sensing, Computing, and Communication in 6G Wireless Networks: Design and Optimization

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