Optimization of trusted wireless sensing models based on deep reinforcement learning for ISAC systems
Abstract This paper investigates using deep reinforcement learning (DRL) methods for optimizing trustworthy federated learning models, with a focus on integrated sensing and communication in practical wireless sensing scenarios. Challenges include computational disparities among edge sensing nodes,...
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| Main Authors: | , , , |
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| Format: | Article |
| Language: | English |
| Published: |
Wiley
2024-12-01
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| Series: | Electronics Letters |
| Subjects: | |
| Online Access: | https://doi.org/10.1049/ell2.70080 |
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