Explanation-Guided Deep Reinforcement Learning for Trustworthy 6G RAN Slicing
Author:
Affiliation:
1. Centre Tecnológic de Telecomunicacions de Catalunya (CTTC),Barcelona,Spain
2. i2CAT Foundation,Barcelona,Spain
Publisher
IEEE
Link
http://xplorestaging.ieee.org/ielx7/10283478/10283479/10283684.pdf?arnumber=10283684
Reference13 articles.
1. Advanced Cloud-Based Network Management for 5G C-RAN;maule;Enabling 6G Mobile Networks,2021
2. Adam: A method for stochastic optimization;kingma;Proc Int Conf Learn Represent (ICLR),0
3. GAN-Powered Deep Distributional Reinforcement Learning for Resource Management in Network Slicing
4. A Collaborative Statistical Actor-Critic Learning Approach for 6G Network Slicing Control
5. Resource Reservation in Sliced Networks: An Explainable Artificial Intelligence (XAI) Approach
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1. XAI-driven Model Design for Resource Utilization Forecasting in Cloud-native 6G Networks;2024 IEEE International Mediterranean Conference on Communications and Networking (MeditCom);2024-07-08
2. Blockchain and Trustworthy Reputation for Federated Learning: Opportunities and Challenges;2024 IEEE International Mediterranean Conference on Communications and Networking (MeditCom);2024-07-08
3. Towards Accountable and Resilient AI-Assisted Networks: Case Studies and Future Challenges;2024 Joint European Conference on Networks and Communications & 6G Summit (EuCNC/6G Summit);2024-06-03
4. DRL-Based Latency-Aware Network Slicing in O-RAN with Time-Varying SLAs;2024 International Conference on Computing, Networking and Communications (ICNC);2024-02-19
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