Toward Bridging the FL Performance-Explainability Tradeoff: A Trustworthy 6G RAN Slicing Use-Case
Author:
Affiliation:
1. Iquadrat Informatica and Universitat Politècnica de Catalunya (UPC), Barcelona, Spain
2. i2CAT Foundation, Barcelona, Spain
3. University of Patras and ISI/ATHENA, Patras, Greece
Funder
6G-BRICKS
ADROIT6G
MINECO, Spain
EU NextGenerationEU/PRTR
Publisher
Institute of Electrical and Electronics Engineers (IEEE)
Link
http://xplorestaging.ieee.org/ielx7/25/10606142/10430406.pdf?arnumber=10430406
Reference25 articles.
1. Zero-touch network and service management (ZSM); reference architecture,2019
2. Statistical Federated Learning for Beyond 5G SLA-Constrained RAN Slicing
3. Principles and Practice of Explainable Machine Learning
4. Applications of Explainable AI for 6G: Technical aspects, use cases, and research challenges;Wang,2021
5. AI-Driven Zero Touch Network and Service Management in 5G and Beyond: Challenges and Research Directions
Cited by 2 articles. 订阅此论文施引文献 订阅此论文施引文献，注册后可以免费订阅5篇论文的施引文献，订阅后可以查看论文全部施引文献
1. Trustworthy Federated Learning: A Comprehensive Review, Architecture, Key Challenges, and Future Research Prospects;IEEE Open Journal of the Communications Society;2024
2. 6GENABLERS: A Holistic Approach to Establish Pervasive Trust in 6G Networks;2023 IEEE 28th International Workshop on Computer Aided Modeling and Design of Communication Links and Networks (CAMAD);2023-11-06
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