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Toward native explainable and robust AI in 6G networks: Current state, challenges and road ahead

  • Published:2022-09 Issue: Volume:193 Page:47-52
  • ISSN:0140-3664
  • Container-title:Computer Communications
  • language:en
  • Short-container-title:Computer Communications

Author:

Fiandrino ClaudioORCID,Attanasio Giulia,Fiore Marco,Widmer Joerg

Publisher

Elsevier BV

Subject

Computer Networks and Communications

Reference31 articles.

1. Survey on 6G frontiers: Trends, applications, requirements, technologies and future research;Alwis;IEEE Open J. Commun. Soc.,2021

2. 6G and beyond: The future of wireless communications systems;Akyildiz;IEEE Access,2020

3. Artificial intelligence for 6G networks: Technology advancement and standardization;SHEHZAD;IEEE Veh. Technol. Mag.,2022

4. 6G White Paper on Edge Intelligence;Peltonen,2020

5. Trustworthy AI;Wing;Commun. ACM,2021

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2. Path signature-based XAI-enabled network time series classification;Science China Information Sciences;2024-06-27

3. An In-Depth Analysis of Advanced Time Series Forecasting Models for the Open RAN;IEEE INFOCOM 2024 - IEEE Conference on Computer Communications Workshops (INFOCOM WKSHPS);2024-05-20

4. AIChronoLens: Advancing Explainability for Time Series AI Forecasting in Mobile Networks;IEEE INFOCOM 2024 - IEEE Conference on Computer Communications;2024-05-20

5. ATHENA: Machine Learning and Reasoning for Radio Resources Scheduling in vRAN Systems;IEEE Journal on Selected Areas in Communications;2024-02
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