Applications of explainable AI for 6G: Technical aspects, use cases, and research challenges
When 5G began its commercialisation journey around 2020, the discussion on the vision of
6G also surfaced. Researchers expect 6G to have higher bandwidth, coverage, reliability …
6G also surfaced. Researchers expect 6G to have higher bandwidth, coverage, reliability …
Federated learning-empowered mobile network management for 5G and beyond networks: From access to core
The fifth generation (5G) and beyond wireless networks are envisioned to provide an
integrated communication and computing platform that will enable multipurpose and …
integrated communication and computing platform that will enable multipurpose and …
A survey on explainable ai for 6g o-ran: Architecture, use cases, challenges and research directions
The recent O-RAN specifications promote the evolution of RAN architecture by function
disaggregation, adoption of open interfaces, and instantiation of a hierarchical closed-loop …
disaggregation, adoption of open interfaces, and instantiation of a hierarchical closed-loop …
Improving performance, reliability, and feasibility in multimodal multitask traffic classification with XAI
The promise of Deep Learning (DL) in solving hard problems such as network Traffic
Classification (TC) is being held back by the severe lack of transparency and explainability …
Classification (TC) is being held back by the severe lack of transparency and explainability …
Explainable AI in 6G O-RAN: A Tutorial and Survey on Architecture, Use Cases, Challenges, and Future Research
The recent o-ran specifications promote the evolution of ranran architecture by function
disaggregation, adoption of open interfaces, and instantiation of a hierarchical closed-loop …
disaggregation, adoption of open interfaces, and instantiation of a hierarchical closed-loop …
A Survey on Explainable Artificial Intelligence for Internet Traffic Classification and Prediction, and Intrusion Detection
With the increasing complexity and scale of modern networks, the demand for transparent
and interpretable Artificial Intelligence (AI) models has surged. This survey comprehensively …
and interpretable Artificial Intelligence (AI) models has surged. This survey comprehensively …
Toward native explainable and robust AI in 6G networks: Current state, challenges and road ahead
Abstract 6G networks are expected to face the daunting task of providing support to a set of
extremely diverse services, each more demanding than those of previous generation …
extremely diverse services, each more demanding than those of previous generation …
Interpreting AI for networking: Where we are and where we are going
In recent years, artificial intelligence (AI) techniques have been increasingly adopted to
tackle networking problems. Although AI algorithms can deliver high-quality solutions, most …
tackle networking problems. Although AI algorithms can deliver high-quality solutions, most …
Towards explainable artificial intelligence in optical networks: the use case of lightpath QoT estimation
Artificial intelligence (AI) and machine learning (ML) continue to demonstrate substantial
capabilities in solving a wide range of optical-network-related tasks such as fault …
capabilities in solving a wide range of optical-network-related tasks such as fault …
Survey on Machine Learning-Enabled Network Slicing: Covering the Entire Life Cycle
Network slicing (NS) is becoming an essential element of service management and
orchestration in communication networks, starting from mobile cellular networks and …
orchestration in communication networks, starting from mobile cellular networks and …