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Found 5 papers, 0 papers with code
AIaaS for ORAN-based 6G Networks: Multi-time Scale Slice Resource Management with DRL
The proposed algorithms analyze the maximum utilization of resources from slice performance to take decisions at the inter-slice level.
Intelligent QoS aware slice resource allocation with user association parameterization for beyond 5G ORAN based architecture using DRL
This can be achieved with slicing and programmable network architectures such as the open radio access network (ORAN).
Towards Bridging the FL Performance-Explainability Trade-Off: A Trustworthy 6G RAN Slicing Use-Case
In the context of sixth-generation (6G) networks, where diverse network slices coexist, the adoption of AI-driven zero-touch management and orchestration (MANO) becomes crucial.
Decision Making
Explainable Artificial Intelligence (XAI)
+3
Explanation-Guided Fair Federated Learning for Transparent 6G RAN Slicing
Future zero-touch artificial intelligence (AI)-driven 6G network automation requires building trust in the AI black boxes via explainable artificial intelligence (XAI), where it is expected that AI faithfulness would be a quantifiable service-level agreement (SLA) metric along with telecommunications key performance indicators (KPIs).
Explainable artificial intelligence
Explainable Artificial Intelligence (XAI)
+2
TEFL: Turbo Explainable Federated Learning for 6G Trustworthy Zero-Touch Network Slicing
Sixth-generation (6G) networks anticipate intelligently supporting a massive number of coexisting and heterogeneous slices associated with various vertical use cases.
Explainable Artificial Intelligence (XAI)
Federated Learning
+1
