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i2CAT Foundation

Industry researcheurope · es
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Research library15linked papers
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Selected work

Representative Papers

XAI-Guided Conservative Decentralized Execution for Offline Multi-Agent Network Slicing

Aug 14, 2026

This study addresses the high interaction costs, safety risks, and deployment challenges associated with online multi-agent reinforcement learning (MARL) in network slice resource allocation. To overcome these limitations, this work proposes X-CODE, a framework integrating explainable AI with offline MARL. By leveraging explainability-aware reward shaping, X-CODE optimizes decentralized execution policies, enabling safe and efficient management without online interactions or inter-agent communication. Experimental results demonstrate that the proposed framework achieves zero resource conflicts during testing and reduces effective inference latency by 88%. Furthermore, it significantly decreases signaling overhead and slicing latency. These findings establish X-CODE as a secure, low-latency intelligent solution for dynamic network slicing environments, effectively bridging the gap between theoretical MARL models and practical, safety-critical telecommunications deployments.

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Enabling Beyond-Visual-Line-of-Sight Drones Operation over Open RAN 5G Networks with Slicing

Aug 10, 2026

This work addresses the challenge of insufficient 5G link reliability that hinders safe beyond visual line-of-sight (BVLoS) unmanned aerial vehicle (UAV) operations. To overcome this limitation, the authors develop a BVLoS UAV operating system based on an open-source O-RAN platform, integrating end-to-end network slicing into the open 5G architecture for the first time to ensure control-link reliability. The proposed system effectively mitigates trajectory deviations caused by link congestion and consistently maintains end-to-end latency within the 3GPP standard limits. By enabling highly reliable and low-latency remote UAV control, this approach significantly enhances flight safety and operational performance in BVLoS scenarios.

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Recent publications

Latest Papers

XAI-Guided Conservative Decentralized Execution for Offline Multi-Agent Network Slicing

Aug 14, 2026

This study addresses the high interaction costs, safety risks, and deployment challenges associated with online multi-agent reinforcement learning (MARL) in network slice resource allocation. To overcome these limitations, this work proposes X-CODE, a framework integrating explainable AI with offline MARL. By leveraging explainability-aware reward shaping, X-CODE optimizes decentralized execution policies, enabling safe and efficient management without online interactions or inter-agent communication. Experimental results demonstrate that the proposed framework achieves zero resource conflicts during testing and reduces effective inference latency by 88%. Furthermore, it significantly decreases signaling overhead and slicing latency. These findings establish X-CODE as a secure, low-latency intelligent solution for dynamic network slicing environments, effectively bridging the gap between theoretical MARL models and practical, safety-critical telecommunications deployments.

0 citationsRead paper

Enabling Beyond-Visual-Line-of-Sight Drones Operation over Open RAN 5G Networks with Slicing

Aug 10, 2026

This work addresses the challenge of insufficient 5G link reliability that hinders safe beyond visual line-of-sight (BVLoS) unmanned aerial vehicle (UAV) operations. To overcome this limitation, the authors develop a BVLoS UAV operating system based on an open-source O-RAN platform, integrating end-to-end network slicing into the open 5G architecture for the first time to ensure control-link reliability. The proposed system effectively mitigates trajectory deviations caused by link congestion and consistently maintains end-to-end latency within the 3GPP standard limits. By enabling highly reliable and low-latency remote UAV control, this approach significantly enhances flight safety and operational performance in BVLoS scenarios.

0 citationsRead paper