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Demo: vrAIn Proof-of-Concept - A Deep Learning Approach for Virtualized RAN Resource Control.

, , , , , and . MobiCom, page 59:1-59:3. ACM, (2019)

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Energy consumption anatomy of 802.11 devices and its implication on modeling and design., , , and . CoNEXT, page 169-180. ACM, (2012)Rigorous and practical proportional-fair allocation for multi-rate Wi-Fi., , , and . Ad Hoc Networks, (2016)Revisiting 802.11 Rate Adaptation from Energy Consumption's Perspective., , , , , and . MSWiM, page 27-34. ACM, (2016)Experimental Evaluation of Power Consumption in Virtualized Base Stations., , , , and . ICC, page 1-6. IEEE, (2021)AIRIC: Orchestration of Virtualized Radio Access Networks with Noisy Neighbours., , , and . CoRR, (2023)Demo: vrAIn Proof-of-Concept - A Deep Learning Approach for Virtualized RAN Resource Control., , , , , and . MobiCom, page 59:1-59:3. ACM, (2019)vrAIn: A Deep Learning Approach Tailoring Computing and Radio Resources in Virtualized RANs., , , , , and . MobiCom, page 30:1-30:16. ACM, (2019)Mobile Transport and Computing Platform for 5G Verticals: Resource Abstraction and Implementation., , , , , , , , , and 6 other author(s). NFV-SDN, page 1-6. IEEE, (2018)Towards 6G: Architectural Innovations and Challenges in the ORIGAMI Framework., , , , , , , , , and 1 other author(s). EuCNC/6G Summit, page 1139-1144. IEEE, (2024)TelecomRAG: Taming Telecom Standards with Retrieval Augmented Generation and LLMs., , , and . CoRR, (2024)