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A Model to Analyze the Energy Savings of Base Station Sleep Mode in LTE HetNets.

, , , and . GreenCom/iThings/CPScom, page 1375-1380. IEEE, (2013)

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Distributed Deep Reinforcement Learning for Functional Split Control in Energy Harvesting Virtualized Small Cells., , , and . CoRR, (2020)Multi-Task Learning at the Mobile Edge: An Effective Way to Combine Traffic Classification and Prediction., , , and . IEEE Trans. Veh. Technol., 69 (9): 10362-10374 (2020)Traffic Anomaly Detection Using Deep Semi-Supervised Learning at the Mobile Edge., , and . IEEE Trans. Veh. Technol., 71 (8): 8919-8932 (2022)A Neural Network based cognitive engine for IEEE 802.11 WLAN Access Point selection., , and . CCNC, page 864-868. IEEE, (2012)A supervised learning approach to cognitive access point selection., , , and . GLOBECOM Workshops, page 1100-1105. IEEE, (2011)A Research Framework for Interaction Computing., and . OPAALS, volume 67 of Lecture Notes of the Institute for Computer Sciences, Social Informatics and Telecommunications Engineering, page 224-244. Springer, (2010)BIONETS Economics and Business Simulation: An Alternative Approach to Quantifying the Added Value for Distributed Mobile Communications and Exchanges., and . BIONETICS, volume 39 of Lecture Notes of the Institute for Computer Sciences, Social Informatics and Telecommunications Engineering, page 77-87. Springer, (2009)An overlay and distributed approach to node mobility in multi-access wireless networks., , and . Wireless Networks, 20 (6): 1275-1293 (2014)Federated Spatial Reuse Optimization in Next-Generation Decentralized IEEE 802.11 WLANs., , , , , , , , , and 3 other author(s). CoRR, (2022)Anticipatory Allocation of Communication and Computational Resources at the Edge Using Spatio-Temporal Dynamics of Mobile Users., , , and . IEEE Trans. Netw. Serv. Manag., 18 (4): 4548-4562 (2021)