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Mitigating Unnecessary Handovers in Ultra-Dense Networks through Machine Learning-based Mobility Prediction.

, , , , and . VTC2023-Spring, page 1-7. IEEE, (2023)

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Deep Learning-Based Signal-to-Noise Ratio Prediction for Realistic Wireless Communication., , , and . VTC Spring, page 1-5. IEEE, (2022)The Effect of Variable Factors on the Handover Performance for Ultra Dense Network., , , , and . CoRR, (2023)Investigating the Impact of Variables on Handover Performance in 5G Ultra-Dense Networks., , , , and . EuCNC/6G Summit, page 567-572. IEEE, (2023)Mitigating Unnecessary Handovers in Ultra-Dense Networks through Machine Learning-based Mobility Prediction., , , , and . VTC2023-Spring, page 1-7. IEEE, (2023)True 3D Holography: A Communication Service of Tomorrow and Its Requirements for a New Converged Cloud and Network Architecture on the Path to 6G., , , , , , , , , and 10 other author(s). 6GNet, page 1-8. IEEE, (2023)Performance Evaluation over DL-Based Channel Prediction Algorithm on Realistic CSI., , , and . VTC Fall, page 1-5. IEEE, (2022)Trust-Awareness to Secure Swarm Intelligence from Data Injection Attack., , , and . ICC, page 1406-1412. IEEE, (2023)Evaluating the Impact of Numerology and Retransmission on 5G NR V2X Communication at A System-Level Simulation., , , , and . CSCN, page 59-65. IEEE, (2023)