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Improving User Environment Detection Using Context-Aware Multi-Task Deep Learning in Mobile Networks.

, , , , and . IEEE Trans. Cogn. Commun. Netw., 8 (4): 1665-1676 (2022)

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Multi-task Deep Learning based Environment and Mobility Detection for User Behavior Modeling., , , and . WiOpt, page 1-7. IEEE, (2019)Mobile User Environment Detection using Deep Learning based Multi-Output Classification., , , , and . WMNC, page 16-23. IEEE, (2019)MPE-IFEC: An enhanced burst error protection for DVB-SH systems., , , , and . Bell Labs Tech. J., 14 (1): 25-40 (2009)Optimization of Unicast Services Transmission for Broadcast Channels in Practical Situations., , and . Bell Labs Tech. J., 17 (1): 5-23 (2012)Deep Learning Based Speed Profiling for Mobile Users in 5G Cellular Networks., , , and . GLOBECOM, page 1-7. IEEE, (2019)Resilience analysis and quantification method for 5G-Radio Access Networks., , , and . NoF, page 1-9. IEEE, (2022)5G Edge Resource Federation: Dynamic and Cross-domain Network Slice Deployment., , , , , , , and . NetSoft, page 338-340. IEEE, (2018)Constellation shaping for broadcast channels in practical situations., , , and . EUSIPCO, page 96-100. IEEE, (2011)Performance Evaluation of Channel Change for DVB-SH Streaming Services., , , , and . ICC, page 1-6. IEEE, (2010)Improving User Environment Detection Using Context-Aware Multi-Task Deep Learning in Mobile Networks., , , , and . IEEE Trans. Cogn. Commun. Netw., 8 (4): 1665-1676 (2022)