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Radar in-band interference effects on macrocell LTE uplink deployments in the U.S. 3.5 GHz band.

, , , , and . ICNC, page 248-254. IEEE Computer Society, (2015)

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Implementing an Optimal Rate Allocation Tuned to the User Quality of Experience., , and . CoRR, (2014)Radar in-band interference effects on macrocell LTE uplink deployments in the U.S. 3.5 GHz band., , , , and . ICNC, page 248-254. IEEE Computer Society, (2015)A neural network approach to category validation of Android applications., , , , and . ICNC, page 740-744. IEEE Computer Society, (2013)Application-Aware Resource Allocation based on Channel Information for Cellular Networks., , , and . WCNC, page 1-6. IEEE, (2019)Radar interference into LTE base stations in the 3.5 GHz band., , , and . Phys. Commun., (2016)Implementing an optimal rate allocation tuned to the user quality of experience., , , , and . ICNC, page 292-297. IEEE Computer Society, (2015)Radar In-Band and Out-of-Band Interference into LTE Macro and Small Cell Uplinks in the 3.5 GHz Band., , , , and . CoRR, (2014)Application-Aware Resource Allocation of Hybrid Traffic in Cellular Networks., , and . IEEE Trans. Cogn. Commun. Netw., 3 (2): 226-241 (2017)Fine-grained end-to-end network model via vector quantization and hidden Markov processes., , , and . ICC, page 2354-2359. IEEE, (2013)A hidden Markov model detection of malicious Android applications at runtime., , , , and . WOCC, page 1-6. IEEE, (2014)