Deep Learning Applications in Mobile Networks




Abstract:
The expected deployment of 5G networks, growing percentages of mobile networks’ market penetration levels and increasing popularity of mobile applications induce new challenges and requirements for mobile network operators. One of the ways of tackling these new challenges is the deployment of advanced machine learning techniques in hopes of handling expected traffic volumes, performing real-time analytics and managing network resources. The paper presents the aspects of mobile networking in which deep learning methods can be implemented. After presenting the basic background and modern deep learning techniques and related technologies, paper presents an overview of the current advances made in these research areas. The paper also identifies the fields within the realm of mobile networking that show particular potential for new exploration.

CITATION:

IEEE format

D. Dašić, M. Vučetić, G. Hew A Kee, M. Stanković, “Deep Learning Applications in Mobile Networks,” in Sinteza 2019 - International Scientific Conference on Information Technology and Data Related Research, Belgrade, Singidunum University, Serbia, 2019, pp. 553-560. doi:10.15308/Sinteza-2019-553-560

APA format

Dašić, D., Vučetić, M., Hew A Kee, G., Stanković, M. (2019). Deep Learning Applications in Mobile Networks. Paper presented at Sinteza 2019 - International Scientific Conference on Information Technology and Data Related Research. doi:10.15308/Sinteza-2019-553-560

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