Article
17 January 2019
Published
Elsevier BV
10.1016/j.neucom.2019.01.031
0925-2312
Engineering and Physical Sciences Research Council
Ozturk, M., Gogate, M., Onireti, O., Adeel, A., Hussain, A., & Imran, M. A. (2019). A novel deep learning driven, low-cost mobility prediction approach for 5G cellular networks: The case of the Control/Data Separation Architecture (CDSA). Neurocomputing, 358, 479-489. https://doi.org/10.1016/j.neucom.2019.01.031
Senior Research FellowSchool of Computing Engineering and the Built Environment
0131 455 4793
M.Gogate@napier.ac.uk
ProfessorSchool of Computing Engineering and the Built Environment
0131 455 2239
A.Hussain@napier.ac.uk
Mobility management; Deep learning; Predictive handover; 5G wireless mobile networks; Control/Data Separation Architecture
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© 2019 The Authors. Published by Elsevier B.V. This is an open access article under the CC BY license. (http://creativecommons.org/licenses/by/4.0/)