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On learning and exploiting time domain traffic patterns in cellular radio access networks

Author
Perez-Romero, J.; Sanchez, J.; Sallent, J.; Agusti, R.
Type of activity
Presentation of work at congresses
Name of edition
12th International Conference on Machine Learning and Data Mining in Pattern Recognition
Date of publication
2016
Presentation's date
2016-07
Book of congress proceedings
Machine learning and data mining in pattern recognition: 12th International Conference, MLDM 2016: New York, NY, USA, July 16-21, 2016: proceedings
First page
501
Last page
515
Publisher
Springer
DOI
https://doi.org/10.1007/978-3-319-41920-6_40 Open in new window
Repository
http://hdl.handle.net/2117/96855 Open in new window
URL
http://link.springer.com.recursos.biblioteca.upc.edu/chapter/10.1007%2F978-3-319-41920-6_40 Open in new window
Abstract
This paper presents a vision of how the different management procedures of future Fifth Generation (5G) wireless networks can be built upon the pillar of artificial intelligence concepts. After a general description of a cellular network and its management functionalities, highlighting the trends towards automatization, the paper focuses on the particular case of extracting knowledge about the time domain traffic pattern of the cells deployed by an operator. A general methodology for supervised ...
Citation
Perez-Romero, J., Sanchez, J., Sallent, J., Agusti, R. On learning and exploiting time domain traffic patterns in cellular radio access networks. A: International Conference on Machine Learning and Data Mining in Pattern Recognition. "Machine learning and data mining in pattern recognition: 12th International Conference, MLDM 2016: New York, NY, USA, July 16-21, 2016: proceedings". New York, NY: Springer, 2016, p. 501-515.
Keywords
5G mobile communication, 5G wireless networks, Artificial intelligence, Cellular radio, Cellular radio access networks, Energy consumption, Energy consumption reduction, Fifth generation wireless networks, Learning (artificial intelligence), Pattern classification, Radio access networks, Radio spectrum management, Spectrum planning, Telecommunication computing, Telecommunication network planning, Telecommunication traffic, Time domain traffic patterns, Traffic pattern supervised classification, Unlicensed spectrum
Group of research
CCABA - Advanced Broadband Communications Center
GRCM - Mobile Communication Reserach Group

Participants