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Conference Paper
QoS guaranteed Small Cell ON/OFF Techniques Based on Deep learning
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- Authors
- Taeyoon Park, Eunghyo Kim, Jaewan Park, Jongwon Han, Een-Kee Hong, Soojung Jung, Taegyun Noh
- Issue Date
- 2018-10
- Citation
- International Conference on Information and Communication Technology Convergence (ICTC) 2018, pp.805-808
- Publisher
- IEEE
- Language
- English
- Type
- Conference Paper
- Abstract
- Recently, there is increasing interest in how to secure network capacity to support the exponential growth of mobile data traffic. Ultra-Dense-Network (UDN) is expected to solve the problem of network capacity by installing a smaller cell with high densification. But UDN has energy efficiency problems. since many cells consume a lot of energy. To solve this problem, small cell on/off is expected to be a key technology. However, small cell on/off has also challenge in guaranteed QoS of traffics. When a small cell is off, traffic of the cell is offloaded to the neighbor cell and the QoS problem occurs. In this paper, we solve the trade-off problem between QoS and energy efficiency by turning on/off small cells in consideration of QoS by deep learning which is a representative method to solve nonlinear problems. We find the optimized weighing factors of multiple criteria for small cell on/off such as traffic load, traffic QoS, number of UEs and path loss based on learning approach.
- KSP Keywords
- Energy efficiency, Key technology, Learning approach, Mobile data traffic, Multiple criteria, Network capacity, Nonlinear problems, Path loss, Trade-off, Traffic Load, Ultra-dense