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- W2911813913 abstract "In this paper, we consider the 3 dimensional (3D) small cell basestations (SBSs) placement problem for hetergeneous users with incomplete QoS requirements. We propose a learning embedded hypergraph construction algorithm to jointly predict the heterogeneous users’ QoS requirements and deploy the SBSs to cover as many users as possible. Specifically, we predict and leverage users’ QoS requirements with a real-world dataset, China Family Panel Studies (CFPS), and design a human behavior based learning framework (HBLF) to anticipate users’ QoS requirements with users’ profiles. Then, based on HBLF, we propose a hypergraph construction algorithm to deploy the SBSs. Simulation results indicate that the learning embedded hypergraph construction can use the least number of SBSs to cover all users compared with a number of algorithms, such as K-means. The HBLF can achieve a higher coverage ratio of users compared with other learning algorithms, such as decision tree. Simulation results also corroborate that the more accurately we can predict the users’ QoS requirements, the more users we can satisfy their QoS requirements." @default.
- W2911813913 created "2019-02-21" @default.
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- W2911813913 date "2018-11-01" @default.
- W2911813913 modified "2023-10-16" @default.
- W2911813913 title "Human Behavior Based Learning Framework for Small Cell Placement in 5G Networks Using Hypergraph Construction" @default.
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- W2911813913 doi "https://doi.org/10.1109/apcc.2018.8633477" @default.
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