標題: Affinity Propagation Clustering for Interference Management in Aerial Small Cells
作者: Cheng, Shao-Hung
Chao, Yung-Sheng
Wang, Li-Chun
Tsai, Ang-Hsun
電機工程學系
Department of Electrical and Computer Engineering
關鍵字: Drone small cell;Unsupervised learning;Interference mitigation;Energy saving
公開日期: 1-Jan-2019
摘要: The drone small cell (DSC) network has become a key technology for air-to-ground wireless communications in a variety of temporary or emergency situations. Based on mobile users, frequently changing DSC topologies have important challenges such as severe co-channel interference and limited battery capacity. However, temporarily dispatched drones cannot obtain labeled and historical data in advance, while they only obtain real-time operational data. The observed data can be analyzed by unsupervised learning methods to find useful information for resource management. In this paper, an interference-aware power control (IPC) framework is designed using affinity propagation clustering (APC). The APC method is one of the unsupervised learning methods. The numerical results show that our proposed IPC framework using the APC method can reduce system interference and significantly improve the energy efficiency of DSC networks.
URI: http://hdl.handle.net/11536/155509
ISBN: 978-1-7281-1204-6
期刊: 2019 IEEE VTS ASIA PACIFIC WIRELESS COMMUNICATIONS SYMPOSIUM (APWCS 2019)
起始頁: 0
結束頁: 0
Appears in Collections:Conferences Paper