Encyclopedia of Wireless Networks

Living Edition
| Editors: Xuemin (Sherman) Shen, Xiaodong Lin, Kuan Zhang

Machine Learning Paradigms in Wireless Network Association

  • Jingjing Wang
  • Chunxiao JiangEmail author
Living reference work entry
DOI: https://doi.org/10.1007/978-3-319-32903-1_68-1



Investigating machine learning aided cooperative resource allocation and network association mechanisms for wireless networks.


Wireless network association has received substantial attention both in the academic and industrial communities. One of their driving forces is that of efficiently providing unprecedented data rates for supporting radical new applications (Jiang et al., 2017). Specifically, a range of network association schemes are expected to learn the diverse and colorful characteristics of both the users’ ambience and the human behaviors, in order to autonomously determine the optimal system configurations for the sake of conserving energy as well as maximizing network capacity. Moreover, smart mobile terminals have to rely on sophisticated learning and decision-making. Machine learning, as one of the most powerful artificial intelligence tools, constitutes a...

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Copyright information

© Springer International Publishing AG, part of Springer Nature 2018

Authors and Affiliations

  1. 1.Department of Electronic EngineeringTsinghua UniversityBeijingPeople’s Republic of China
  2. 2.Department of Electronic Engineering, Tsinghua Space CenterTsinghua UniversityBeijingPeople’s Republic of China

Section editors and affiliations

  • Hsiao-hwa Chen

There are no affiliations available