期刊
ICT EXPRESS
卷 7, 期 4, 页码 414-420出版社
ELSEVIER
DOI: 10.1016/j.icte.2021.01.003
关键词
Nearest neighbour search; Nearest neighbour classification; k-NN; 5G; Localisation; Beamforming; MIMO; Anomaly; SDN; Network Slicing; NFV; Energy efficiency
资金
- EPSRC, UK [EP/S016813/1, EP/N010523/1]
- Royal Academy of Engineering, UK [122040]
- EPSRC [EP/S016813/1, EP/N010523/1] Funding Source: UKRI
This paper provides an overview of Nearest Neighbour (NN) methods, discussing their theoretical background, algorithms, implementations, and key applications. It also examines the challenges related to 5G and beyond wireless networks that can be addressed using NN classification techniques.
In this paper, we present an overview of Nearest neighbour (NN) methods, which are frequently employed for solving classification problems using supervised learning. The article concisely introduces the theoretical background, algorithmic, and implementation aspects along with the key applications. From an application standpoint, this article explores the challenges related to the 5G and beyond wireless networks which can be solved using NN classification techniques. (C) 2021 The Korean Institute of Communications and Information Sciences (KICS). Publishing services by Elsevier B.V.
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