4.5 Article

Nearest neighbour methods and their applications in design of 5G & beyond wireless networks

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

  1. EPSRC, UK [EP/S016813/1, EP/N010523/1]
  2. Royal Academy of Engineering, UK [122040]
  3. EPSRC [EP/S016813/1, EP/N010523/1] Funding Source: UKRI

向作者/读者索取更多资源

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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