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Nearest neighbor Methods and their Applications in Design of 5G & Beyond Wireless Networks

arXiv 2107.07869 ↗First posted 16 Jul 2021cs.NI cs.LG eess.SPcited by 0

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Abstract (arXiv)

In this paper, we present an overview of Nearest neighbor (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.

Key facts. No citing papers in the map yet (data through 7 Oct 2026). Builds on 3 of its 27 references that are in the map. First posted on arXiv 16 Jul 2021.

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References · 3

  1. 2020Reconfigurable Intelligent Surfaces: Principles and Opportunitiescited by 34
  2. 20185G Wireless Network Slicing for eMBB, URLLC, and mMTC: A Communication-Theoretic Viewcited by 17
  3. 2017A Machine Learning Framework for Resource Allocation Assisted by Cloud Computingcited by 3

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