Nearest neighbor Methods and their Applications in Design of 5G & Beyond Wireless Networks
This work is incremental, offering a review of existing methods for researchers and practitioners in wireless networking.
The paper provides an overview of nearest neighbor methods for classification in supervised learning and explores their applications in addressing challenges for 5G and beyond wireless networks, without presenting new experimental results or specific numerical outcomes.
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.