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Jang, J., Chung, M., Hwang, S.C., Lim, Y., Yoon, H., Oh, T., Min, B., Lee, Y., Kim, K.S., Chae, C. and Kim, D.K. (2016) Smart Small Cell with Hybrid Beamforming for 5g: Theoretical Feasibility and Prototype Results. IEEE Wireless Communications, 23, 124-131.
https://doi.org/10.1109/MWC.2016.1500387WC

has been cited by the following article:

• TITLE: A Precoding Real-Time Buffer Based Self-Healing Solution for 5G Networks

  AUTHORS: Tamer Omar, Thomas Ketseoglou, Omar Naffaa, Asatur Marzvanyan, Connor Carr

  KEYWORDS: Self-Healing, MIMO-Beamforming, Millimeter Wavelength, Base Station, Latency

  JOURNAL NAME: Journal of Computer and Communications, Vol.9 No.6, June 8, 2021

  ABSTRACT: In order to meet key requirements imposed by transitioning to a 5G network, new network management techniques must be employed in order to increase network reliability and efficiency. Most notably, it is important that a Self-Organizing Network (SON) is able to recover autonomously from network failure or congestion through Self-Healing procedures (i.e. autonomous detection, diagnosis, and correction). This paper aims to develop a self-healing algorithm that can effectively “heal” a 5G network by testing a proposed self-healing algorithm within a network simulator that adheres to current 5G standards. The simulator developed in this paper aims to model a network of small cells that can inherit one of multiple states (healthy, congested, and failing) to validate the effectiveness of a programmed self-healing algorithm in recovering a simulated network. Results show that the application of a self-healing in a network is able to resolve issues related to Quality of Service (QoS) and reduced network data rates in portions of a network that are in a partially congested or failing state.