Author(s)

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

Department of Electrical and Computer Engineering, California State Polytechnic University, Pomona, USA.

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.

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

Omar, T. , Ketseoglou, T. , Naffaa, O. , Marzvanyan, A. and Carr, C. (2021) A Precoding Real-Time Buffer Based Self-Healing Solution for 5G Networks. Journal of Computer and Communications, 9, 1-23. doi: 10.4236/jcc.2021.96001.