RACH Traffic Prediction in Massive Machine Type Communications

arXiv:2405.05235v1 Announce Type: cross
Abstract: Traffic pattern prediction has emerged as a promising approach for efficiently managing and mitigating the impacts of event-driven bursty traffic in massive machine-type communication (mMTC) networks. However, achieving accurate predictions of bursty traffic remains a non-trivial task due to the inherent randomness of events, and these challenges intensify within live network environments. Consequently, there is a compelling imperative to design a lightweight and agile framework capable of assimilating continuously collected data from the network and …

abstract arxiv challenges communication communications cs.lg cs.sy eess.sy event events however impacts machine massive networks pattern prediction predictions randomness traffic type