RACH Traffic Prediction in Massive Machine Type Communications
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 in