Modeling and Performance Analysis of 5G RRC Protocol with Machine-Type Communications

5G New Radio (NR) introduces a new Radio Resource Control (RRC) state, i.e., RRC INACTIVE, for providing the efficient service for massive Machine Type Communications (mMTC). To release the full potential of the new RRC state, it is of great importance to properly model the new RRC state transition process and reveal the effect of system parameters on the network performance. To address the above issue, this paper proposes a novel 5G RRC analytical model based on discrete-time vacation queuing theory, where the time period of the device in RRC INACTIVE state is regarded as the vacation period of the server in the queueing system. By leveraging this novel model, key performance metrics, such as the random access rate and the RRC resource utilization ratio, are explicitly characterized and obtained as functions of system parameters, including packet arrival rate, service rate and inactivity timer. The analysis reveals that to reduce the random access rate, the system should increase the inactivity timer, packet arrival rate or decrease the service rate. On the other hand, to improve the RRC resource utilization ratio, the inactivity timer should be cut down especially when the arrival rate is small or the service rate is large. The analysis is verified by simulations and sheds important light on practical 5G network design for supporting mMTC.