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Machine-type communication (MTC) has the essential role for supporting in connecting the huge number of devices in the 5G systems, which is predicted to be officially released in 2020. Massive MTC (mMTC) is the key to solve a large number of devices as its low-cost energy consumption and wide area coverage. Enabling the massive number of machine-type devices( MTDs) to request services to the base stations (BSs) resulted in the randomness of the random access mechanism. The position of MTDs, BSs, and the events are modeled in Spatial Poisson Point Process (SPPP), as the arrival of the events is based on the Poisson Arrival Process. Stochastic geometry is used to capture the characterization of the mMTC over cellular and events with enhanced access-barring class and random access through the PPP. Then, we proposed the event-based traffic model by combining the spatial point process and the poisson arrival process as the event model (Spatial Point Event) with the parameters from the Markov chain. Hence, we calculate the approximation of the expected traffic rate. The validation of the traffic model is using simulation and compared to the previous traffic model.
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