Machine-to-machine (M2M) devices with their expected exponential booming in the near future, will be one of the significant factors to influence all mobile networks. Inevitably, the expected huge number of M2M devices causes saturation problems, and leads to remarkable impacts on both M2M and human-to-human (H2H) traffics, services, and applications. The research free-space lack requires creating an appropriate model which describes the functionality of long-term evolution-advanced (LTE-A) and long-term evolution for machine (LTE-M), through mathematical frameworks to evaluate relevant performance metrics. In this study, we bridge this gap by proposing a continuous-time Markov chain (CTMC) model as a stochastic process tool to characterise the H2H/M2M coexistence based on analytical equations. Afterwards, the authors validate the proposed model through extensive Monte Carlo simulations. Eventually, it becomes approachable to characterise the impact of H2H/M2M coexistence in one LTE-NLTE-M radio resource allocation in dense areas and under disaster scenarios. The simulation results show that using a prioritise LTE-A system for both M2M and H2H traffics is convenient in dense area scenarios, while in emergency cases, it is more appropriate to use a non-prioritise traffic strategy to keep H2H and M2M traffics working properly at the same time.