On capturing spatial diversity of joint M2M/H2H dynamic uplink transmissions in 3GPP lte cellular system

While queuing theory has indeed been instrumental to various communication problems for over half a century, the unprecedented proliferation of wireless technology in the last decades brought along novel research challenges, where user location has become a crucial factor in determining the respective system performance. This recent shift turned important to characterize large cellular macrocells, as well as the emerging effects of network densification. However, the latter trend also called for increased attention to the actual user loading and uplink (UL) traffic dynamics, accentuating again the necessity of queuing analysis. Hence, by combining queuing theory and stochastic geometry in a feasible manner, we may quantify the dependence of system-level performance on the traffic loading. As performance of both session-and file-based UL transmissions has already been investigated recently in the context of heterogeneous networks, this paper explores a possibility of combining these two applications to provide a first-order evaluation of joint machine-to-machine (M2M) and human-to-human (H2H) transmissions in 3GPP LTE cellular systems. Employing a two-dimensional Markov chain for the aggregated process, we provide an approximation for the state transitions and, finally, arrive at a system-level approximation for the steady-state mode, which allows estimating a variety of system parameters averaged across space and time. © Springer International Publishing Switzerland 2015.