Efficient Pilot Allocation for URLLC Traffic in 5G Industrial IoT Networks In this paper we address the problem of resource allocation for alarm traffic in industrial Internet of Things networks using massive MIMO. We formulate the general problem of how to allocate pilot signals to alarm traffic such that delivery is guaranteed, while also minimising the number of pilots reserved for alarms, thus maximising the channel resources available for other traffic, such as industrial control traffic. We present an algorithm that fulfils these requirements, and evaluate its performance both analytically and through a simulation study. For realistic alarm traffic characteristics, on average our algorithm can deliver alarms within two time slots (of duration equal to the 5G transmission time interval) using fewer than 1.5 pilots per slot, and even in the worst case it uses around 3.5 pilots in any given slot, with delivery guaranteed in an average of approximately four slots.

Characterizing Delay and Control Traffic of the Cellular MME with IoT Support Massive Internetofthings (MIoT) represents one of the main use cases of 5G, as well as one of the most challenging ones. Accordingly, MIoT traffic is given special treatment in the core network, with the Mobility Management Entity (MME) serving both control and data traffic. In this context, it is critical to properly dimension the MME and to adapt its capability to traffic fluctuations. To this end, we present a compact, closed form linking the number of IoT sources with the rate at which bearers are requested from the MME, and such a rate delay incurred by MME operations. Our model represents a valuable tool to make effective, realtime scaling decisions in virtualized cellular core networks.