LTE-A random access channel capacity evaluation for M2M communications

The densification of the urban population and the rise of smart cities applications foster the need for capillary networks collecting data from sensors monitoring the cities. Among the multiple networking technologies considered for this task, cellular networks, such as LTE-A, bring an ubiquitous coverage of most cities. It is therefore necessary to understand how to adapt LTE-A, and what should be the future 5G architecture, in order to provide efficient connectivity to Machine-to-Machine (M2M) devices alongside the main target of mobile networks, Human-to-Human devices. Indeed, cellular random access procedures are known to suffer from congestion in presence of a large number of devices, while smart cities scenarios expect huge density of M2M devices. Several solutions have been investigated for the enhancement of the current LTE-A access management strategy. In this paper, we contribute to the modeling and computation of the capacity of the LTE-A Random Access Channel (RACH) in terms of simultaneous successful access. In particular, we investigate the hypothesis of piggybacking the payload of Machine Type Communications from M2M devices within the RACH, and show that M2M densities considered realistic for smart cities applications are difficult to sustain by the current LTE-A architecture.