Dynamic uplink resource dimensioning for massive MTC in 5G networks based on SCMA

In this paper, we address the uplink radio resource allocation problem in a 5G massive Machine Type Communication (mMTC) scenario, characterized by a large number of battery constrained MTC devices generating small-sized bursty traffic. The current cellular network is unsuitable for this scenario, due to the limited uplink resources allocated to the Physical Random Access Channel (PRACH) and to the Physical Uplink Shared Channel (PUSCH). For this reason, we adopt in the PUSCH the Sparse Code Multiple Access (SCMA) technique, which is suitable for the multiplexing of a huge amount of small-sized data, and propose a dynamic load-aware PRACH and PUSCH resource allocation. In addition, in order to make our solution viable, we propose a predictive estimate of expected traffic based only on information available at the gNodeB. By simulations, we compare our dynamic control with static resource allocations. The results show that the proposed control significantly improves the number of succeeded communications, while guaranteeing lower energy consumption.