Joint Congestion Control and Resource Allocation for Massive MTC in 5G Networks Based on SCMA

Abstract

The massive Machine Type Communications (mMTC) usage scenario, also known as massive Internet of Things (mIoT), involves a large number of MTC devices having high requirements on increased battery lifetime, which autonomously transfer small amounts of data with relaxed delay requirements, without human intervention. 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). With this in mind, in this paper we propose a new framework, customized for massive MTC services, that includes a joint control of the dynamic resource allocation between the PRACH and the PUSCH, and a new random access procedure based on an adaptive Access Class Barring (ACB) scheme that appropriately spreads random access re-attempts in time. In addition, to further increase the transmission efficiency, we adopt the Sparse Code Multiple Access (SCMA) technique for PUSCH resources, because SCMA results as the most promising Non-Orthogonal Multiple Access (NOMA) technique to support massive MTC connectivity with small-size data. Simulation results show that the proposed control framework significantly improves the number of succeeded communications and guarantees lower energy consumption in comparison with other proposals available in literature.