Resource Allocation for SCMA-Based IoT Systems With Layered Multicast

Due to the lack of spectrum resources, effective methods must be proposed to meet the needs of the Internet of Things (IoT) massive connectivity. In this paper, two effective techniques to improve spectral efficiency, namely, sparse code multiple access (SCMA) and wireless multicast, are used together for the IoT system to expand network capacity. Different from existing works, we introduce layered coding into the SCMA-based IoT system and consider two channel state information (CSI) feedback scenarios, which can make full use of the diversity gain of multiple receivers. The original multicast data are divided into one basic layer (BL) and several enhancement layers (ELs) by layered coding. IoT receivers with good channel gain can achieve better quality of service by receiving more data layers. In the transmission scheme with CSI, the physical resources allocated to the BL and ELs can be dynamically adjusted. In the transmission scheme without CSI, a fixed resource allocation scheme is performed because it is impossible to calculate the multicast rate of each codebook in real time. To further improve the system capacity, we have proposed resource allocation algorithms for these two schemes according to different requirements for computational complexity. The simulation results show that the proposed schemes can provide a higher system capacity than unicast SCMA and nonlayered multicast SCMA.