Sparse Code Multiple Access-Based Edge Computing for IoT Systems

In this paper, a sparse code multiple access (SCMA)-based edge computing scheme is proposed for Internet-of- Things (IoT) systems. The aim of implementing SCMA, which is a nonorthogonal multiple access resource allocation technique, is to improve network connectivity and maximize data rate provision. The proposed edge-IoT system is investigated under different SCMA configurations to explore the various performance aspects such as connectivity, throughput, task completion time, and complexity. First, the problem is formulated as a data rate maximization problem for SCMA-based heterogeneous networks under power constraints. Then, the problem is subdivided into a power allocation problem, which is solved using the water filling approach, and a codebook allocation problem that is solved using a heuristic algorithm. The results show that the SCMA scheme can significantly improve the IoT performance compared to the conventional orthogonal frequencydivision multiple access resource allocation scheme in terms of connectivity, throughput, and task completion time provided that SCMA configurations are suitable with IoT processing capabilities to avoid undesired detection latency.