Performance Analysis of Grant-Free Random-Access NOMA in URLL IoT Networks

Internet-of-Things (IoT) networks have recently emerged to provide massive connectivity for many application scenarios and services. Additionally, developing spectrum-access strategies for a large number of nodes with sporadic data traffic behaviors in IoT networks has attracted much attention recently. However, developing such strategies becomes more challenging when ultra-reliable low-latency (URLL) transmissions are required. As IoT networks entail spectrum-efficient transmission schemes, non-orthogonal multiple-access (NOMA) has emerged as a key enabler for such networks. On the other hand, grant-free random-access (RA) techniques are particularly promising for high spectral-efficiency and massive connectivity, since they reduce signaling overhead, and packet latency. Therefore, in this paper, uplink RA-NOMA IoT networks with clustered IoT devices is studied, where short packet and diversity transmissions are adopted to meet the URLL requirements. To reduce the negative effect of diversity transmission on packet latency, multiple replicas of packets are accommodated within different resource blocks (RBs) in the same transmission time interval (TTI). The analytical expressions of network metrics, namely, average packet latency, reliability, and GoodPut are derived. Furthermore, the effect of the number of packet replicas, blocklength, and cluster size on the network metrics is evaluated. Finally, the analytical derivations are utilized to find the optimal values for the number of packet replicas, blocklength, and power control parameters, such that the network GoodPut is maximized, subject to URLL constraints.