Performance Analysis of URLL Random-Access NOMA-Enabled IoT Networks with Short Packet and Diversity Transmissions

Abstract

Recently, non-orthogonal multiple-access (NOMA) has been proposed to improve spectrum-efficiency and throughput of 5G cellular networks, and is also considered a key-enabler for ultra-reliable and low-latency (URLL) communications. Moreover, the Internet-of-Things (IoT) paradigm has emerged to provide massive-connectivity for intelligent devices and systems, which entail spectrum-efficient transmission schemes. Hence, exploiting NOMA for URLL transmissions in IoT networks is inevitable. Furthermore, random-access (RA) techniques are also considered essential to enable massive URLL IoT networks, since they reduce signaling overhead and packet latency, especially when massive numbers of clustered IoT devices with sporadic traffic behaviour are considered. In this paper, the performance of uplink RA-NOMA in URLL IoT networks with short packet and diversity transmissions is analyzed. Specifically, network metrics-such as average packet latency, reliability, and GoodPut-are mathematically derived. Additionally, the effect of transmission diversity, and number of data bits per blocklength on the different network metrics has been extensively evaluated, illustrating several tradeoffs between the different network metrics as well as highlighting the importance of carefully selecting the network parameters to satisfy the URLL requirements.