Performance Evaluation of Random Access for Small Data Transmissions in Highly Dense Public and Private NB-IoT Networks

With an increasing number of global Internet of Things devices, networks face the challenge of high scalability and support of massive numbers of small data transmissions. With Early Data Transmission for NB-IoT networks, which is called Small Data Transmission for 5G New Radio and Reduced Capability networks, standardization has introduced efficiency optimizations with reduced signaling overhead for better scalability of these networks. Though, previous work demonstrated that current NB-IoT configurations are not well-balanced when it comes to Random Access windows and additional uplink resources. In this work, we evaluated different sets of Random Access parameters derived from public NB-IoT networks and identified new optimal parameters for smart urban networks as well as for private high-density micro cells, based on a detailed analytic Random Access model. The identified optimal Random Access parametrization supports 30 million Random Access preamble transmissions per day when using 15 additional non-anchor carriers and 1% Block Error Rate, which is an improvement of 150% to 223% compared to current public networks. When it comes to private high-density micro cells, up to 1,200 Random Access preambles per second are supported, which is between 23 and 82 times more than with legacy configurations. The results demonstrate the importance of well-configured NB-IoT networks, especially for contention-based channels like Random Access. For further increasing numbers of Internet of Things devices in the future, networks must be adapted for better spectral efficiency and better support of small data transmissions, as shown in this work.