Evaluation, Modeling and Optimization of Coverage Enhancement Methods of NB-IoT

Narrowband Internet of Things (NB-IoT) is a new Low Power Wide Area Network (LPWAN) technology released by the Third Generation Partnership Project (3GPP). The primary goals of NB-IoT are enhanced coverage, low cost, and long battery life. In order to enhance coverage, NB-IoT has new features, such as increasing transmission repetitions, decreasing bandwidth, and adapting the Modulation and Coding Scheme (MCS). In this paper, we present an implementation of these three features of NB-IoT in NS-3, an end-to-end network simulator. Using the developed simulation framework, the influence of the coverage enhancement features on network reliability and latency is evaluated. Furthermore, we propose a hybrid link adaptation strategy based on all three features, which tries to achieve optimal latency and coverage. To achieve this, we formulate and solve an optimization problem that finds the optimal value of repetitions, bandwidth and MCS such that the latency is minimum and the reliability is maintained. Based on the hybrid link adaption strategy, a new scheduler is implemented and evaluated in the NS-3 simulator. Through numerical results we show that the hybrid link adaptation method achieves lower latency and higher coverage than any of the coverage enhancement techniques. We also show that the proposed optimization method achieves the same performance as the exhaustive search method but with lower complexity.