On Positioning Performance for the Narrow-Band Internet of Things: How Participating eNBs Impact?

Due to the advantages including low cost, low power, massive connections, and wide coverage, and with the assistance of fog computing to achieve low latency, location awareness, etc., narrow-band Internet of Things (NB-IoT) can be widely applied in industry. Many NB-IoT industrial applications need a positioning feature for tracking, fault localization and fast repair, etc. When dedicated positioning systems, e.g., Global Position System, are unavailable for a low-power, low-cost NB-IoT device, it is necessary to rely on terrestrial cellular network for localization. Existing performance studies in NB-IoT cellular-network-based positioning have been mostly carried out by targeting deterministic scenarios. However, it is hard to provide general insights with changing system design parameters and propagation effects, due to the random variations in device location, network coverage, channel condition, etc. This paper develops a general analytical model to study the NB-IoT positioning performance. The location randomness of the device to be localized is considered through the distance distributions between the device and its surrounding evolved node Bs (eNBs). This makes it possible for using the powerful probabilistic distance-based tools from geometric probability to derive the probability that at least a fixed number of participating eNBs can be heard by the device. The model considers both the interference and the NB-IoT system-related parameter settings. It also includes modeling the eNB transmission coordination and traffic load. The obtained results reveal how participating eNBs impact the NB-IoT positioning performance, with the effects of a set of parameter settings investigated.