MC-LoRa: Multi-node Concurrent Localization for LoRaWAN Indoors and Outdoors

Abstract

Multi-node localization is crucial for large-scale and densely deployed Internet of Things (IoT) devices connected via LoRaWAN. Due to limitations in bandwidth and the number of RX chains (antennas), existing LoRaWAN-based localization methods often rely on frequency hopping or additional infrastructure to improve location accuracy. Although promising, these methods struggle to localize multiple nodes during packet collisions. In this paper, we propose MC-LoRa, which features a multi-node localization pipeline that includes reliable preamble detection under the near-far effect, tackling inter-symbol interference among multiple packets, and a virtual antenna array method to obtain extra channel state measurements within a single channel. This approach not only enhances angle resolution in our AoA-based system but also eliminates the need for time-consuming frequency hopping, requiring only software processing in existing gateways. Our extensive evaluation results show that MC-LoRa achieves median errors of 7.1m (single-node), 9.2m (multi-node) in an outdoor area of 140m × 100m, and 2.0m (single-node), 3.9m (multi-node) in an indoor area of 20m × 16m, which represent improvements of 1.1×, 2× and 1.5×, 1.7× compared to the baseline. Additionally, MC-LoRa can provide localization service for hundreds of LoRaWAN nodes with accuracy comparable to that of a state-of-the-art single-node system. Its wide localization range and high accuracy enable MC-LoRa to benefit a variety of applications, including asset tracking, navigation in vast indoor spaces (e.g., airports, warehouses and halls), and smart cities.