Angle of arrival estimation for low power and long range communication networks

Over a decade ago, Low Power Wide Area Networks (LPWAN) emerged to meet the new communication requirements demanded by the Internet of Things (IoT) revolution. Therefore, seemingly futuristic ideas that are based on the IoT concept (e.g. smart cities, smart highways, smart farms, etc) appear ever more plausible. This communication revolution can be attributed to the LPWAN’s capability of establishing long range communication links (up to several kilometers) using low power transceivers. Moreover, due to the low production cost, the LPWAN transceivers are expected to be deployed in incredibly large numbers throughout the world. Besides this large number, most of these transceivers are also mobile and thus require a means of tracking their location. Consequently, locating and tracking the massive amount of transceivers is considered a key feature that distinguishes LPWAN technologies from each other. Locating a transmitting device in a wireless communication system requires inverse calculations for the received signal’s parameters. Over the years, several techniques have been developed and deployed to provide localization solutions. These techniques depend either on the Received Signal Strength (RSS), the Time of Arrival (ToA), the Time Difference of Arrival (TDoA) or the Angle of Arrival (AoA) parameters of the received signals. RSS and ToA-based approaches estimate the distance between the transmitter and the receiver by respectively measuring the signal strength and the travel time of the received signal. TDoA approaches estimate the transmitter’s location by measuring the travel time difference of the received signals by various receivers. Finally, AoA-based approaches estimate the angle between the transmitter and the receiver by measuring the phase of the received signal at different points in space using array antennas. However, unlike RSS and time-based localization systems, commercially available AoA-based localization systems for LPWAN technologies do not yet exist. This absence can be attributed to the high deployment cost and complexity that are associated with the AoA estimation systems. Therefore, promoting AoA-based localization solutions for LPWAN technologies can only be achieved by reducing the production cost and simplifying the system complexity, which constitute the main goal of this thesis. This thesis constitutes two major parts, the first part provides hardware and software solutions to estimate the AoA parameters of the received LPWAN signals in real life environments. These solutions aim to simplify the AoA estimation system’s complexity and reduce the implementation costs, meanwhile maintaining accurate AoA estimates of the received signals. The second part provides localization algorithms that convert the AoA estimates of the received signals to a location estimate. The proposed localization algorithms aim to improve the localization accuracy using minimal computational power. The proposed solutions were subjected to a thorough system design, a detailed mathematical formulation, and three different validation methods (validation by simulations, experiments in controlled environments and experiments in real life environments). Therefore, this thesis might help reduce the gap between the theoretical algorithms and practical implementation, to provide accurate, cost effective, and computationally efficient AoA estimation solutions that are suitable for LPWAN technologies.

Publication year:2021

Keywords:Doctoral thesis

Accessibility:Open