Automating CSI Measurement with UAVs: From Problem Formulation to Energy-Optimal Solution

Indoor localization has been an active research area given the popularity of Location-Based Services. The CSI fingerprinting based approach is one of the most practical and effective approaches since it can provide adequate accuracy with low overhead for users. The key drawback that limits its wide application is the huge amount of human effort required to build the fingerprint map. This paper is the first to explore addressing this limitation by automating CSI map construction using an Unmanned Aerial Vehicle (UAV). Given the limited battery capacity of commodity UAVs, it is extremely important yet challenging to optimize energy efficiency for the UAV during the CSI measurement task. To address this challenge, we formulate an energy optimization problem based on a novel graph model that includes the cost of possible actions for UAVs. We then transform the formulated problem to the classic Generalized Traveling Salesman Problem (GTSP), which can be solved efficiently. We implement the system on an off-the-shelf programmable drone equipped with a CSI measurement module. We achieve great energy efficiency improvement over the conventional coverage path planning algorithm. Meanwhile, accurate indoor localization can be achieved using the CSI data collected by our UAV system.