This paper discusses the problem of accurately detecting signals from contraband WiFi devices, with the aim of achieving a high probability of detection.
This paper presents research that sought to resolve the problem of accurately detecting signals from contraband WiFi devices, noting that source locations may be selected in a worst-case fashion from within an indoor structure, such as a correctional facility, with the structure layout being known but inaccessible prior to deployment, and only a small number of detectors available for sensing the signals. The authors approached this question as a covering problem, where the goal was to achieve a high probability of detection at each of the grid points of the terrain. The authors employed a variant of the maximum coverage problem, which allowed them to account for aggregate coverage by several detectors, and a state-of-the-art commercial wireless simulator to provide SINR (Signal to Interference and Noise Ratio) measurements that informed their problem instances. The authors’ approach was formulated as a mathematical program to which additional constraints were added to limit the number of detectors. The authors evaluated the performance of the detector placement for classifier accuracy. In this paper, the authors present preliminary results, combining both simulation and real-world data to evaluate the performance of their approach against two competitors inspired from previously existing literature.