Statistical Inference on Spectrum Data for Design and Enforcement of Harm Claim Thresholds

Abstract

Harm claim thresholds (HCTs) are a promising approach for regulators to specify interference limits in a technology-neutral fashion, and a useful parameter spectrum access systems can use to manage the aggregate interference caused by transmitters they control. However, existing literature provides very little guidance how HCTs should be set and enforced. In this paper, we propose a detailed regulatory framework for gathering and processing of measurement data for enforcing and setting HCTs. We introduce the central concepts of stratification and weighting of measurement data, and show their importance in ensuring representativeness of measurements and enabling robust estimation of statistical confidence on results. For deriving HCT thresholds from measurements, we propose additional representativeness criteria that a regulator should apply to avoid underestimation of field strength levels related to existing wireless services. We demonstrate application of our proposed framework using an extensive drive test data set, and show that the chosen HCT percentile is critical in determining how much data needs to be gathered for enforcement. We also show how spatial prediction techniques can be used to deal with data sets that have been collected non-uniformly over the region of interest, emphasizing the need for modern bias-corrected techniques.