Measurement-calibrated Conflict Graphs for Dynamic Spectrum Distribution (Poster Abstract)

Abstract—Building accurate interference maps is critical for performing reliable and efficient spectrum allocation. In this work, we use empirical data to explore the feasibility of using measurement-calibrated propagation models to build accurate interference models. Our work shows that calibrated propagation models generate location-dependent signal prediction errors, producing overly conservative conflict graphs that actually improve reliability of spectrum allocation by reducing the impact of unpredicted accumulative interference. I. SUMMARY The key to a successful spectrum allocation is gaining an accurate understanding of interference patterns among spectrum users. Generating accurate model of interference for specific environments, however, is a challenging task. Due to the complex nature of RF propagation, modeling interferenc