A Spectrum Surveying Framework for Dynamic Spectrum Access Networks

Dynamic spectrum access networks and wireless spectrum policy reforms heavily rely on accurate spectrum utilization statistics, which are obtained via spectrum surveys. In this paper, we propose a generic spectrum-surveying framework that introduces both standardization and automation to this process, as well as enables a distributed approach to spectrum surveying. The proposed framework outlines procedures for the collection, analysis, and modeling of spectrum measurements. Furthermore, we propose two techniques for processing spectrum data without the need for a priori knowledge. In addition, these techniques overcome the challenges associated with spectrum data processing, such as a large dynamic range of signals and the variation of the signal-to-noise ratio across the spectrum. Finally, we present mathematical tools for the analysis and extraction of important spectrum occupancy parameters. The proposed processing techniques have been validated using empirical spectrum measurements collected from the FM, television (TV), cellular, and paging bands. Results show that the primary signals in the FM band can be classified with a miss-detection rate of about 2% at the cost of 50% false-alarm rate, while nearly 100% reliability in classification can be achieved with the other bands. However, the classification accuracy depends on the duration and the range of frequencies over which data are collected, as well as the RF characteristics of the spectrum measurement receiver.