Towards Fine-Grained Indoor White Space Sensing

Exploring white spaces in the indoor environment has been recognized as a promising way to satisfy the rapid growth of the wireless spectrum demand. Although a few indoor white space exploration systems have been proposed in the past few years, they mainly focused on exploring white spaces at a small set of candidate locations. However, what we need are the white space availabilities at arbitrary indoor locations instead of only those at the candidate locations. In this paper, we first perform an indoor TV spectra measurement to study the characteristics of indoor white spaces in a fine-grained way. Then, we propose a Fine-gRained Indoor white Space Estimation mechanism, called FRISE, which could accurately estimate the white space availabilities at arbitrary indoor locations. FRISE mainly consists of a method to determine the positions of candidate locations and an accurate spatial interpolation algorithm. Furthermore, we evaluate the performance of FRISE based on real-world measured data. The evaluation results show that FRISE outperforms the existing methods in estimating white spaces at arbitrary indoor locations.