Paper on Sample-Efficient Spatio-Spectral Whitespace Detection published in IEEE Access!

The paper “Sample-Efficient Spatio-Spectral Whitespace Detection Using Least Matching Pursuit” proposes a novel approach to identify unused resources in both frequency and space with multi-antenna RF transceivers. This work uses non-uniform wavelet sampling (NUWS) in order to efficiently sample multi-antenna RF signals and utilizes least matching pursuit (LMP) to identify unused frequencies in space at sub-Nyquist sampling rates. Simulation results demonstrate that reliable spatio-spectral whitespace detection is possible with 16x lower sampling rates than methods relying on Nyquist sampling.

The paper has been co-authored by Sweta Soni (Cornell), Alyssa B. Apsel (Cornell), and Prof. Christoph Studer and appeared in IEEE Access. You can find the paper on external page IEEE.