Basis Mismatch in a Compressively Sampled Photonic Link

Abstract

To accurately reproduce an incoming signal, compressive sampling requires that the signal have a sparse representation from within a finite basis or dictionary of vectors. If the incoming signal cannot be sparsely represented by vectors within the given basis or dictionary—a situation sometimes termed basis mismatch—then reconstruction error or failure is likely. In this letter, we present both simulated and experimental results showing the influence of basis mismatch on the ability of a photonic compressive sampling system to accurately reconstruct harmonic signals. Our reconstruction algorithm utilizes gradient projection for sparse reconstruction coupled with a discrete Fourier basis.