Sparse signal recovery with side information

The paper proposes an algorithm for signal recovery with side information. It is assumed that the decoder has a priori knowledge about the sparse source signal in the form of side information, that can be used to estimate positions of significant elements in the source. The proposed iterative algorithm extends the orthogonal matching pursuit (OMP) algorithm used in compressive sampling, and is robust to partially noisy side information. Thus it is suitable for scenarios whereby a correlated source is available at the decoder. We apply the algorithm to spectrum sensing and image acquisition, and show great advantages of the proposed solution, compared to OMP (no side information) in terms of improved performance and reduced execution time.