Vector Gaussian Successive Refinement With Degraded Side Information

We investigate the problem of successive refinement for Wyner-Ziv coding with degraded side information and obtain a complete characterization rate region quadratic vector Gaussian case. The achievability part is based on evaluation Tian-Diggavi inner bound that involves auxiliary random vectors. For converse part, matching outer obtained aid new extremal inequality. Herein, proof this inequality depends integration monotone path argument doubling trick as well information-estimation relations.