System Model and Background

• We consider the structured sampling of structured signals, more specifically, using block diagonal (BD) measurement matrices to sense signals with uniform partitions that share the same sparsity profile. This model arises in distributed compressive sensing systems. • We are interested in the efficient recovery of the sparse signal and the corresponding performance as determined by the restricted isometry property (RIP) of the measurement matrix. • We characterize the RIP of the random BD matrix with respect to signals with the aforementioned structure. • We study the multiple measurement vector (MMV) problem as a special case of the general problem considered here. System model where • The sparse signal vecto