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We study the problem of sampling and reconstruction of bandlimited graphsignals where the objective is to select a node subset of prescribedcardinality that ensures interpolation of the original signal with the lowestreconstruction error. We propose an efficient iterative selection samplingapproach and show that in the noiseless case the original signal is exactlyrecovered from the set of selected nodes. In the case of noisy measurements, abound on the reconstruction error of the proposed algorithm is established. Wefurther address the support identification of the bandlimited signal withunknown support and show that under a pragmatic sufficient condition, theproposed framework requires minimal number of samples to perfectly identify thesupport. The efficacy of the proposed methods are illustrated through numericalsimulations on synthetic and real-world graphs.

A Novel Scheme for Support Identification and Iterative Sampling of Bandlimited Graph Signals