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Recently, new progress has been made in using basis expansion models for system identification with compressed sensing. To aid the application of these methodologies, we introduce a metric, called localized coherence, for choosing input signals that result in better estimation performance. Its definition is motivated through the analysis of the normalized mean Euclidean error of the channel estimate and its efficacy is demonstrated through numerical simulations.
Date of Publication: June 2011