A novel sensing matrix design applied to distributed compressed estimation in WSN

We proposed a novel sensing matrix for compressed sensing (CS) based distributed compressed estimation (DCE) scheme. In traditional approaches for sensing matrix design, normalization of the column vectors is independent from optimizing mutual coherence. The proposed algorithm integrates these two processes into one framework, which gives the cost function a profound physical meaning. Applying this new sensing matrix design algorithm results in a higher reconstruction accuracy and a better realtime performance on channel estimation for a wireless sensor network (WSN), which is a development of DCE scheme via CS. Simulations show the higher reconstruction accuracy and shorter running time of DCE related to the new sensing matrix compared to the analysis existing approaches.

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