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Decentralized Turbo Bayesian Compressed Sensing with Application to UWB Systems

Abstract

In many situations, there exist plenty of spatial and temporal redundancies in original signals. Based on this observation, a novel Turbo Bayesian Compressed Sensing (TBCS) algorithm is proposed to provide an efficient approach to transfer and incorporate this redundant information for joint sparse signal reconstruction. As a case study, the TBCS algorithm is applied in Ultra-Wideband (UWB) systems. A space-time TBCS structure is developed for exploiting and incorporating the spatial and temporal a priori information for space-time signal reconstruction. Simulation results demonstrate that the proposed TBCS algorithm achieves much better performance with only a few measurements in the presence of noise, compared with the traditional Bayesian Compressed Sensing (BCS) and multitask BCS algorithms.

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Correspondence to Depeng Yang.

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Open Access This article is distributed under the terms of the Creative Commons Attribution 2.0 International License (https://creativecommons.org/licenses/by/2.0), which permits unrestricted use, distribution, and reproduction in any medium, provided the original work is properly cited.

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Yang, D., Li, H. & Peterson, G.D. Decentralized Turbo Bayesian Compressed Sensing with Application to UWB Systems. EURASIP J. Adv. Signal Process. 2011, 817947 (2011). https://doi.org/10.1155/2011/817947

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  • DOI: https://doi.org/10.1155/2011/817947

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