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Erschienen in:
2014 | OriginalPaper | Buchkapitel
An Improved Orthogonal Matching Pursuit Algorithm for Signal Reconstruction in Wireless Body Sensor Network
verfasst von : Rui Jiang, Yongsheng Ding, Kuangrong Hao, Shiyu Shu
Erschienen in: Life System Modeling and Simulation
Verlag: Springer Berlin Heidelberg
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Energy efficiency is the primary challenge of wireless body sensor network (WBSN). Compressed sensing (CS) is a rapidly emerging signal processing technique that enables accurate capture and reconstruction of sparse signals from only a fraction of Nyquist Rate samples, significantly reducing the data-rate and system power consumption which solve the key issues in the WBSN. This paper proposes an improved CS-based Orthogonal Matching Pursuit (IOMP) algorithm in the WBAN. We evaluate the IOMP algorithm against the OMP algorithm from four aspects: compression ratio, percentage root-mean-square distortion,signal noise ratio and iterative times. Simulation results shows that, at the same compressed ratio, PRD SNR and iterative times of the proposed method are improved over those of the OMP algorithm.