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- W2365362425 abstract "Due to the low power spectrum density and complicated transfer multi-path of Ultra-Wideband(UWB) signal,it is important to do channel estimation accurately.But it’s difficult to sample it directly as its wider band width.However,compressed sensing(CS) provides a feasible way with lower sampling speed.Common random projection matrix remains high coherence with UWB channel sparse transform matrix and this leads the algorithm achieve reconstruction requirement only at high compressing ratio,which means that it still needs a high sampling speed.To solve these problems,an UWB channel estimation method based on an adaptive projection matrix using bayesian compressed sensing(BCS) is proposed in this paper.BCS sets posterior probability density function which is controlled by hyperparameters to each value in the channel vector and computes its statistical characteristics.Using covariance matrix to reckon new projection vector which can lower the differential entropy of reconstruction value steepest.This method enhances the certainty of reconstruction value and lowers the sampling speed using fewer samples.The experimental results show that this method can achieve a better reconstruction performance compared to the existing CS reconstruction algorithm at low compressing ratio and decrease the sampling speed notably." @default.
- W2365362425 created "2016-06-24" @default.
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- W2365362425 date "2013-01-01" @default.
- W2365362425 modified "2023-09-25" @default.
- W2365362425 title "UWB channel estimation through compressed sensing based on adaptive projection matrix" @default.
- W2365362425 hasPublicationYear "2013" @default.
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