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Wang W.,Electronic Engineering Institute | Yang J.,Key Laboratory of Electronic Restriction AnHui Province
Journal of Computational Information Systems | Year: 2012

Due to the low power spectrum density and complicated transfer multi-paths of Ultra-Wideband (UWB) signal, it is important to estimate transmit channel's properties accurately, either in cooperative or non-cooperative communication. But it's difficult to sample UWB signal directly as its wider band width. However, compressed sensing (CS) provides a feasible way with lower sampling speed. Based on the steepest descend method, Gradient Pursuit (GP) algorithm can search along the negative gradient direction at an appropriate step size in order to decrease the reconstruction error rapidly. But the reconstruction performance of GP algorithm is not fantastic because it lacks restriction on sparsity of the reconstruction vector. To solve this problem, an improved GP algorithm is proposed in this paper. Compared with original GP algorithm, an l 1-norm restriction on channel vector is added to objective function in improved algorithm. The conception of polarity vector is raised in order to obtain the derivative of l 1-norm more conveniently. The proposed algorithm utilizes the property that l 1-norm has strong restriction on sparsity to reinforces the bound of reconstruction vector as sparse as possible. The experimental results show that proposed algorithm can promote reconstruction precision compared with GP algorithm and other existing algorithms used in UWB channel estimation, and it can also raise reconstruction speed compared with OMP and BP algorithm. © 2011 by Binary Information Press. Source


Weidong W.,Electronic Engineering Institute | Weidong W.,Key Laboratory of Electronic Restriction AnHui Province | Jun-an Y.,Electronic Engineering Institute | Jun-an Y.,Key Laboratory of Electronic Restriction AnHui Province | And 4 more authors.
IET Communications | Year: 2014

Pulse position modulation-ultra wideband (PPM-UWB) communication adopts ultra narrow pulse as the transmitted signal. Owing to the low-power spectral density and ultra wide bandwidth, it is difficult to detect and sample PPM-UWB signal directly. There are already some researches on using compressed sensing (CS) theory for UWB communication with lower sampling speed. However, these methods take the sparseness of pulse position or transmission channel into account separately and they are unfit for practical communication. To solve these problems, a dual-sparse reconstruction method is proposed in this paper to process PPM-UWB communication signal based on CS theory. Proposed method designs the target signal which needed to be reconstructed as a dual-sparse vector. This vector combines the sparseness of PPM pulse position and UWB channel multi-paths simultaneously, hence it has dual sparseness. The information code can be demodulated from reconstructed dual-sparse vector directly by using energy detection method. Extensive numerical simulations demonstrate the validity and applicability of proposed method. © The Institution of Engineering and Technology 2014. Source

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