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Fast estimation of sparse doubly spread acoustic channels.

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Bibliographic Details
Title: Fast estimation of sparse doubly spread acoustic channels.
Authors: Zeng, Wen-Jun, Xu, Wen
Source: Journal of the Acoustical Society of America; Jan2012, Vol. 131 Issue 1, p303-317, 15p
Subject Terms: SPARSE matrices, SOUND, DOPPLER effect, DATA structures, ALGORITHMS
Abstract: The estimation of doubly spread underwater acoustic channels is addressed. By exploiting the sparsity in the delay-Doppler domain, this paper proposes a fast projected gradient method (FPGM) that can handle complex-valued data for estimating the delay-Doppler spread function of a time-varying channel. The proposed FPGM formulates the sparse channel estimation as a complex-valued convex optimization using an ℓ1-norm constraint. Conventional approaches to complex-valued optimization split the complex variables into their real and imaginary parts; this doubles the dimension compared with the original problem and may break the special data structure. Unlike the conventional methods, the proposed method directly handles the complex variables as a whole without splitting them into real numbers; hence the dimension will not increase. By exploiting the block Toeplitz-like structure of the coefficient matrix, the computational complexity of the FPGM is reduced to O(LNlogN), where L is the dimension of the Doppler shift and N is the signal length. Simulation results verify the accuracy and efficiency of the FPGM, indicating that is robust to parameter selection and is orders-of-magnitude faster than standard convex optimization algorithms. The Kauai experimental data processing results are also provided to demonstrate the performance of the proposed algorithm. [ABSTRACT FROM AUTHOR]
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Database: Complementary Index
Description
Abstract:The estimation of doubly spread underwater acoustic channels is addressed. By exploiting the sparsity in the delay-Doppler domain, this paper proposes a fast projected gradient method (FPGM) that can handle complex-valued data for estimating the delay-Doppler spread function of a time-varying channel. The proposed FPGM formulates the sparse channel estimation as a complex-valued convex optimization using an ℓ<subscript>1</subscript>-norm constraint. Conventional approaches to complex-valued optimization split the complex variables into their real and imaginary parts; this doubles the dimension compared with the original problem and may break the special data structure. Unlike the conventional methods, the proposed method directly handles the complex variables as a whole without splitting them into real numbers; hence the dimension will not increase. By exploiting the block Toeplitz-like structure of the coefficient matrix, the computational complexity of the FPGM is reduced to O(LNlogN), where L is the dimension of the Doppler shift and N is the signal length. Simulation results verify the accuracy and efficiency of the FPGM, indicating that is robust to parameter selection and is orders-of-magnitude faster than standard convex optimization algorithms. The Kauai experimental data processing results are also provided to demonstrate the performance of the proposed algorithm. [ABSTRACT FROM AUTHOR]
ISSN:00014966
DOI:10.1121/1.3665992