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- W2980116174 abstract "For single-carrier underwater acoustic (UWA) communications, a time-domain channel estimation based equalizer (CEE) is usually overlooked in favor of a direct adaptive equalizer (DAE), mainly due to its high complexity despite potentially better performance. The complexity burden of a CEE is mainly caused by the calculation of the equalizer coefficients, which involves matrix inversion operations at a complexity cubic in the channel length L. The value of L for a UWA channel can amount to several tens or even hundreds, making the CEE scheme prohibitively costly. In this work, a CEE scheme with a complexity quadratic in L is proposed. It is designed from the Kalman filter (KF) perspective and referred as the Kalman equalizer (KE). In the KE, an adaptive channel estimator is coupled with a KF based symbol estimator. The estimated channel is used to construct the KF measurement matrix, and there is no need to compute any equalizer coefficients. Moreover, the channel sparsity can be conveniently utilized to reduce the equalization complexity. The proposed KE scheme was verified by experimental data collected in at-sea trials and showed significant performance gain over a DAE." @default.
- W2980116174 created "2019-10-18" @default.
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- W2980116174 date "2019-06-01" @default.
- W2980116174 modified "2023-10-17" @default.
- W2980116174 title "Kalman Filter Based Equalization for Underwater Acoustic Communications" @default.
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- W2980116174 doi "https://doi.org/10.1109/oceanse.2019.8866875" @default.
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