Abstract
Underwater acoustic (UWA) communications systems suffer from a low signal-to-noise ratio (SNR) and a doubly selective channel, which are caused by many limitations, such as high propagation loss, slow propagation speed, and time-varying environmental factors. To overcome a low SNR, various diversity techniques are often adopted in UWA communications. However, such diversity can only be exploited with knowledge of the channel. Accordingly, channel estimation needs to be performed without obtaining the benefit of diversity. Moreover, accurate side information that can support a channel estimator (CE) is difficult to acquire at a low SNR under doubly selective channel. In this article, a novel CE based on an adaptive denoising is proposed for UWA orthogonal frequency-division multiplexing (OFDM) systems. The proposed method exploits two different types of pilot symbols. Channel impulse response (CIR) is estimated based on primary pilot symbols. By minimizing the squared error of the received secondary pilot symbols, a near-optimal denoising window is adaptively determined based on the channel length for the given CIR estimate. The proposed method does not require a priori information about channel statistics and SNR values. Analysis on the effect of denoising and the performance of the proposed denoising window estimator are also presented. Simulation and at-sea experiments verify that the proposed method has superior performance, compared with conventional CEs over diverse channel conditions. Complexity analysis shows that the proposed method is computationally efficient. Therefore, the proposed method is effective for real-time UWA OFDM systems under a harsh UWA channel with strong noise.
Highlights
Underwater wireless communications systems have received substantial attention because it is essential to facilitate new applications, such as underwater environment monitoring, undersea rescues, deep sea mining, and so on
It is seen from the table that orthogonal matching pursuit (OMP) and DW-SACoSaMP require more than 20 times greater complexity compared with the proposed method, where huge complexity is mainly from the matrix inversion operation performed at every iteration
In this paper, a channel estimator (CE) method based on an adaptive denoising technique is proposed for a underwater acoustic (UWA) cyclic prefix (CP)-orthogonal frequency division multiplexing (OFDM) system in order to overcome strong noise and a harsh underwater channel
Summary
Underwater wireless communications systems have received substantial attention because it is essential to facilitate new applications, such as underwater environment monitoring, undersea rescues, deep sea mining, and so on. Yong-Ho Cho et al.: Channel Estimation Based On Adaptive Denoising for Underwater Acoustic OFDM Systems high-speed link with UWA communications systems. The proposed method yields a near-optimal denoising window by minimizing the squared error (SE) of the received secondary pilot symbols without a priori information about channel statistics and SNR values. The effect of denoising and the performance of the proposed denoising window estimator are analyzed from the perspective of mean squared error (MSE) It is demonstrated through simulation and at-sea experiments that the proposed method outperforms conventional CEs [8], [15], [24] under diverse UWA channels. Coll(X) and rowl(X), Hak-Lim Ko et al.: Channel Estimation Based On Adaptive Denoising for Underwater Acoustic OFDM Systems respectively, are the l-th column and row vector of X D(·) denotes a diagonalization operation. coll(X) and rowl(X), Hak-Lim Ko et al.: Channel Estimation Based On Adaptive Denoising for Underwater Acoustic OFDM Systems respectively, are the l-th column and row vector of X
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