Channel Estimation Based On Adaptive Denoising for Underwater Acoustic OFDM Systems

• Published in: IEEE access Vol. 8; p. 1
• Main Authors: Cho, Yong-Ho, Ko, Hak-Lim
• Format: Journal Article
• Language: English
• Published: Piscataway IEEE 01.01.2020; The Institute of Electrical and Electronics Engineers, Inc. (IEEE)
• Subjects: Acoustic noise; Adaptive denoising; Adaptive systems; channel estimation; experiment; Impulse response; Noise reduction; Orthogonal Frequency Division Multiplexing; orthogonal frequency division multiplexing (OFDM); Propagation; Signal to noise ratio; Symbols; System effectiveness; underwater acoustic communications; Underwater acoustics; Underwater communication
• ISSN: 2169-3536; 2169-3536
• DOI: 10.1109/ACCESS.2020.3018474

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 paper, 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.