Orthogonal Projection and Distributed Compressed Sensing-Based Impulsive Noise Estimation for Underwater Acoustic OSDM Communication

Zhou, Yuehai; Wang, Rong; Yang, Xiaoyu; Tong, Feng

doi:10.1109/jiot.2023.3303182

Cited by 3 publications

(4 citation statements)

References 43 publications

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“…In this section, we evaluate the performance of the proposed algorithm for both CIR and DD spread function estimations within the single-carrier transmission scheme. A twocomponent Gaussian mixture noise (GMN) model [2] is adopted to simulate environments contaminated by impulsive noise with the probability density function denoted as…”

Section: Numerical Simulationsmentioning

confidence: 99%

“…This leads to a total of N " 500 unknown channel parameters to estimate. For sparse channel estimation, the probe symbol sequence length is M " 2 3 N « 330, highlighting the problem is ill-posed. The second-order method, IPM-PCG, is excluded due to computational intensity and reduced accuracy in complex-valued problems.…”

Section: Simulation Ii: Doubly Spread Channel Estimationmentioning

confidence: 99%

“…In recent years, the expanding scope of marine exploration and the burgeoning Internet of Underwater Things (IoUT) in maritime domains have increased the demand for highdata-rate and reliable wireless communication links [1,2]. Underwater Acoustic (UWA) transmission, leveraging sound waves for their lower attenuation and longer propagation range compared to alternative carriers like electromagnetic and optical waves, is still the most practical solution in ocean environments [3].…”

Section: Introductionmentioning

confidence: 99%

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Channel Estimation for Underwater Acoustic Communications in Impulsive Noise Environments: A Sparse, Robust, and Efficient Alternating Direction Method of Multipliers-Based Approach

Tian,

Yang,

et al. 2024

Remote Sensing

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Channel estimation in Underwater Acoustic Communication (UAC) faces significant challenges due to the non-Gaussian, impulsive noise in ocean environments and the inherent high dimensionality of the estimation task. This paper introduces a robust channel estimation algorithm by solving an l1−l1 optimization problem via the Alternating Direction Method of Multipliers (ADMM), effectively exploiting channel sparsity and addressing impulsive noise outliers. A non-monotone backtracking line search strategy is also developed to improve the convergence behavior. The proposed algorithm is low in complexity and has robust performance. Simulation results show that it exhibits a small performance deterioration of less than 1 dB for Channel Impulse Response (CIR) estimation in impulsive noise environments, nearly matching its performance under Additive White Gaussian Noise (AWGN) conditions. For Delay-Doppler (DD) doubly spread channel estimation, it maintains Bit Error Rate (BER) performance comparable to using ground truth channel information in both AWGN and impulsive noise environments. At-sea experimental validations for channel estimation in Orthogonal Frequency Division Multiplexing (OFDM) systems further underscore the fast convergence speed and high estimation accuracy of the proposed method.

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Section: Numerical Simulationsmentioning

confidence: 99%

Section: Simulation Ii: Doubly Spread Channel Estimationmentioning

confidence: 99%

Section: Introductionmentioning

confidence: 99%

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Channel Estimation for Underwater Acoustic Communications in Impulsive Noise Environments: A Sparse, Robust, and Efficient Alternating Direction Method of Multipliers-Based Approach

Tian,

Yang,

et al. 2024

Remote Sensing

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“…It also acts as a major performance degradation factor by causing a decrease in the Signal-to-Noise Ratio (SNR) and it acts as a noise source within the ambient sound level in coastal seas [7,8]. Examples include areas such as human underwater communication [9,10], animal underwater communication [11], sonar signal processing [12,13], and target detection [14]. In particular, in the field of underwater communication, the bit error rate performance of orthogonal frequency division multiplexing systems may be severely degraded due to the influence of frequent SSN [10].…”

Section: Introductionmentioning

confidence: 99%

Snapping Shrimp Noise Detection Based on Statistical Model

Park,

Seok,

Hong

2023

JMSE

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Snapping Shrimps (SSs) live in a warm ocean except the North and South Poles, and they are characterized by generating strong shock waves underwater using large claws. Shock waves generated by these SSs are used for marine noise research as a signal and as a noise source, because they cause a decrease in the Signal-to-Noise Ratio (SNR), acting as one of the disruptors in fields such as sonar for target detection and underwater communication. A state-of-the-art technique to detect Snapping Shrimp Noise (SSN) is Linear Prediction (LP) analysis. Using the feature where SSN occurs for a very short time, the SSN interval was detected based on the phenomenon where the residuals appear large in the SSN interval when the LP analysis is used. In this paper, we propose an SSN interval detection technique using the Likelihood Ratio (LR) as a follow-up study to the LP-analysis-based method for further performance improvements. The proposed method was used to analyze the statistical distribution characteristics of the LP residual of SSNs compared to Gaussian, Laplace, and Gamma distributions through the Goodness-Of-Fit test. Based on this, the statistical-model-based LRs of the three distributions were computed to detect the SSN interval. Comparing the proposed method with the state-of-the-art method, the proposed method achieved 0.0620, 0.0675, and 0.0662 improvements in Gaussian, Laplace, and Gamma distributions in the Receiver Operating Characteristic curve and Area Under Curve, respectively. The study results confirmed that the proposed method can operate effectively in the marine acoustic environment. This can help find accurate intervals for the automatic labeling of or reduction in SSN.

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Research on an M-Ary Frequency Shift Keying With Index Modulation System for Underwater Acoustic Communication

Yang,

Zhou,

Yao

et al. 2024

IEEE Internet Things J.

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Orthogonal Projection and Distributed Compressed Sensing-Based Impulsive Noise Estimation for Underwater Acoustic OSDM Communication

Cited by 3 publications

References 43 publications

Channel Estimation for Underwater Acoustic Communications in Impulsive Noise Environments: A Sparse, Robust, and Efficient Alternating Direction Method of Multipliers-Based Approach

Channel Estimation for Underwater Acoustic Communications in Impulsive Noise Environments: A Sparse, Robust, and Efficient Alternating Direction Method of Multipliers-Based Approach

Snapping Shrimp Noise Detection Based on Statistical Model

Research on an M-Ary Frequency Shift Keying With Index Modulation System for Underwater Acoustic Communication

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