Time-Frequency Domain Turbo Equalization for Single-Carrier Underwater Acoustic Communications

He, Chengbing; Jing, Lianyou; Xi, Rui; Wang, Han; Hua, Fei; Dang, Qianqian; Zhang, Qunfei

doi:10.1109/access.2019.2919757

Cited by 14 publications

(4 citation statements)

References 38 publications

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“…For communication over underwater acoustic channels, OFDM is an efficient scheme. However, its performance will suffer from high peak-to-average power ratio (PAPR) value, and inter-carrier interference (ICI) caused by uneven Doppler frequency shift [16]. Compared with OFDM, Single-carrier (SC) technology has a better PAPR and is less sensitive to frequency offset.…”

Section: System Modelmentioning

confidence: 99%

“…In order to obtain the parameter value c i , a necessary condition for E(•) to be a minimum is that After the differential calculation for Eq. (13), we obtain Because function F (•) has the form of (12), we get Therefore, applying (16) to (15), we have Equation (17) forms a system of k equations in k unknown parameters c i By solving formula (18), the estimation ĉ i for parameters c i can be obtained. Then, we substitute ĉ i into (12), the correction estimation value for γ a,n can be given by γ o,n can be calculated with (10) Substitute (20) into (19), the relationship between SMSE, SMSE n and estimation SNR γ a,n can be given by (13)…”

Section: Fitting Between Estimated Snr and Actual Snrmentioning

confidence: 99%

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Adaptive modulation based on steady-state mean square error for underwater acoustic communication

Liu

Tan

Bai

2021

J Wireless Com Network

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To improve the transmission efficiency and facilitate the realization of the scheme, an adaptive modulation (AM) scheme based on the steady-state mean square error (SMSE) of blind equalization is proposed. In this scheme, the blind equalization is adopted and no training sequence is required. The adaptive modulation is implemented based on the SMSE of blind equalization. The channel state information doesn’t need to be assumed to know. To better realize the adjustment of modulation mode, the polynomial fitting is used to revise the estimated SNR based on the SMSE. In addition, we also adopted the adjustable tap-length blind equalization detector to obtain the SMSE, which can adaptively adjust the tap-length according to the specific underwater channel profile, and thus achieve better SMSE performance. Simulation results validate the feasibility of the proposed approaches. Simulation results also show the advantages of the proposed scheme against existing counterparts.

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Section: System Modelmentioning

confidence: 99%

Section: Fitting Between Estimated Snr and Actual Snrmentioning

confidence: 99%

Adaptive modulation based on steady-state mean square error for underwater acoustic communication

Liu

Tan

Bai

2021

J Wireless Com Network

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“…An adaptive nonlinearity (piecewise linear) was introduced into the channel equalization algorithm and its effectiveness was demonstrated through highly realistic experiments conducted on real-field data as well as accurate simulations of UWA channels (Kari et al, 2017). In recent years, in order to alleviate propagation errors, expedite convergence speed, and further enhance receiver performance, there has been growing research on adaptive turbo equalization (He et al, 2019;Xi et al, 2019;Qin et al, 2020). Considering the sparsity inherent in UWA channels, sparse matrices have been utilized to construct sparse equalizers, aiming to achieve faster convergence and lower error rates (Xi et al, 2020;Wang et al, 2021;Wang et al, 2021).…”

Section: Introductionmentioning

confidence: 99%

A simplified decision feedback Chebyshev function link neural network with intelligent initialization for underwater acoustic channel equalization

Zhou,

Zhang,

et al. 2024

Front. Mar. Sci.

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IntroductionIn shallow-water environments, the reliability of underwater communication links is often compromised by significant multipath effects. Some equalization techniques such as decision feedback equalizer, and deep neural network equalizer suffer from slow convergence and high computational complexity.MethodsTo address this challenge, this paper proposes a simplified decision feedback Chebyshev function link neural network equalizer (SDF-CFLNNE). The structure of the SDF-CFLNNE employs Chebyshev polynomial function expansion modules to directly and non-linearly transform the input signals into the output layer, without the inclusion of hidden layers. Additionally, it feeds the decision signal back to the input layer rather than the function expansion module, which significantly reduces computational complexity. Considering that, in the training phase of neural networks, the random initialization of weights and biases can substantially impact the training process and the ultimate performance of the network, this paper proposes a chaotic sparrow search algorithm combining the osprey optimization algorithm and Cauchy mutation (OCCSSA) to optimize the initial weights and thresholds of the proposed equalizer. The OCCSSA utilizes the Piecewise chaotic population initialization and combines the exploration strategy of the ospreywith the Cauchy mutation strategy to enhance both global and local search capabilities. RseultsSimulations were conducted using underwater multipath signals generated by the Bellhop Acoustic Toolbox. The results demonstrate that the performance of the SDFCFLNNE initialized by OCCSSA surpasses that of CFLNN-based and traditional nonlinear equalizers, with a notable improvement of 2-6 dB in terms of signal-to-noise ratio at a bit error rate (BER) of 10−4 and a reduced mean square error (MSE). Furthermore, the effectiveness of the proposed equalizer was validated using the lake experimental data, demonstrating lower BER and MSE with improved stability. DiscussionThis underscores thepromise of employing the SDFCFLNNE initialized by OCCSSA as a promising solution to enhance the robustness of underwater communication in challenging environments.

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“…To face this issue, Frequency Domain Equalization (FDE) has been proposed [18]- [20], as it allows rather good system performance with lower computational complexity. To further improve the system performance over long channel delay spreads such as encountered in UWA communications, Hybrid Time-Frequency Domain Equalizers (HTFDE) have been considered recently [21]- [24], where the complexity of the time-frequency equalizer is considerably lower than that of the time only equalizer while both techniques have similar system performance.…”

Section: Introductionmentioning

confidence: 99%

Hybrid Turbo Equalization for Faster-than-Nyquist Underwater Communication Systems

Arbi

Geller

2021

OCEANS 2021: San Diego – Porto

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Faster-Than-Nyquist (FTN) signaling is a promising technique to enhance the UnderWater Acoustic (UWA) communications rate. However, the main issue of this technique is Inter-Symbol Interference (ISI) that needs to be tackled efficiently at the receiver side. To face this issue, we propose a new Hybrid Time-Frequency Domain Equalizer (HTDFE) for FTN UWA communication systems. In contrast to the conventional HTDFE, each Frequency Domain Equalizer (FDE) at the multiple output side is followed by a joint phase estimator and feedforwardfeedback Time Domain Equalizer (TDE). Simulations over a real underwater channel show that the proposed algorithm allows a gain in performance compared to the conventional solutions.

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Time-Frequency Domain Turbo Equalization for Single-Carrier Underwater Acoustic Communications

Cited by 14 publications

References 38 publications

Adaptive modulation based on steady-state mean square error for underwater acoustic communication

Adaptive modulation based on steady-state mean square error for underwater acoustic communication

A simplified decision feedback Chebyshev function link neural network with intelligent initialization for underwater acoustic channel equalization

Hybrid Turbo Equalization for Faster-than-Nyquist Underwater Communication Systems

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