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Open AccessArticle

A Traffic-Aware Fair MAC Protocol for Layered Data Collection Oriented Underwater Acoustic Sensor Networks

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Sidan Yang

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Xuan Liu

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Yishan Su

Remote Sens. 2023, 15(6), 1501; https://doi.org/10.3390/rs15061501 - 08 Mar 2023

Viewed by 656

Abstract

Underwater acoustic channels are characterized by long propagation delay, limited available bandwidth and high energy costs. These unique characteristics bring challenges to design media access control (MAC) protocol for underwater acoustic sensor networks (UASNs). Especially in data-collection-oriented UASNs, data generated at underwater nodes [...] Read more.

Underwater acoustic channels are characterized by long propagation delay, limited available bandwidth and high energy costs. These unique characteristics bring challenges to design media access control (MAC) protocol for underwater acoustic sensor networks (UASNs). Especially in data-collection-oriented UASNs, data generated at underwater nodes are transmitted hop-by-hop to the sink node. The traffic loads undertaken by nodes of different depths are different. However, most existing MAC protocols do not consider the traffic load imbalance in data-collection-oriented UASNs, resulting in unfairness in how the nodes transmit their own generated data. In this paper, we propose a novel traffic-aware fair MAC protocol for layered data-collection-oriented UASNs, called TF-MAC. TF-MAC accesses a medium by assigning time slots of different lengths to each layer via different traffic loads to achieve traffic fairness of nodes. To improve throughput and avoid collision in the network, an overlapping time slot division mechanism for different layers and multi-channel allocation scheme within each single layer is employed. Considering the time-varying traffic loads of the nodes, an adaptive packet length algorithm is proposed by taking advantage of the spatial-temporal uncertainty of underwater channels. A sea experiment was conducted to prove the spatial-temporal uncertainty of UASNs, which provides a feasibility basis for the proposed algorithm. Simulation results show that TF-MAC can greatly improve the network performance in terms of throughput, delay, energy consumption, and fairness in the layered data-collection-oriented UASNs. Full article

(This article belongs to the Special Issue Underwater Communication and Networking)

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Open AccessArticle

A Single-Hydrophone Coherent-Processing Method for Line-Spectrum Enhancement

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Remote Sens. 2023, 15(3), 659; https://doi.org/10.3390/rs15030659 - 22 Jan 2023

Viewed by 640

Abstract

Improving the line-spectrum detection capability of a single hydrophone is of great significance for the passive detection of small underwater platforms. In this paper, we propose a single-hydrophone cross-power spectrum (SHCS) method based on time-domain coherence. This method uses the coherence of the [...] Read more.

Improving the line-spectrum detection capability of a single hydrophone is of great significance for the passive detection of small underwater platforms. In this paper, we propose a single-hydrophone cross-power spectrum (SHCS) method based on time-domain coherence. This method uses the coherence of the line spectrum and the non-coherence of the continuous spectrum noise to obtain coherent gain and improve the signal-to-noise ratio (SNR) of the line spectrum. The effects of the input SNR, number of averaging operations, and overlap ratio on the performance of the SHCS method under a background of Gaussian white noise are simulated and analyzed. The results show that when the overlap ratio is 0 and the number of averaging operations reaches saturation, the SHCS method can achieve the best performance and about 15 dB coherence gain is obtained. The performance of the SHCS method was verified by sea experiments. Under the extremely low input SNR, in which the line spectrum was almost completely submerged in the marine environmental noise, the SHCS method can obtain about 10 dB coherence gain. Under the conventional input SNR, in which the line spectrum could be observed, the SHCS method can obtain about 13 dB coherence gain. The results of processing the radiated noise from an actual cargo ship also demonstrate the effectiveness of the SHCS method. Full article

(This article belongs to the Special Issue Underwater Communication and Networking)

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Open AccessArticle

Robust Underwater Direction-of-Arrival Tracking Based on AI-Aided Variational Bayesian Extended Kalman Filter

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Remote Sens. 2023, 15(2), 420; https://doi.org/10.3390/rs15020420 - 10 Jan 2023

Cited by 1 | Viewed by 656

Abstract

The AI-aided variational Bayesian extended Kalman filter (AI-VBEKF)-based robust direction-of-arrival (DOA) technique is proposed to make reliable estimations of the bearing angle of an uncooperative underwater target with uncertain environment noise. Considering that the large error of the guess of the initial mean [...] Read more.

The AI-aided variational Bayesian extended Kalman filter (AI-VBEKF)-based robust direction-of-arrival (DOA) technique is proposed to make reliable estimations of the bearing angle of an uncooperative underwater target with uncertain environment noise. Considering that the large error of the guess of the initial mean square error matrix (MSEM) will lead to inaccurate DOA tracking results, an attention-based deep convolutional neural network is first proposed to make reliable estimations of the initial MSEM. Then, by utilizing the AI-VBEKF estimating scheme, the uncertain measurement noise caused by the unknown underwater environment along with the bearing angle of the target can be estimated simultaneously to provide reliable results at every DOA tracking step. The proposed technique is demonstrated and verified by both of the simulations and the real sea trial data from the South China Sea in July 2021, and both the robustness and accuracy are proven superior to the traditional DOA-estimating methods. Full article

(This article belongs to the Special Issue Underwater Communication and Networking)

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Open AccessArticle

Multi-Node Joint Power Allocation Algorithm Based on Hierarchical Game Learning in Underwater Acoustic Sensor Networks

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Remote Sens. 2022, 14(24), 6215; https://doi.org/10.3390/rs14246215 - 08 Dec 2022

Cited by 1 | Viewed by 1026

Abstract

In order to improve the overall service quality of the network and reduce the level of network interference, power allocation has become one of the research focuses in the field of underwater acoustic communication in recent years. Aiming at the issue of power [...] Read more.

In order to improve the overall service quality of the network and reduce the level of network interference, power allocation has become one of the research focuses in the field of underwater acoustic communication in recent years. Aiming at the issue of power allocation when channel information is difficult to obtain in complex underwater acoustic communication networks, a completely distributed game learning algorithm is proposed that does not require any prior channel information and direct information exchange between nodes. Specifically, the power allocation problem is constructed as a multi-node multi-armed bandit (MAB) game model. Then, considering nodes as agents and multi-node networks as multi-agent networks, a power allocation algorithm based on a softmax-greedy action selection strategy is proposed. In order to improve the learning efficiency of the agent, reduce the learning cost, and mine the historical reward information, a learning algorithm based on the two-layer hierarchical game learning (HGL) strategy is further proposed. Finally, the simulation results show that the algorithm not only shows good convergence speed and stability but also can adapt to a harsh and complex network environment and has a certain tolerance for incomplete channel information acquisition. Full article

(This article belongs to the Special Issue Underwater Communication and Networking)

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Open AccessArticle

Adaptive Modulation and Coding for Underwater Acoustic Communications Based on Data-Driven Learning Algorithm

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Remote Sens. 2022, 14(23), 5959; https://doi.org/10.3390/rs14235959 - 24 Nov 2022

Cited by 1 | Viewed by 882

Abstract

With the development of the underwater acoustic (UWA) adaptive communication system, energy-efficient transmission has become a critical topic in underwater acoustic (UWA) communications. Due to the unique characteristics of the underwater environment, the transmitter node will almost always have outdated channel state information [...] Read more.

With the development of the underwater acoustic (UWA) adaptive communication system, energy-efficient transmission has become a critical topic in underwater acoustic (UWA) communications. Due to the unique characteristics of the underwater environment, the transmitter node will almost always have outdated channel state information (CSI), which results in low energy efficiency. In this paper, we take full advantage of bidirectional links and propose an adaptive modulation and coding (AMC) scheme that aims to maximize the long-term energy efficiency of a single link by jointly scheduling the coding rate, modulation order, and transmission power. Considering the complexity characteristics of UWA channels, we proposed a bit error ratio (BER) estimation method based on deep neural networks (DNN). The proposed network could realize channel estimation, feature extraction, and BER estimation by using a fixed pilot of the feedback link. Then, we design a channel classification method based on the estimated BERs of the modulation and coding scheme (MCS) and further model the UWA channels as a finite-state Markov chain (FSMC) with an unknown transition probability. Thus, we formulate the AMC problem as a Markov Decision Process (MDP) and solve it through a reinforcement learning framework. Considering the large state-action pairs, a double deep Q-network (DDQN) based scheme is proposed. Simulation results demonstrate that the proposed AMC scheme outperforms the fixed MCS with a perfect channel information state, and achieves near-optimal energy efficiency. Full article

(This article belongs to the Special Issue Underwater Communication and Networking)

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Open AccessArticle

Research on Co-Channel Interference Cancellation for Underwater Acoustic MIMO Communications

by

Yuehai Zhou

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Feng Tong

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Xiaoyu Yang

Remote Sens. 2022, 14(19), 5049; https://doi.org/10.3390/rs14195049 - 10 Oct 2022

Cited by 1 | Viewed by 820

Abstract

Multiple-input–multiple-output (MIMO) communication systems utilize multiple transmitters to send different pieces of information in parallel. This offers a promising way to communicate at a high data rate over bandwidth-limited underwater acoustic channels. However, underwater acoustic MIMO communication not only suffers from serious inter-symbol [...] Read more.

Multiple-input–multiple-output (MIMO) communication systems utilize multiple transmitters to send different pieces of information in parallel. This offers a promising way to communicate at a high data rate over bandwidth-limited underwater acoustic channels. However, underwater acoustic MIMO communication not only suffers from serious inter-symbol interference, but also critical co-channel interference (CoI), both of which degrade the communication performance. In this paper, we propose a new framework for underwater acoustic MIMO communications. The proposed framework consists of a CoI-cancellation-based channel estimation method and channel-estimation-based decision feedback equalizer (CE-DFE) with CoI cancellation functionalities for underwater acoustic MIMO communication. We introduce a new channel estimation model that projects the received signal to a specific subspace where the interference is free; therefore, the CoI is cancelled. We also introduce a CE-DFE with CoI cancellation by appending some filters from traditional CE-DFE. In addition, the traditional direct adaptive decision feedback equalization (DA-DFE) method and the proposed method are compared in terms of communication performance and computational complexity. Finally, the sea trial experiment demonstrates the effectiveness and merits of the proposed method. The proposed method achieves a more than 1 dB of output SNR over traditional DA-DFE, and is less sensitive to parameters. The proposed method provides a new approach to the design of robust underwater acoustic MODEM. Full article

(This article belongs to the Special Issue Underwater Communication and Networking)

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Open AccessArticle

Adaptive Packet Coding for Reliable Underwater Acoustic Communications

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Remote Sens. 2022, 14(19), 4712; https://doi.org/10.3390/rs14194712 - 21 Sep 2022

Viewed by 632

Abstract

This work investigates adaptive random linear packet coding (RLPC) for reliable underwater acoustic (UWA) communications. Our goal is to minimize the total transmission time of data blocks by adjusting the packet coding rate. We first consider the application of RLPC with the conventional [...] Read more.

This work investigates adaptive random linear packet coding (RLPC) for reliable underwater acoustic (UWA) communications. Our goal is to minimize the total transmission time of data blocks by adjusting the packet coding rate. We first consider the application of RLPC with the conventional automatic repeat request (ARQ) scheme. We dynamically adjust the coding rate to fit the time variations of UWA channels by choosing the optimal number of packets in each transmission. The optimal number of packets in each transmission is obtained based on a dynamic programming (DP) algorithm according to the feedback messages, which contain the number of successfully transmitted packets in the last transmission and the channel state information. Furthermore, considering the long propagation delay of UWA communications, we propose a modified juggling-like ARQ (J-ARQ) for the RLPC scheme, for which the duration of each transmission can be adjusted based on the characteristics of RLPC. A two-step DP algorithm is proposed to find out the optimal solutions for this case. Simulation results show that the proposed schemes can improve the throughput efficiency and reduce the outage probability. Full article

(This article belongs to the Special Issue Underwater Communication and Networking)

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Open AccessArticle

Trajectory Optimization of Autonomous Surface Vehicles with Outliers for Underwater Target Localization

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Remote Sens. 2022, 14(17), 4343; https://doi.org/10.3390/rs14174343 - 01 Sep 2022

Cited by 6 | Viewed by 1160

Abstract

Location awareness is crucial for underwater applications; without it, gathered data would be essentially useless. However, it is impossible to directly determine the location of an underwater target because GPS-reliant methods cannot be utilized in the underwater environment. To this end, the underwater [...] Read more.

Location awareness is crucial for underwater applications; without it, gathered data would be essentially useless. However, it is impossible to directly determine the location of an underwater target because GPS-reliant methods cannot be utilized in the underwater environment. To this end, the underwater target localization technique has become one of the most critical technologies in underwater applications, wherein GPS-equipped autonomous surface vehicles (ASVs) are typically used to assist with localization. It has been proved that, under the assumption of Gaussian noise, an appropriate geometry among ASVs and the underwater target can enhance localization accuracy. Unfortunately, the conclusion may not hold if outliers arise and the closed-form expression of Cramér–Rao lower bound (CRLB) cannot be established. Eventually, it becomes hard to derive the accepted geometry, particularly for the received signal strength (RSS)-based ranging scenario. Therefore, this work optimizes the trajectory of ASVs with RSS-based ranging and in the presence of outliers to optimally estimate the location of an underwater target. The D-optimality criterion is applied in conjunction with the Monte Carlo method to determine the closed-form expression of the function, which then transforms the problem into an optimized framework. Nevertheless, the framework cannot be solved in the absence of the target location. In this case, the paper presents two methodologies to overcome the issue and achieve the optimum configuration without identifying the target location. (1) A min–max strategy that assumes that the target location drops in an uncertain region for a single or two ASVs is proposed; and (2) a two-phase localization approach (TPLA) that calculates the target location at each time slot for three ASVs is developed. Finally, the optimal trajectories of ASVs are constructed by a series of waypoints based on an analytically tractable measurement model in various conditions. Full article

(This article belongs to the Special Issue Underwater Communication and Networking)

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Open AccessArticle

Deep Reinforcement Learning-Based Adaptive Modulation for Underwater Acoustic Communication with Outdated Channel State Information

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Remote Sens. 2022, 14(16), 3947; https://doi.org/10.3390/rs14163947 - 14 Aug 2022

Cited by 4 | Viewed by 1325

Abstract

Underwater acoustic (UWA) adaptive modulation (AM) requires feedback about channel state information (CSI) but the long propagation delays and time-varying features of UWA channels can cause the CSI feedback to be outdated. When the AM mode is selected by outdated CSI, the mismatch [...] Read more.

Underwater acoustic (UWA) adaptive modulation (AM) requires feedback about channel state information (CSI) but the long propagation delays and time-varying features of UWA channels can cause the CSI feedback to be outdated. When the AM mode is selected by outdated CSI, the mismatch between the outdated CSI and the actual CSI during transmission degrades the performance and can even lead to communication failure. Reinforcement learning has the ability to learn the relationships between adaptive systems and the environment. This paper proposes a deep Q-network (DQN)-based AM method for UWA communication that uses a series of outdated CSI as the system input. Our study showed that it could extract channel information and select appropriate modulation modes in the expected channels more effectively than single Q-learning (QL) without needing a deep neural network structure. Furthermore, to mitigate any decision bias that was caused by partial observations of UWA channels, we improved the DQN-based AM by integrating a long short-term memory (LSTM) neural network, named LSTM-DQN-AM. The proposed scheme could enhance the DQN’s ability to remember and process historical input channel information, thus strengthening its relationship mapping ability for state-action pairs and rewards. The pool and sea experimental results demonstrated that the proposed LSTM-DQN-AM outperformed DQN-, QL- and threshold-based AM methods. Full article

(This article belongs to the Special Issue Underwater Communication and Networking)

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Open AccessArticle

Performance Analysis of Relay-Aided NOMA Optical Wireless Communication System in Underwater Turbulence Environment

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Remote Sens. 2022, 14(16), 3894; https://doi.org/10.3390/rs14163894 - 11 Aug 2022

Cited by 2 | Viewed by 883

Abstract

Non-orthogonal multiple access (NOMA) is a promising technology to improve spectrum utilization effectively for underwater optical wireless communications (UOWC). To exploit the benefits of NOMA in a turbulent environment, cooperative transmission has been introduced in the NOMA–UOWC network. The existing studies on NOMA [...] Read more.

Non-orthogonal multiple access (NOMA) is a promising technology to improve spectrum utilization effectively for underwater optical wireless communications (UOWC). To exploit the benefits of NOMA in a turbulent environment, cooperative transmission has been introduced in the NOMA–UOWC network. The existing studies on NOMA suggest that relay selection and power optimization are the main factors affecting system performance. In this paper, a general NOMA node pairing method and two power optimization schemes for NOMA–UOWC are proposed, and both schemes are proven to be strictly quasi-convex. The two optimization schemes are solved by the BFGS algorithm and the particle swarm algorithm, respectively. The effectiveness of the proposed schemes are evaluated by our simulations, and the main factors affecting the relay-aided NOMA performance are derived. Full article

(This article belongs to the Special Issue Underwater Communication and Networking)

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Open AccessArticle

Energy-Efficient Cooperative MIMO Formation for Underwater MI-Assisted Acoustic Wireless Sensor Networks

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Remote Sens. 2022, 14(15), 3641; https://doi.org/10.3390/rs14153641 - 29 Jul 2022

Cited by 1 | Viewed by 758

Abstract

The energy problem has become one of the critical factors limiting the development of underwater wireless sensor networks (UWSNs), and cooperative multiple-input–multiple-output (MIMO) technology has shown advantages in energy saving. However, the design of energy-efficient cooperative MIMO techniques does not consider the actual [...] Read more.

The energy problem has become one of the critical factors limiting the development of underwater wireless sensor networks (UWSNs), and cooperative multiple-input–multiple-output (MIMO) technology has shown advantages in energy saving. However, the design of energy-efficient cooperative MIMO techniques does not consider the actual underwater environment, such as the distribution of nodes. Underwater magnetic induction (MI)-assisted acoustic cooperative MIMO WSNs as a promising scheme in throughput, signal-to-noise ratio (SNR), and connectivity have been demonstrated. In this paper, the potential of the networks to reduce energy consumption is further explored through the joint use of cooperative MIMO and data aggregation, and a cooperative MIMO formation scheme is presented to make the network more energy efficient. For this purpose, we first derive a mathematical model to analyze the energy consumption during data transmission, considering the correlation between data generated by nodes. Based on this model, we proposed a cooperative MIMO size optimization algorithm, which considers the expected transmission distance and transmission power constraints. Moreover, a competitive cooperative MIMO formation algorithm that jointly designs master node (MN) selection and cooperative MIMO size can improve energy efficiency and guarantee the connectivity of underwater nodes and surface base station (BS). Our simulation results confirm that the proposed scheme achieves significant energy savings and prolongs the network lifetime considerably. Full article

(This article belongs to the Special Issue Underwater Communication and Networking)

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Open AccessArticle

A Low-Complexity Underwater Acoustic Coherent Communication System for Small AUV

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Remote Sens. 2022, 14(14), 3405; https://doi.org/10.3390/rs14143405 - 15 Jul 2022

Cited by 5 | Viewed by 1121

Abstract

While underwater acoustic (UWA) communication offers a practical way to establish a wireless link with underwater vehicles, designing a UWA communication system onboard a small autonomous underwater vehicle (AUV) still poses significant challenges. As the adoption of the low-complexity, robust noncoherent communication technology [...] Read more.

While underwater acoustic (UWA) communication offers a practical way to establish a wireless link with underwater vehicles, designing a UWA communication system onboard a small autonomous underwater vehicle (AUV) still poses significant challenges. As the adoption of the low-complexity, robust noncoherent communication technology is limited by low bandwidth efficiency and a low data rate, coherent UWA communication requires Doppler mitigation and channel equalization measures to achieve a relatively high data rate in a moving state. Due to the strict constraints of a small-scale AUV in terms of resources and energy consumption, it is not appropriate to use high-complexity Doppler/multipath compensation technology from the prospect of system implementation. In this paper, an efficient and low-complexity UWA differential binary phase-shift keying (DBPSK) system onboard a small AUV is proposed by simplifying the Doppler and multipath compensation. Specifically, for Doppler, the delay of the adjacent DBPSK symbols is calculated according to the Doppler estimate to facilitate delay-tuning Doppler correction. For multipath, low-complexity LMS channel equalization is incorporated with error correction coding to enable multipath mitigation. With a simple structure and low computational complexity, the proposed scheme facilitates the practical hardware implementation and system integration in the small AUV platform. The numerical simulations are conducted to assess the validity of the proposed scheme under different channel conditions and the effectiveness of the proposed scheme is further verified by two UWA communication field tests, which are performed at a practical shallow water sea and lake, respectively. Full article

(This article belongs to the Special Issue Underwater Communication and Networking)

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Open AccessArticle

A Real-Time Digital Self Interference Cancellation Method for In-Band Full-Duplex Underwater Acoustic Communication Based on Improved VSS-LMS Algorithm

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Remote Sens. 2022, 14(12), 2924; https://doi.org/10.3390/rs14122924 - 18 Jun 2022

Viewed by 1144

Abstract

Theoretically, the spectral efficiency of in-band full-duplex underwater acoustic communications (IBFD-UWAC) is twice that of a half-duplex one. However, the actual achievable spectral efficiency of IBFD-UWAC is determined by the performance of the self-interference cancellation (SIC). In addition, the hostile underwater environment poses [...] Read more.

Theoretically, the spectral efficiency of in-band full-duplex underwater acoustic communications (IBFD-UWAC) is twice that of a half-duplex one. However, the actual achievable spectral efficiency of IBFD-UWAC is determined by the performance of the self-interference cancellation (SIC). In addition, the hostile underwater environment poses a challenge to the tracking performance of the SIC due to its complexity and variability. In this paper, we propose a digital SIC method based on the improved variable step-size least mean square (IVSS-LMS) algorithm where we modify the step-size adjustment criterion in the classical LMS filter and establishes a nonlinear relationship with the Sigmoid function to control the step-size using the instantaneous state error, thus improving the robustness and tracking performance of IVSS-LMS. Hardware-in-loop simulation (HLS) based on Simulink

^{®}

platform verifies the real-time implementability and effectiveness of the proposed IVSS-LMS algorithm. Furthermore, the sea trial results show that the digital SIC method based on the proposed algorithm can be implemented in real-time and the convergence speed, and steady-state performance are significantly improved. Full article

(This article belongs to the Special Issue Underwater Communication and Networking)

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Open AccessArticle

Modulation Mode Recognition Method of Non-Cooperative Underwater Acoustic Communication Signal Based on Spectral Peak Feature Extraction and Random Forest

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Remote Sens. 2022, 14(7), 1603; https://doi.org/10.3390/rs14071603 - 26 Mar 2022

Cited by 2 | Viewed by 1558

Abstract

The modulation mode recognition of non-cooperative underwater acoustic (UWA) communication signal faces great challenges due to the influence of the UWA channel and the demand for efficient recognition. This work proposes a recognition method for UWA orthogonal frequency division multiplexing (OFDM), binary frequency [...] Read more.

The modulation mode recognition of non-cooperative underwater acoustic (UWA) communication signal faces great challenges due to the influence of the UWA channel and the demand for efficient recognition. This work proposes a recognition method for UWA orthogonal frequency division multiplexing (OFDM), binary frequency shift keying (2FSK), four-frequency shift keying (4FSK), and eight-frequency shift keying (8FSK) by using spectral peak feature extraction combined with random forest (RF). First, a new spectral peak feature extraction method is proposed. In this method, pre-processing, waveform optimization, and feature extraction are used to ensure that the extracted feature maintains high robustness in the UWA channel. Then, we designed an RF classifier that can meet the demand for high-efficiency recognition and good performance. Finally, simulation and experimental results verified the feasibility of the recognition method. Full article

(This article belongs to the Special Issue Underwater Communication and Networking)

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Open AccessTechnical Note

Hadamard–Viterbi Joint Soft Decoding for MFSK Underwater Acoustic Communications

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Remote Sens. 2022, 14(23), 6038; https://doi.org/10.3390/rs14236038 - 29 Nov 2022

Viewed by 566

Abstract

Multiple Frequency-Shift Keying (MFSK) has been used widely for underwater acoustic communications due to its low complexity and channel robustness. However, the traditional MFSK has the limitation of a low bit rate compared with coherent acoustic communication. To increase the bit rate, this [...] Read more.

Multiple Frequency-Shift Keying (MFSK) has been used widely for underwater acoustic communications due to its low complexity and channel robustness. However, the traditional MFSK has the limitation of a low bit rate compared with coherent acoustic communication. To increase the bit rate, this study designs a new MFSK with the concept of orthogonal frequency division multiplexing (OFDM). We also adopt a channel-concatenated coding to resist the multipath interference and design the iterative joint decoding. The channel-concatenated coding consists of a Hadamard code and a convolutional code. Correspondingly, the iterative joint decoding uses the Hadamard–Viterbi joint soft decoding framework with a newly designed branch metric, which uses the Hadamard structure. As an important preprocessing link for a received signal, frame synchronization and Doppler compensation are also described in detail in this study. Simulations and experiments are conducted to show the effectiveness of the proposed MFSK underwater acoustic communications. Full article

(This article belongs to the Special Issue Underwater Communication and Networking)

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