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The data dissemination in OUSNs differs significantly from those in terrestrial wireless sensor networks, due to the signal irregularity in underwater communications and the limited storage capacity of nodes. To alleviate the storage overflows on nodes and make room for the newly arriving data packets, some stored data packets ought to be actively discarded by nodes. This research begins with the construction of a differential equation set to describe the propagation process of data packets in OUSNs, and the storing-discarding equilibrium is investigated such that each data packet is expected to propagate and disappear during the allowable dissemination time slots. After that, the optimal storing probabilities and discarding probabilities are obtained for the nodes with different in-degrees to maximize the delivery ratio of data packets. Then, we propose an Adaptive Data Dissemination Algorithm (ADDA) for the storage-limited OUSNs with signal irregularity, where at each time slot the newly arriving data packets are stored and the stored data packets are discarded by nodes according to the obtained storing probabilities and discarding probabilities, respectively. Simulation results demonstrate the excellent performance of ADDA, showing that it can enhance the delivery ratio of data packets and reduce the number of storage overflow.

Time-domain synchronous orthogonal frequency division multiplexing (TDS-OFDM) is presented to enhance the spectral and energy efficiency over the conventional cyclic prefix OFDM and zero padding OFDM, but the interbloc interference (IBI) between the data block and adjacent pilot symbols deteriorates its performance. The IBI is considered as the main TDS-OFDM drawback in the harsh long-delay underwater acoustic (UWA) multipath channel. This article proposes a new scheme called X-transform time-domain synchronous index modulation (IM) OFDM to eliminate the TDS-OFDM IBI, explore the multipath diversity, and reduce the peak-to-average power ratio (PAPR). Particularly, X-transform, which merges the discrete Hartley transform and discrete Fourier transform in a very low-complexity unitary matrix, and IM techniques have been employed to remove the effects of IBI existing in underwater acoustic (UWA) TDS-OFDM. Moreover, compressive sensing has been adopted to guarantee a reliable UWA channel estimation based on a guard interval IBI-free region. The proposed scheme is evaluated over simulated and experimental UWA channels. The computer simulation and the real experiment show the outperformance of the proposed scheme in terms of bit error rate, computational complexity, PAPR, energy efficiency, and spectral efficiency over its conventional benchmarks.

The current Internet of Underwater Things (IoUT) for marine observations and emergency responses suffer from two critical issues: energy-efficient and timely data collection. Autonomous underwater vehicles (AUVs), serving as tools for collecting and forwarding distributed data, can deal with the unbalanced power consumption in traditional multihop underwater communication network. However, the low speed of the AUV has not been able to guarantee timeliness of delay-sensitive data. In this paper, we introduce a hybrid data collection scheme (HDCS), taking both real-time data collection and energy efficiency (EE) issues into consideration. All sensor nodes (SNs) are firstly clustered based on their locations in the network. We develop an analytic expression to describe the attenuation of value of information (VoI), involving the relationship between the importance degree and timeliness; initial VoI could be measured by historical data. The emergency can be recognized by the presented criterion, and the transmission mode of cluster heads (CHs) in the same layer is judged by CHs themselves according to VoI. The selected CHs shall transmit the urgent data via multihop routing to avoid over attenuation of VoI. The normal data are collected by AUVs visiting all remaining CHs, and the shortest trajectory is achieved by addressing a variation of the classic traveling salesman problem (TSP). Our simulation experiments show that this mechanism can effectively increase long-term VoI while significantly improving EE.

Intelligent algorithms in artificial intelligence have brought several benefits to digital signal processing. The boom in machine learning and intelligent systems provides new perspectives and methods to solve many research problems in Underwater Acoustic (UWA) Orthogonal Frequency Divisional Multiplexing (OFDM) communication. Partial transmit sequence is a tremendous technique for the mitigation of high Peak-to-Average Power Ratio (PAPR) in OFDM communication systems, but finding the optimum phase factors has still a few problems. In this paper, a Partial Transmit Sequence (PTS) based on an Intelligent Detoxification Function of Liver Algorithm-Partial Transmit Sequence (IDFLA-PTS) is proposed for the mitigation of PAPR in the UWA OFDM communication systems. This algorithm reduces the PAPR and the complexity of the proposed UWA OFDM model. The IDFLA-PTS is also compared with the Genetic Algorithm-Partial Transmit Sequence (GA-PTS). Besides this, the Bit Error Rate (BER) performance of the IDFLA-PTS is shown when a High Power Amplifier (HPA) is used for the BELLHOP channel model. The experimental results of the proposed IDFLA-PTS method achieved nearly optimum results with fair complexity as compared to GA-PTS and boosted the BER performance.

Node localization is one of the major challenges that exist in underwater communication. Various techniques exist for terrestrial networks, while few of them are applicable in underwater networks due to the dynamic characteristic of the underwater channels, e.g., the lack of global positioning system (GPS) coverage under the water surface. Moreover, assorted environmental properties affect almost all employed communication techniques. In this letter, we propose an environmental-aware positioning system by considering the variations of the underwater speed of sound according to the dynamic changes in the physical properties of the seawater, such as temperature, salinity, and pressure, besides the internal waves' effects. The proposed system employs the received signal strength (RSS) technique in estimating the distances between the network nodes. Moreover, we examine the application of various dynamic responses neural networks (NNs) in predicting the underwater node position, such as the feedforward, recurrent, time delay, and distributed delay NNs. The results show that the NN-based prediction models enhance the performance of the positioning system and could achieve small prediction errors in the range of 0.002 for both training and testing patterns.

We describe a new approach to transmitting broadband signals from electrically-small antennas (ESAs), with a focus on lower frequencies where ESA limitations are most pronounced. ESAs traditionally suffer from a stringent tradeoff between bandwidth and efficiency that is caused by a high reactive input impedance. Conventional resonant matching networks can reduce this impedance to improve efficiency, but at the cost of having a narrow operational bandwidth and often a large physical structure. Here, we propose a time-varying matching technique that removes the need for resonant-matching entirely. Our concept is to rapidly vary the conductivity of the antenna in order to prevent reflections from returning to the antenna feed, effectively making the antenna non-reciprocal so that it appears infinitely long and is therefore matched to the characteristic impedance of the surrounding transmission line. An ESA with such a matching scheme would be able to radiate over a wider bandwidth since the matching occurs in the time domain. This technique would be particularly useful for generating VLF/LF waves, which are uniquely suited for many applications such as long-range and underwater communication. We present the theory of operation for such an antenna as well as results from numerical modeling which suggest improved performance over that of a conventional ESA.

This paper proposes a space shift keying (SSK) multiple-input multiple-output (MIMO) system for underwater acoustic communication (UWAC). Designing a competent wireless communication for underwater applications is a rebellious task in terms of energy, cost and channel propagation. SSK is considered in RF communication as a very resourceful technique that promises low energy consumption, high data rate, robustness to channel imperfections, and low receiver computational complexity. As well, SSK is implemented without any acoustic modulation chain while relying mainly on audio de–multiplexer for UWAC, which is very simple and basic component. As such, considering SSK for UWAC is envisaged to provide several benefits that will be explored here. The theoretical error performance of the proposed system is analyzed and corroborated through Monte-Carlo simulation results, while considering a κ-μ shadowed fading channel, which is shown in literature to accurately model underwater acoustic propagation. The impact of different system and channel parameters on the SSK-MIMO system performance is investigated. It is revealed that shadowing reduces channel correlation and enhances system performance assuming fixed signal-to-noise ratio values. As well, the considered SSK-MIMO system is shown to achieve a coverage length of around 10km while maintaining an of 10-4.

The non-line-of-sight (NLOS) underwater communication can offer a viable route in signal propagation and coverage, thus mitigating the pointing, acquisition, and tracking difficulties in line-of-sight optical communication. However, implementing the NLOS link is non-trivial. While the NLOS technique relies on light scattering, i.e., channel turbulence can facilitate NLOS communication, the associated path-loss (PL) can be significant. Signal fading can degrade link robustness, which arises due to ocean water temperature and salinity fluctuation and gradients. To evaluate the robustness of NLOS in natural waters, we systematically measure the link metrics, such as the bit error ratio, PL, and signal-to-noise ratio (SNR), of water bodies of uniform and nonuniform vertical salinity ranging from 30–40‰ (part-per-thousand). We found that salinity-induced turbulence can establish NLOS communication with PL reduction of 2.35 dB/m and SNR increase by 32.5$\%$ for dynamic water. Furthermore, a strong correlation was obtained between the strength of signal fluctuations and the received SNR. Finally, we obtained a Gaussian distribution of the statistical scintillation behavior. These results demonstrated the benefit of using the NLOS regime for underwater wireless sensor networks for aiding designers and engineers.

Recently, cooperative autonomous underwater vehicles (AUVs) have been deployed in application areas such as surveillance and protection of maritime infrastructures for inspection and monitoring purposes. These cooperative methodologies require wireless transmission of data between the different AUVs operating in the underwater environment. Communication over ranges exceeding 100 m exclusively relies on underwater acoustic communication. However, the propagating acoustic waves suffer from several challenges due to the presence of path loss, multi-path propagation, the slow and variant propagation speed, background noise, and Doppler distortion. Since the power supply of the AUVs is limited, communication must be very energy efficient and energy constraints have to be known to be able to plan the mission of AUVs. Due to the difficulties of real experiments, the modeling and simulation of the energy consumption and underwater acoustic communication play an essential role in studying and developing these systems. We provide a modular simulation model for the energy consumption and acoustic underwater communication of AUVs implemented in the network simulator OMNeT++ using the INET framework. More specifically, we extend several INET modules in such a way as to reflect the characteristics of AUVs and underwater communication. We study and analyze the AUVs’ energy consumption and dependence of the message quality on different properties such as those mentioned above.

Purpose Utilization of electromagnetic wave (EMW) sensors in an underwater environment has the potential to increase the data rate compared to acoustic-based sensors because of the ability to use larger signal bandwidth. Nevertheless, EMW signals has the drawback of large signal attenuation in underwater, attributed to the high relative permittivity and conductivity of water compared to the atmosphere, hence employment of wide signal bandwidth is necessary to balance the data rate-attenuation trade-off. The purpose of this paper is to analyze the characteristics of both narrowband and wideband EMW signal propagation underwater and devise a path loss model for both cases. Design/methodology/approach Path loss measurement was conducted using a point-to-point configuration in a laboratory water tank while transmitting narrowband and wideband signals between a pair of wideband underwater antennas. The wideband underwater antennas use buffer-layer structures as the impedance matching layer to optimize the antenna performance when operating underwater. The path loss for narrowband signal was modeled using a multi-layer propagation equation in lossy medium considering losses at the medium boundaries. For the case of the wideband signal, a modified version of the model introducing power integration over bandwidth is adopted. These models were formulated through numerical simulations and verified by measurements. Findings The measured narrowband path loss marked an 80 dB attenuation using 800 MHz at 2 m distance. The proposed narrowband model agrees well with the measurements, with approximately 3 dB modeling error. Utilization of the proposed wideband path loss model resulted in a reduction of the gradient of the path loss curve compared to the case of the narrowband signal. The measured wideband path loss at 2 m distance underwater was approximately −65 dB, which has been shown to enable a working signal-to-noise ratio of 15 dB. This proves the potential of realizing high data rate transmission using the wideband signal. Originality/value The paper proposed a wideband propagation model for an underwater EMW sensor network, using power integration over bandwidth. The effectiveness of using wideband EMW signals in reducing path loss is highlighted, which is seldom discussed in the literature. This result will be of useful reference for using wideband signals in designing a high data rate transmission system in underwater wireless sensor networks, for example, in link budget, performance estimation and parameter design of suitable transmission scheme.

The underwater glider (UG) is a new type of long-endurance marine vehicle that is currently widely used in marine environment surveillance. However, the limited capability of underwater communication and the uncertainty of the marine environment leads to a large deviation between the dead-reckoned trajectory and the real trajectory of UG. Therefore, a localization and navigation method based on ocean current data is proposed in this study. Firstly, the working principle and configuration of UG are illustrated, and the dynamic model is also analyzed. Then, the depth-averaged current is derived with motion parameters of UG, and the ocean current data from the Hybrid Coordinate Ocean Model is also introduced and processed. Meanwhile, to make an accurate localization, the DAC is stratified according to the layer weight extracted from the processed ocean current model to obtain layered DAC (LDAC). Subsequently, because the sample intervals of sensors are asynchronous with LDAC, a new matching algorithm based on sample time difference is presented to match the information of sensors and LDAC. Furthermore, the matched data is applied to localization for accurate dead reckoning. Finally, based on the data collected from two experiments, the LDAC-aided localization method proposed in this paper is compared with other benchmark positioning methods, including dynamic model-aided localization, sea current-aided localization, and acoustic beacon-aided localization methods. The results indicate that the proposed new method achieves better localization performance than other benchmark methods. In addition, the proposed method could be applied to other autonomous vehicles with communication constraints.

This article introduces the latest advancements in the field of Internet of Underwater Things (IoUT) with importance toward the technological aspects for communication and location awareness. The IoUT is composed of underwater devices such as sensor nodes with defined communication and networking protocols. The IoUT framework integrates various marine communication technologies based on acoustic waves, radio waves, optical waves, and magnetic induction. This new framework enables multiple applications, including ocean exploration, assisted navigation, location awareness, and environmental pollution control. Hence, this article provides state-of-the-art communication technologies and consumer electronics aspect for implementing the IoUT network. Furthermore, this article also states the recent advancements in IoUT and its useful applications in the underwater environment. Moreover, we also classify various research requirements and challenges concerning the efficient design and proper implementation of IoUT networks.

In acoustic underwater communication and sonar applications, obstacles inside and outside the line-of-sight (LOS) affect signal propagation. Both reflection and diffraction occur in underwater communication and measurement systems due to these obstacles. To the best of our knowledge, the influence of diffraction and reflection is neither described nor modeled for finite pulses yet. We propose and develop a multipath propagation model for spectral diffraction components and phase information of the received signal based on knife-edge diffraction together with reflections, transmission effects, and backscatter. This paper designs a short range underwater ultrasonic experimental system composed of an ultrasonic transceiver with wideband pulses and advanced spectral signal processing. We evaluate our proposed model with measurements made in a water tank with an obstacle moved between the transmitter and receiver. When the model includes all major propagation components and effects, it achieves an accuracy for localization of 97% of the results in the range of twice the obstacle diameter in our test setup.

Compared with the orthogonal frequency division multiplexing (OFDM) modulation, the orthogonal time frequency space(OTFS) modulation has a lower peak-to-average power ratio. It can effectively resist the time selective fading caused by the Doppler effect and has significant performance advantages over doubly dispersive channels. However, the conventional OTFS linear minimum mean square error (LMMSE) method has a high complexity and is not easy to process in real time. In order to solve this problem, we propose a low-complexity equalization algorithm with infinite norm constraints based on the optimal coordinate reduction. The equalization algorithm not only obtains the optimal solution through a certain number of iterations and avoids direct matrix inversion but also equalizes infinite norm constraints to improve the symbol detection performance gains. At the same time, the OTFS delay-Doppler channel matrix we utilize is sparse and the two-norm squares of each column vector equally reduces the complexity of optimal coordinate descent. Finally, the simulation in the underwater acoustic communication scenario we designed verify the effectiveness of the proposed equalization algorithm. The simulation results show that the performance of the proposed equalization algorithm is close to that of the LMMSE method, while its low complexity is ensured.

The majority of research works on underwater communications have been struggling against the water medium for a long time. Either acoustic, electromagnetic, or optical waves suffer from specific propagation defects in the water. Briefly, acoustic waves suffer from long propagation delay and frequency-selective fading. Electromagnetic waves are susceptible to the significant attenuation in the conductive seawater. Strong absorption and severe Rayleigh scattering make wireless optical communication vulnerable. Therefore, a reliable, long-range (up to kilometer), and high data-rate (up to megabits per second) wireless communication is still unavailable in the underwater environments so far. Fortunately, in the past few decades, massive offshore pipeline networks have been deployed for oil and gas transportation. These pipelines provide a new medium for realizing underwater communications, in which the acoustic wave propagates in the pipe wall (also known as stress wave). This stress wave assisted communication scheme overcomes some drawbacks within the aforementioned modalities. So, in this article, we propose a brand new underwater communication paradigm, namely underwater stress wave communications, which utilizes stress wave and offshore pipeline networks for underwater data transmission. Fundamentally different from the conventional underwater communication schemes, stress wave signals propagate through the solid pipe instead of water. Therefore, underwater stress wave communications exhibit several unique and promising features, including 1) lower latency and higher bandwidth compared with acoustic communications; 2) longer communication range than electromagnetic and optical communications; and 3) nearly deterministic and constant channel conditions. To fully utilize these promising features to establish reliable, secure, and high-data-rate communication links along offshore pipelines, this article investigates the stress wave channel characteristics including path loss, available bandwidth, and channel response. Furthermore, we demonstrated a stress wave communication along a steel pipe both in the air and water, and experiment results indicated the feasibility of stress-wave-based communications.

Efficient and reliable underwater sonar image transmission is increasingly desired for underwater investigation by autonomous underwater vehicles (AUV). However, it is extremely challenging due to the severe interference nature of underwater acoustic channels and the large data size of sonar images. In this paper, we first combine multicarrier modulation techniques with characteristics of compressed sonar image data to improve the transmission performance, where in previous research, image compression and multicarrier modulation were investigated separately. The compressed bitstream of sonar images is regarded as a new type of image with unique frequency characteristic. A non-uniform non-orthogonal multicarrier modulation scheme based on frequency characteristics of compressed sonar image data (F-NNMC) is proposed to meet the requirements of efficient and reliable sonar image transmission. The non-orthogonality between subcarriers improves the spectrum efficiency, and the non-uniform subcarrier structure can carry more effective information of the transmitted compressed data to improve the reliability. The simulation and experiment show that the proposed F-NNMC needs less frequency resource and has better peak signal-to-noise ratio (PSNR), structural similarity (SSIM), as well as lower bit error rate (BER) compared to orthogonal and non-orthogonal modulations.

Despite the fact that the ocean plays a role in everything from the air we breathe to daily weather and climate patterns, we know very little about our ocean. Underwater wireless sensor network (UWSN) is one of the options helping us to discover some domains such as natural assets and underwater resource exploration. However, the acoustic signal is the only suitable option in underwater communication in the absence of radio waves, which face a number of challenges under this environment. To overcome these issues, many routing schemes are introduced by researchers though energy consumption is still a challenge in underwater communication. To overcome the issue of rapid energy consumption, a reliable and energy-efficient routing method is introduced that avoids the redundant forwarding of data; hence, it achieves energy efficiency and eventually prolongs the network lifetime. Simulation results support the claim that the proposed scheme achieves energy efficiency along higher delivery ratio by reducing the data transmission error rate during the routing decisions.

Underwater wireless sensor network transmission leads to higher energy consumption due to propagation distance and high energy loss. Moreover, the acoustic medium of acoustic animals and shadow affects the transmission between the source node and destination node. Some demerits of underwater communication are multipath fading, high path loss, frequent packet drops, limited bandwidth, salinity, pressure, temperature, sink hole and curved paths. These factors affect the network lifetime, packet delivery ratio (PDR), link quality and energy. To overcome these problems, Multilayer Clustering-based Butterfly Optimization Routing (MCBOR) algorithm has been introduced to deliver the data packets to the destination without any loss using the sense of butterflies. The proposed work aims to increase PDR and reduce transmission loss. The performance of the proposed MCBOR is evaluated by comparing its performance with state-of-the-art methods. Based on the evaluation report, the proposed MCBOR gives a packet delivery ratio of 0.98%, end to end delay of 6.3 s, and residual energy of 0.47 J. Thus, MCBOR is proved to be more efficient in PDR and reduces transmission loss.

Matched Field Processing (MFP) is one of the most famous algorithms for source detection and underwater localization. Traditional MFP relies on a match between the received signal at the hydrophone array and a replica signal, which is constructed using Green’s Function, then by scanning the space in range and depth to provide an estimation of source position in shallow water and deep water. Different environment models relying on Green’s function exist for constructing the replica signal; this includes normal modes in a shallow water waveguide, the Lloyd-Mirror Pattern, and the Image model. Using the proposed estimation algorithm, here, an analytical Lloyd-Mirror model is developed based on the reflection from the target surface for a case where a target is located in the source signal propagation path. So, in this paper, a new underwater acoustic target localization algorithm using the generalized Lloyd-Mirror Pattern is presented. This idea is verified using an acoustic data from a 2019 underwater communication trial in Grand Passage, Nova Scotia, Canada.

Many threatened crocodilians are shy and difficult to observe in the wild, limiting the current knowledge of their behaviour and ecology. Although acoustic communication is commonly used by adults ...

Underwater acoustic communication (UAC) modem is an important infrastructure of underwater network construction. In recent years, with the performance improvement of the STM32 processor, the realization of reliable UAC through high-performance STM32 processor is conducive to reduce the system power consumption, cheapen the hardware cost, and ease the development difficulty. In this letter, we propose an embedded UAC system with the STM32H743 processor as the core and the peripheral sending/receiving circuit as the signal conditioning circuit module. The system can support a variety of modulation and demodulation methods, including single/multi-carrier frequency-shift keying and orthogonal frequency division multiplexing. Furthermore, in order to reduce the computational cost of the system, a fast and robust frame synchronization algorithm based on the segmented fast Fourier transform is applied. The sea trials show that the system can realize the reliable UAC transmission of 100 b/s–1 kb/s in the distance of 5–8 km in the shallow water area.

This letter presents a new scheme to solve the issue of high redundant energy in Unique Word Orthogonal Frequency Division Multiplexing (UW-OFDM). The proposed scheme, called Low-Redundant Energy UW-OFDM (LRE-UW-OFDM), is suitable for time-varied harsh channels such as the Underwater Acoustic (UWA) channel were inserting the UW data in the time domain leads to huge redundant energy and a dramatic deterioration in Bit Error Rate (BER) performance. The insertion of UW in the proposed LRE-UW-OFDM is done in frequency domain to be any desired sequences in time domain with constant redundant subcarriers energy regardless of the size and the location of data subcarriers. The proposed scheme is evaluated over a long-delay UWA channel demonstrating its outperformance against conventional schemes in terms of BER and mean symbol energy.

In this article, we present an unmanned aerial vehicle (UAV)-aided ocean monitoring network for remote oceanic data collection, in which monitoring data are transmitted first from battery-powered underwater sensor nodes (USNs) to sea surface sink nodes (SNs) in a data collection cycle using underwater acoustic communication, and then a UAV hovering in air collects all the data from SNs and relays them to a ground base station via wireless communication links. Aiming at maximizing network lifetime, we model the resource allocation, USN-to-SN access, and SN-to-UAV access issues as a mixed-integer nonconvex optimization problem. To efficiently solve it, we decompose the optimization into two stages. The first stage is to minimize time consumption in an SN-to-UAV nonorthogonal multiple access process and we solve it by designing a UAV deployment scheme, a subchannel matching scheme, and a joint power and time allocation scheme, based on which, the second stage is to maximize the residual energies of USNs in USN-to-SN transmissions under a modified frequency-division multiple access strategy in each collection cycle. The second-stage optimization is further decomposed into some similar subproblems, and each of them is considered as a bipartite graph matching problem between USNs and underwater acoustic channels. For each subproblem, we propose improved weight-based matching and bisection-based searching algorithms. Finally, we design a low-complexity iteration algorithm to approximate the optimal solution of the original problem by solving these subproblems. The simulation results validate the effectiveness of our proposals.

As a significant component of ocean exploration, underwater localization has attracted extensive attention in both military and civil fields. Due to its low cost and convenience, underwater wireless sensor networks (UWSNs) is favored by related fields. As an important part of the Internet of Things (IoT), it can strengthen the trinity of land, sea, and air. The location of the underwater sensor node is the foundation of the UWSN application and is one of the research hotspots today. Many relevant research scholars have optimized the localization algorithm or introduced new methods to better locate the target nodes, thus promoting the development of related fields. In this article, the challenges of underwater acoustic communication and underwater positioning, the comparison between UWSNs and terrestrial wireless sensor networks (WSNs), the network structure, routing technology, and localization evaluation criteria are all introduced in detail. Moreover, we survey many cutting-edge underwater localization algorithms based on a new taxonomy (i.e., distance measurement, network scale, and anchor utilization). Moreover, these localization algorithms are compared and analyzed from various aspects. Meanwhile, localization discussion and research prospects are illustrated in this article.

Developing a reliable and robust underwater acoustic communication system is a difficult task, due to the complicated nature of the underwater channel, non-stationary noise, and a number of other factors. Indeed, channel estimation or equalization presents numerous challenges in this non-stationary, highly Doppler, multipath environment; as a result, traditional equalizers and PLL-based methods have limited performance. Generally, communication over such time-varying channels is accomplished via packets that contain a prefix/preamble signal for training, a payload containing the actual data, and a silent period for proper alignment. The prefix signal must be designed properly because it is used to estimate the channel and also to determine the start of packet. This paper proposes a novel prefix signal based on the hyperbolic chirp signal, where its Doppler invariance properties enable the extraction of the entire packet even when Doppler and severe multipath are present. Additionally, this proposed prefix enables an efficient and accurate method for fully characterising an underwater channel. The proposed prefix signal is used to estimate the multipath delay and amplitude, and different Doppler scales. Extensive simulations using various channel models are used to determine the proposed method robustness and efficacy under a wide range of conditions. Additionally, the proposed algorithm has been validated on a real-world channel.

Laser-based optical links offer the possibility of secure, high data rate underwater communication. Challenges include quickly modulating the light, and rapidly and reliably decoding the received s...

In underwater communication, establishing a communication link between the sensor in the sea bed and the surface sinks is a daunting task. Further, the data has to be transmitted with minimum delay and maximum reliability. Therefore, the present study proposes a biobjective routing protocol for underwater wireless sensor networks. The existing protocols are reviewed and it is found that the traditional depth based and vector-based routing protocols are not able to tackle these conflicting objectives and hence suffer transmission failures with high delay. A biobjective optimization of delay and reliability of routes is proposed to obtain pareto-optimal routes employing uninformed search technique and a modified greedy best first search heuristic. Through simulation experiments, it is found that the biobjective protocol performs better than depth based, delay based and reliability-based routing protocols. However, since the biobjective routing problem in underwater wireless sensor networks is known to be NP-hard and dynamic in nature, the computational effort of uninformed search in yielding the exact solutions increases as the network size increases. The modified greedy best first search heuristic is employed to yield sub-optimal routes with less computational effort without compromising on the quality of the solutions and hence suitable for larger networks.

Underwater communication is crucial for subsea engineering. Currently, although a variety of available technologies are available for underwater communication, almost all of them are highly dependent on the conditions of the subsea environment. Hence, underwater communication is still a challenging issue. This article develops a new stress wave communication method that can be implemented along steel pipes for underwater data transmission. In this article, we analyze stress wave propagation along pipelines, and the corresponding channel response shows the features of dispersion and frequency selectivity. Thus, a suitable carrier frequency is then selected and binary phase-shift keying is applied to encode information into the carrier stress wave. The proposed single-input-single-output communication system is implemented on a steel pipe and experiments are conducted both when in air and seawater. Results demonstrate the validity and stability of the proposed method. The communication data rate of the method can reach 1000 b/s with a low bit error rate. The proposed method shows great promise for enabling underwater communication with lower loss and longer range than conventional underwater communication methods.

In fluctuating underwater acoustic (UWA) communication, reducing the interference caused by multi-path propagation is important to get better performance. For this reason, Chirp Spread Spectrum (CSS), which has insensitive Doppler effect and having effective bandwidth, using Linear Frequency Modulation (LFM) waveform was used in UWA communication before. But LFM waveform has high auto-correlation function sidelobes it becomes interference and gets worse performance in reverberation environment. This presentation proposes an UWA communication using Generalized Sinusoidal Frequency Modulation (GSFM) waveform which is generalized form of sinusoidal FM. GSFM waveform usually attains much higher spectral efficiency and lower peak-to-average power ratio than LFM while maintaining same bandwidth and pulse duration. GSFM waveform has various types and we use two GSFM pulses that is a Forward type in time-frequency domain and a time reversing type of Forward type in this presentation. Each type represents binary values '0' and '1', respectively. Each of pulses occupy same band of frequency and each of GSFM pulses have nearly orthogonality. Simulation results in various underwater channel environments with noise will be presented. A Bellhop-based underwater channel model is used for simulation. The proposed method will be analyzed compared to the conventional CSS method with LFM waveform.

In Underwater communication, the main issues are channel variation, propagation delay, and multipath transmission path variation, attenuation of transmitted signal over a long-distance transmission. Even though continental communication is used in many places, underwater communication has recently been adopted in important places. The reason behind it is using audio waves instead of EM wave which has a low data rate. Hence, a novel underwater acoustic OFDM communication is introduced in this paper with the Polar Run Limited encoder (PRLE) scheme and compared with various existing methods. PRLE encodes the data on the transmitter side and at the receiver side with the help of the codebook, the original information is retrieved. The main concept of FWFT is it reduces size and complexity in order to achieve a high-performance UW-OFDM system. The proposed PRL decoding depends on the codebook information, hence the channel state information (CSI) is not needed for UW transmission. The simulation result shows that the BER value is reduced to 78% when compared with CRC followed convolution encoding method and complexity reduced by 21% compared with FFT based transform technique. As a result, this proposed system has achieved a less BER, low SNR, and low complexity system which can improve the MIMO system operation.

Recently, bionic signals have been used to achieve covert underwater acoustic communication (UWAC) with high signal-to-noise ratios (SNRs) over transmission systems. A high SNR allows the attackers to proceed with their mischievous goals and makes transmission systems vulnerable against malicious attacks. In this paper we propose an improved Merkle hash tree based secure scheme that can resist current underwater attacks, i.e., replay attack, fabricated message attack, message-altering attack, and analyst attack. Security analysis is performed to prove that the proposed scheme can resist these types of attacks. Performance evaluations show that the proposed scheme can meet UWAC limitations due to its efficiency regarding energy consumption, communication overhead, and computation cost.

The results of numerical simulation of interferometric processing of hydroacoustic information for two frequency ranges in the case where intense internal waves induce horizontal refraction of waves of a broadband-source field on a stationary path are presented and discussed. Two nonoverlapping spectral-density ranges are formed as a result of double Fourier transform of the interference pattern in the time–frequency domain. Filtering of these ranges and subjecting them to double inverse Fourier transform provides interference patterns of undisturbed and disturbed fields (i.e., patterns in the absence and in the presence of intense internal waves, respectively). The relative error in reconstructing the interference pattern of undisturbed field is estimated. Approaches to adaptation of the obtained results to the problems of underwater acoustic communication are proposed and outlined.

The impact of bubbles on underwater acoustic communication has mostly been studied in environments with strong winds ( $>$ 12 m/s), and it has been found that the main impact is the strong attenuation due to dense bubble clouds. Without continuous replenishment during high winds, these dense bubble clouds dissipate rapidly in a few minutes, along with the strong attenuation. We find that after the dense bubble clouds dissipate, they leave behind a diffused bubble cloud with very small bubbles. The lifetime of this diffused bubble cloud is much longer than that of the dense bubble cloud. The attenuation due to these residual bubbles is small, but they result in an increase in channel variability due to their random motion. Furthermore, because they can be transported by currents to distant locations, we argue that these bubbles have a more persistent impact in many environments, including ones where winds are not very strong, but there are other sources of bubbles (e.g., shipping channels). We give a statistical characterization of the propagation through these bubbles, and show the impact on acoustic communications with experimental data.

With an advent of Underwater sensor networks, underwater communication has reached its new dimension of research. These networks are characterized by the elongated end to end delay, high energy utility and most importantly dynamic network topologies. By incorporating these characteristics, numerous automated routing algorithms has been proposed to achieve the energy efficient and low latency data transmission. But still, short-comings still exists due to the above mentioned characteristics and the most comprehensive routing algorithms are badly desired. In this article, a novel routing scheme based on Q-learning framework and Deep Extreme Learning Machines aided with Adaptive Firefly Routing algorithm to address the above mentioned research constraints including energy efficiency and network unsteadiness in underwater communication , that practices the hybrid combination of reward function and adaptive fireflies to determine the optimal routing mechanism. In this algorithm, traditional q-learning mechanism has been replaced by the powerful q-deep extreme learning mechanism which uses the adaptive reward function for the varying underwater environment and to boost the packet-delivery ratio (PDR) and throughputs. Also the paper uses the powerful firefly aided routing mechanism to achieve the energy efficient data transmission and to avoid the void dilemma problems. The extensive experimentations has been conducted on the proposed algorithm and compared with other state of art schemes such as Q deep q-Learning energy aware routing protocol (DQLER), DELR Protocols and VBF protocols in which the proposed algorithm has outperformed than the compared existing algorithms in terms of complexity, energy consumption , packet delivery ratio and end to end delay.

Impulsive noise significantly deteriorates the performance of orthogonal frequency-division multiplexing (OFDM)-based underwater acoustic (UWA) communication systems. The pulse blanking (PB) based approach can mitigate the impulsive noise. However, it causes inter-carrier interference (ICI) and signal attenuation to the receiver. In this work, we first show that the ICI introduces pronounced non-Gaussianity to the receiver chain and leads to significant performance degradation. We then propose a non-Gaussianity-aware iterative ICI cancelation scheme to mitigate the adverse impacts of PB. A companding transformation scheme is incorporated into the soft symbol computation to alleviate the non-Gaussianity of the log-likelihood ratios (LLRs) caused by the residual ICI and impulsive noise. Simulation results illustrate that the proposed non-Gaussianity-aware iterative receiver achieves significant performance gains over the conventional non-Gaussianity-agnostic one with even lower computational complexity.

Underwater environments create a challenging channel for communications. In this paper, we design a novel receiver system by exploring the machine learning technique--Deep Belief Network (DBN)-- to combat the signal distortion caused by the Doppler effect and multi-path propagation. We evaluate the performance of the proposed receiver system in both simulation experiments and sea trials. Our proposed receiver system comprises of DBN based de-noising and classification of the received signal. First, the received signal is segmented into frames before the each of these frames is individually pre-processed using a novel pixelization algorithm. Then, using the DBN based de-noising algorithm, features are extracted from these frames and used to reconstruct the received signal. Finally, DBN based classification of the reconstructed signal occurs. Our proposed DBN based receiver system does show better performance in channels influenced by the Doppler effect and multi-path propagation with a performance improvement of 13.2dB at $10^{-3}$ Bit Error Rate (BER).

The time-varying multipath introduces major distortions to transmissions in the underwater acoustic communication channel. Channel estimation is often used as one of the central steps to address such distortions in high-rate communication receivers. The focus of this paper is to quantify the impacts of the channel fluctuations on the performance of the least-squares channel estimator. A metric, channel variation ratio (CVR), is defined to describe the rate of fluctuations in the channel impulse responses. Equations are derived to reveal the direct relationships between the CVR and channel estimation performance, which is measured by the channel estimation mean squared error (MSE) and signal prediction error (SPE). The equations show that both the MSE and SPE increase linearly with the CVR. The MSE and SPE metrics both have an error floor for time-varying impulse responses, even with zero ambient noise. It is confirmed that an optimum estimated channel length, achieving the minimum estimation error, exists for time-varying impulse responses. The truncation effects in the channel estimation are also investigated. Experimental data are used to validate the findings.

The traditional channel sounding protocol requires that the whole sounding process must be completed within a coherent time. When the communication delay is close to or greater than the coherent time, the protocol will not work properly. In order to solve this problem, a novel Non-Time-Limited channel sounding protocol is proposed. The proposed channel sounding protocol does not need to guarantee the channel reciprocity, has no limit on the communication delay and has strong multi-relay scalability. At the same time, a relay-assisted security extension mechanism is proposed to prevent the collaborative eavesdropping of the neighboring attackers. Simulation experiments show that the Non-Time-Limited channel sounding protocol can get rid of the influence of channel change speed on key generation, effectively improve key consistency in high-speed mobile scenarios, and still maintain good key agreement rate performance in underwater acoustic communication.

Underwater wireless sensor network (UWSN) is a typical application of wireless network in underwater environment, which mainly uses acoustic communication at present. However, due to the characteristics of high bit error rate, very limited bandwidth and high transmission delay, the data transmission collision of underwater communication is very serious. In order to reduce transmission collision and improve network performance, we propose a collision-free time slot scheduling MAC protocol based on multi-level quorum system for high loaded UWSNs. The proposed protocol can allocate different time slots for nodes in the same collision area, while realize space reuse for nodes in different collision areas. Considering the unbalanced data transmission of each node, a multi-level quorum system algorithm is constructed for fairness, which can allocate time slots on demand according to the data transmission amount of each node. In order to ensure reliable transmission of data, a light weight retransmission mechanism is designed to reduce the impact of long delay on channel duty cycle. Simulation results prove that the proposed MAC protocol can effectively avoid transmission collision, reduce transmission delay, improve system energy efficiency, and have good adaptability for different network topologies.

Underwater acoustic communications (UACs) are demanded in a wide range of marine applications. However, one of the main challenges for UACs is unexpected interferences from nearby acoustic activities, especially dynamic and short-period interferences (called shot interference), which are hard to detect, estimate, and mitigate over time- and frequency-selective acoustic channels. In this article, we propose a novel filter that mitigates the interference effects for both single-carrier and multi-carrier systems without any prior knowledge of the interference. An Adaptive Sliding Window Interference Detection (ASWID) algorithm is developed to detect the location and the number of interfered symbols. Meanwhile, a least trimmed squares (LTS) equalizer is presented for the shot interference estimation and mitigation based on robust regression. The proposed algorithms are evaluated through numerical simulations and real channel measurements. Our results show that the proposed designs can detect and mitigate shot interferences effectively for single-carrier and multi-carrier UAC systems.

Underwater connectivity has been a leading field of study in undersea navigation, deep-sea investigation and autonomous underwater vehicle control (AUVs). Because of the low attenuation (signal reduction) of sound in water, acoustic communication is the most versatile and broadly used tool in underwater network. Factors such as long propagation delay, restricted usable bandwidth, large Doppler range, time-varying channel conditions, pressure and various salinity conditions make the application of the underwater acoustic communication (UWAC) system difficult. Underwater naval monitoring and underwater exploration are the basic uses of Underwater Wireless Sensor Networks (UWSN). The outline of sensor networks has been resurrected into a new age of global physical object tracking with the latest advancement of innovation. This advances in design paved the way for new unopened insider information to be revealed in the area of underwater ecosystems, deep water conditions and discovery of ice sheets. This work provides a proficient packet transmitting technique in a selective frequency to increase the coverage, synchronisation and connectivity between sensor AUVs that are under secluded ocean contour observation. The theoretical model is used to represent the complex dynamics in the sea. Taking into account all the channel properties below the sea, the channel model was created. The AUVs are connected to a cluster-based network and the 3-D location of the AUVs is transmitted using an appropriate depth-based cluster-based routing protocol (DB-CBRP). Through choosing the optimal frequency for the transmission of routing packets, the network's total life is extended with the least delay in routing. As a result of its strength against overly reduced transmission capability and recurrence reuse, the CBRP approach is used to restrict channel impairments. The simulation results of the proposed algorithm reveal that the surveillance AUVs have greater communication, coverage and share their position with each other.

Multiple features can be extracted from time-frequency representation (TFR) of signals for the purpose of acoustic event detection. However, many underwater acoustic signals are formed by multiple events (impulsive and tonal), which generates difficulty on the high-resolution TFR for each component. For the characterization of such different events, we propose an anisotropic chirplet transform to achieve the TFR with high energy concentration. Such transform applies a time-frequency varying Gaussian window to compensate the energy of each component while suppressing unwanted noise. Using a set of directional chirplet ridges from the obtained TFR, a structure-split-merge algorithm is designed to reconstruct a multimodal sparse representation, which provides instantaneous frequency and time features. Specifically, a pulsed-to-tonal ratio, based on these features, is computed to distinguish two acoustic signals. The presented method is validated using shallow water experimental underwater acoustic communication signals, and large sequences of harmonics and pulsed bursts from common whales.

The orbital angular momentum (OAM)-based acoustic vortex (AV) communication has been proven to provide a topological spinning characteristics for data transmission with an improved channel capacity, exhibiting good application prospects in underwater acoustic communications. To improve the accuracy and efficiency of data communication, the spectrum decomposition of OAM modes for OAM-multiplexed AV beams is studied with a simplified structure of single-ring transceiver arrays. The principle of spectrum decomposition for the single-OAM or OAM-multiplexed AV beams is derived based on the phase-coded approach and the orthogonal property of AVs. With the single-ring arrays of 16 transducers and 16 receivers, numerical studies and experimental measurements of eight-OAM-multiplexed AV beams transmitting ASCII codes are conducted. The formation of OAM-multiplexed AV beams is demonstrated by the cross-sectional scanning measurements, and the OAM modes are decoded successfully with a 16-point circular sampling. Compared with the traditional orthogonality-based decoding algorithm, the spectrum decomposition can be realized using a rotational measurement without the multiple premeasurements of single-OAM AV beams. The favorable results demonstrate the feasibility of the spectrum decomposition-based OAM communication for AV beams using a simplified structure of single-ring transceiver arrays, which would facilitate the practical application in underwater communications.

In Underwater Acoustic Sensor Network (UWASN), node redeployment strategy is utilized to handle the reliable network coverage. The sensors deployed in the underwater are used to intellect the area and collected information is moved to the sink node. Node redeployment strategy is essential for the nodes which are placed outside the monitoring area in UWASN. In this paper, the node redeployment strategy is performed based on the hybrid Emperor Penguin Optimization (EPO) algorithm with Particle Search Algorithm (PSO) for better underwater acoustic communication and the proposed method is named as HEPSO. This hybridization is performed to reduce node failure rate and network energy consumption rate by optimally place the sensor nodes in underwater acoustic communication. The stability of the network topology is guaranteed by this algorithm and it enhances the node redeployment strategy by calculating the fitness function for each and every node. The implementation of the proposed algorithm is carried out by the MATLAB platform. The performance parameters like network coverage rate, network connectivity rate, network lifetime, number of nodes outside monitored space and total movement distance of nodes are evaluated and related with current methods like NRBSCT (Node Redeployment Based on Stratified Connected Tree) and MRNR (Moving Redundancy Nodes Redeployment) strategy.

Currently, autonomous underwater vehicles (AUV) are increasingly used to perform tasks related to the maintenance of underwater communications and various underwater production complexes, as well as performing underwater technological operations. To effectively perform these operations, AUV must have high-quality control systems that will ensure their accurate movement both along long spatial trajectories formed during their movement to the objects of work, and when performing complex maneuvers near underwater infrastructure objects. At the same time, the main difficulty that arises in the process of synthesis of AUV control systems is the significant non-linearity of the dynamic models of these control objects, the presence of interactions between their degrees of freedom, as well as the uncertainty and variability of their parameters. In this paper, we propose a method for synthesizing the spatial motion control system of the AUV, which allows us to take into account these negative effects. This system contains two loops. The first loop includes a combined system containing a nonlinear controller to achieve the desired dynamic characteristics of the AUV, when its parameters are equal to the nominal values, and a controller with self-tuning according to the reference model, which provides compensation for an unknown or variable part of the parameters. In this case, the parameters of the controller with the reference model are selected to reduce the possible amplitude of the discontinuous signal for controlling the AUV velocity. The second loop is a non-linear position controller that allows to take into account the dynamic properties of the velocity control loop and the kinematic properties of the AUV. The advantage of the proposed control system in comparison with traditional ones based on PID controllers is a higher control accuracy when moving along complex spatial trajectories, regardless of changes in the AUV parameters. The simulation results confirmed the high efficiency of the synthesized two-loop control system.

In this letter, we proposed an efficient underwater acoustic (UWA) image communication algorithm based on reinforcement learning which can improve the image quality while reduce the energy consumption and time delay in fast time variant UWA channels. In the proposed algorithm, the received image quality and other communication performance parameters are estimated at the sink continuously and then feedback to the sensor by an independent channel in order to avoid bandwidth loss caused by large time delay. At the sensor, the most suitable modulation and coding method is chosen to maximize a special designed value function in order to achieve the best efficient underwater image communication. Sea test results show that the proposed UWA image communication algorithm can reduce the bit-error rate by 3.1 dB, the energy consumption of the sensor by 26.9% and the time delay by 58.2%. The proposed algorithm can also shorten the convergence time by 47.4% compared with the model-free reinforcement learning underwater communication algorithm.

Multi Access Interference (MAI) is the main source limiting the capacity and quality of the Multiple-Input Multiple-Output Orthogonal Frequency Division Multiplexing (MIMO-OFDM) system which fulfills the demand of high-speed transmission rate and high quality of service for future underwater acoustic (UWA) communication. Multi User Detection (MUD) is needed to overcome the performance degradation caused by MAI. In this research, both local and global optimal solutions are obtained in Bionic Binary Spotted Hyena Optimizer (BBSHO) algorithm using the Position Coordinate Vectors (PCVs) of the social behavior of spotted hyenas to achieve MUD. Further, Extremal Optimization (EO) is introduced in BBSHO algorithm to improve the local search ability within the search space. Hence, a hybrid BBSHO algorithm is proposed for achieving MUD at the receiver of the MIMO-OFDM system whose transceiver model in underwater is implemented using BELLHOP simulation system. By MATLAB simulation, it is shown that the Bit Error Rate (BER) performance of the proposed hybrid algorithm outperforms with best optimal solution within the search space towards MUD for Interference to Noise Ratio (INR) at 10 dB, 20 dB, and 40 dB over conventional detectors and metaheuristic approaches such as Binary Spotted Hyena Optimizer (BSHO), Binary Particle Swarm Optimization (BPSO) in the UWA network.

Low-cost, long-endurance navigation is a crucial universal supporting technology for long-range underwater vehicles while entering, exploring, and developing the deep sea. To overcome the limitations of existing navigation systems (e.g., high cost and unsuitability for long-endurance operation), this study proposes a cooperative navigation system based on “light” marine equipment such as wave glider, underwater acoustic communication modem (UACM), and micro-electro-mechanical system (MEMS) sensor. The focus was to resolve the crucial technical problems faced by the above mentioned “light” marine equipment during deep integration. First, the wave glider path planning based on deep reinforcement learning is studied to ensure continuous and reliable information interaction between the wave glider and underwater vehicle. Second, underwater acoustic communication one-way ranging based on a sound velocity profile (SVP) coupling model and a constant gradient SVP fast algorithm is studied to achieve fast and accurate estimation of the horizontal range between the wave glider and underwater vehicle. Finally, UACM-MEMS sensor cooperative navigation based on decision feedback-denoising auto-encoding and adaptive Kalman filter is studied to ensure the accuracy of navigation. Through deep integration of each “light” marine equipment, low-cost, long-endurance cooperative navigation can be realized in the deep sea.

The Underwater Acoustic Channel (UAC) is a time variant channel and its multipath effects create ISI. This is one of the most important obstacles in the UAC channel which reduces the transmission rate. To remove this obstacle, a proper filter has to be designed in the receiver section. In this article, optimal step size for equalizer is computed and compared the results with the known techniques namely Decision Feedback Equalizer with interleave division multiple access (DFE IDMA) and Cyclic Prefix - Orthogonal Frequency Division Multiplexing (CP-OFDM) Equalizer. Channels are modeled using ray tracing methods. The various factors considered are ambient noise, attenuation loss, bottom and surface loss. The overall path loss for channels is computed by summing up the attenuation loss, surface and bottom loss. Simulation results evident that for short range UAC channel, the BER in the order of 10-2 is achieved using proposed methodology with least Eb/No compared to standard DFE method.