Underwater Acoustic Networks Research Articles

Secure Underwater Distributed Antenna Systems: A Multi-Agent Reinforcement Learning Approach

Dear Editor, Underwater distributed antenna systems (DAS) are stationary infrastructures consisting of multiple geographically distributed antenna elements (DAEs) which are interconnected through high-rate backbone networks [1]. Compared to centralized systems, the DAS could provide a larger coverage area and higher throughput for underwater acoustic (UWA) transmissions. In this work, exploiting the low sound speed in water, a multi-agent reinforcement learning (MARL)-based approach is proposed to secure underwater DAS against eavesdropping at the physical layer. Specifically, the theoretical secrecy rate is firstly derived for time-slotted UWA networks (UWANs) considering the large propagation delays. Furthermore, we investigate the long-term sum secrecy rate optimization problem under the MARL framework, where each DAE learns its optimal transmission strategy online. Simulation results show that the proposed method achieves higher secrecy performance compared to competing benchmark methods.

Adaptive Varying Contention Window MAC Protocol Based on Underwater Acoustic Propagation Delay

Underwater acoustic wave propagation time delay and fluctuations are much greater than radio waves. However, many of the protocols used for underwater acoustic networking and communication are designed according to the principles of terrestrial wireless communication networks, failing to give full consideration to utilizing the underwater acoustic propagation and its time delay variation. For this reason, this paper proposes an adaptive varying contention window MAC (AVCW-MAC) protocol based on propagation delay. The protocol uses AVCW random backoff mechanism to differently set up the contention window (CW) of each node based on the different propagation delays from each underwater sensor node to the cluster head node to improve the channel utilization. In addition, to avoid excessive difference in the CW of each node, the backoff factors <italic xmlns:mml="http://www.w3.org/1998/Math/MathML" xmlns:xlink="http://www.w3.org/1999/xlink">K</i> <sub xmlns:mml="http://www.w3.org/1998/Math/MathML" xmlns:xlink="http://www.w3.org/1999/xlink">1</sub> and <italic xmlns:mml="http://www.w3.org/1998/Math/MathML" xmlns:xlink="http://www.w3.org/1999/xlink">K</i> <sub xmlns:mml="http://www.w3.org/1998/Math/MathML" xmlns:xlink="http://www.w3.org/1999/xlink">2</sub> are introduced in the AVCW random backoff mechanism to improve the fairness of nodes’ accessing the channel. Simulation results show that for the same amount of sensor nodes, the AVCW-MAC protocol have significantly improved network throughput and decreased average end-to-end latency when compared to legacy CW-MAC protocols.

An Efficient Geo-Routing-Aware MAC Protocol Based on OFDM for Underwater Acoustic Networks

Performing an effective Media Access Control (MAC) protocol suffers from strong dependencies between Underwater Acoustic Networks’ upper and lower layers: 1) the network layer frequently uses geo-routing protocols, which do not provide the specific next-hop for MAC protocols, resulting in serious data collisions. 2) in such scenarios with the unknown next-hop, fixed Orthogonal Frequency Division Multiplexing (OFDM) resource does not adapt to the changing environment, and degrades network performance (OFDM is a mature modulation technology in the physical layer). However, there is scant research on MAC protocols considering the network layer and the physical layer simultaneously, to solve data collisions and resource allocation. To this end, we present a cross-layer MAC protocol to integrate Geo-routing protocols and OFDM technology (GO-MAC) at the same time. GO-MAC employs a handshake scheme to allocate optimal communication resources and select the next-hop concurrently. Firstly, we formulate the OFDM resource allocation as a joint optimization problem based on transmission mode, subcarrier spacing, guard interval, and transmission power, to decrease transmission delay and energy consumption. Then a Karush-Kuhn-Tucker conditions based Heuristic algorithm (KKT-H) is proposed to solve this problem. Finally, we consider node congestion and channel quality to assist geo-routing protocols with the next-hop selection, and decrease packet collisions. Simulation results show that our protocol matches geo-routing protocols and OFDM technology better than the state-of-the-art protocols, providing higher end-to-end reliability with lower costs.

Multi-objective Game Learning Algorithm Based on Multi-armed Bandit in Underwater Acoustic Communication Networks

Multi-objective Game Learning Algorithm Based on Multi-armed Bandit in Underwater Acoustic Communication Networks

Adaptive Scheduling MAC Protocol in Underwater Acoustic Broadcast Communications for AUV Formation

With the rapid development of autonomous underwater vehicles (AUVs) and the continuous improvement of marine exploration requirements, AUV formation has emerged as a promising technique for performing underwater tasks with greater flexibility, adaptability, and scalability. To achieve AUV formation control, underwater acoustic communication networks (UACNs) are widely used to support information exchange among AUVs. Considering broadcast communications in fully connected mobile UACNs, existing medium access control (MAC) protocols face severe packet collision risk or low reuse efficiency. To improve the timeliness and reliability of the information exchange among AUVs, we develop an efficient scheduling-based adaptive broadcasting MAC (AB-MAC) protocol. The AB-MAC protocol is incompletely centralized, which can be reflected in two aspects. First, to ensure the consistency of the transmission schedule in the network, the AB-MAC protocol selects a control node for each frame to schedule the transmission of all nodes according to the updated network topology. The slot lengths and transmission sequences are changeable in each frame to avoid packet collisions and minimize frame lengths. Second, to further improve the efficiency and robustness of the protocol, all nodes adaptively adjust their transmission time by integrating the information contained in their previously received control packets and ordinary packets. The transmission scheduling problem is formulated as a combinatorial optimization problem, which can be solved by our proposed improved Genetic Algorithm. Numerical results demonstrate that the AB-MAC protocol not only performs well in terms of network throughput and average update interval but also has a high level of robustness even in low-quality underwater acoustic channels.

A Spatially Fair and Low Conflict Medium Access Control Protocol for Underwater Acoustic Networks

The large propagation delay in underwater acoustic networks results in spatial and temporal uncertainty between communication links. This uncertainty, in turn, leads to problems with spatial unfairness and packet collision in media access control (MAC) solutions. To address these issues, this research paper proposes a spatially fair and low-conflict media access control (SFLC-MAC) protocol. Within the protocol, a contention window spatial fairness adjustment strategy is designed, including random and fair states. Nodes autonomously adjust their contention states based on the perceived network information. Nodes in the fair state increase their listening time to ensure that nodes in the random state can successfully access the channel, thereby overcoming the fairness issues in channel access. A method based on postponing data packet transmission is proposed to avoid collisions between data packets and neighbors’ control packets. By scrutinizing the spatio-temporal constraints pertinent to these conflicts, the exact duration of the delay required for this method is ascertained. Simulation results demonstrate that SFLC-MAC effectively improves network throughput, reduces end-to-end delay, decreases network energy consumption, and enhances channel access fairness among nodes.

Adaptive Relay Selection Strategy in Underwater Acoustic Cooperative Networks: A Hierarchical Adversarial Bandit Learning Approach

Relay selection solutions for underwater acoustic cooperative networks suffer significant performance degradation as they fail to adapt to incomplete information, noisy interference and overwhelming dynamics. To address this challenge, a hierarchical adversarial multi-armed bandit learning framework by proposing an online reward estimation layer is designed to improve adaptive relay decision control. In online reward estimation layer, adaptive Kalman filter estimator is developed to properly handle noisy observation to support accurate reward. Meanwhile, an online predict mechanism is projected for all relays to enrich learning information. Furthermore, based on estimate error variance, an adaptive exploration structure is developed to accelerate the balance between exploration and exploitation. All gathered information are exploited to learn relay quality for the decision-making. Accordingly, we present a Hierarchical Adversarial Bandit Learning (HABL) algorithm to fully exploit the heuristic interaction between the hierarchical framework. HABL integrates reward estimation, information prediction, adaptive exploration and decision making carefully in a holistic algorithm to maximize the learning efficiency. Thereby, the HABL-based relay selection algorithm has higher system throughput and lower communication cost. Further, we rigorously analyze the convergence of HABL algorithm and give its upper bound on the cumulative regret. Finally, extensive simulations elucidate the effectiveness of the HABL.

An On-Demand Scheduling-Based MAC Protocol for UW-WiFi Networks

Underwater Internet-of-Things (UIoT) is an extension of Internet-of-Things technology in underwater. The underwater acoustic network with WiFi architecture (UW-WiFi), as a specific deployment of UIoT, has been proved to be a promising technique for wide-ranging marine applications. However, due to the unique features of underwater acoustic channel, such as long and variable propagation delay, low available bandwidth and high bit error rate, conventional medium access control (MAC) protocols designed for terrestrial WiFi networks need an overhaul to work efficiently for UW-WiFi networks. In consideration of the aforementioned channel features, different demands of nodes to occupy channel resources and the reliability of data transmission, a time sequence-based dynamic on-demand assignment (SDDA) MAC protocol for UW-WiFi networks is proposed in this paper. In SDDA, the collision-free scheduling is integrated with the reservation mechanism, aiming to address the issue of various access requirements of diverse task nodes on channel resources in the UW-WiFi network system. The designed protocol employs propagation delays and the amount of data to be sent by terminal nodes to achieve non-conflict transmissions of control packets and on-demand scheduling of data packets. Additionally, the scheme does not require extra overhead for time synchronization. Comparison simulations demonstrate that SDDA provides considerable benefits in terms of channel utilization, end-to-end delay and packet delivery ratio. At last, the SDDA protocol is implemented and a UW-WiFi network system is set up in the marine environment. The ocean field experiment results agree well with the simulated ones and also verify that the proposed protocol achieve conflict-free on-demand scheduling, fairness among terminal nodes at different ranges and the practicability in actual environments.

Centralized Co-Operative Detection Algorithm Based on Double Thresholds for Underwater Acoustic Networks

Spectrum-sensing algorithms are one of the effective solutions to the problem of the underwater spectrum resource constraint. However, because the underwater acoustic channel is one of the most complex channels, it has many characteristics, such as a limited communication bandwidth, multipath effect, and ocean noise, all of which render the spectrum detection more difficult. As basic spectrum-sensing algorithms, energy detection algorithms are widely used in underwater acoustic communication and radio. However, most of the existing dual-threshold energy detection methods do not judge the signals with energy values between the thresholds or discard them directly. In this paper, a double-threshold centralized co-operative detection algorithm is proposed to solve this problem. In this algorithm, each sensing user makes a judgment independently, and if the historical energy statistics are between the thresholds, the number of sampling points is increased, and the judgment is made again. In the centralized collaborative sensing algorithm, each sensing user’s results are sent to the fusion center, which uses the OR judgment criterion to make decisions. Simulation results show that this algorithm can improve the detection performance and reduce the error rate.

Exploring propagation delay and mobility in underwater acoustic networks

This work investigates the impact of mobility on underwater acoustic communication networks where the propagation delay is comparable to or larger than the packet duration. A new simulator is proposed to implement the acoustic communication timing model when the nodes are mobile or static. Synchronous and asynchronous Medium Access Control (MAC) protocols are employed with ALOHA, TDMA (Time-Division Multiple Access), and Artificial Intelligent (AI) agent nodes. Extensive simulations are conducted to study the throughput of a MAC network where a large number of source nodes transmit to a single sink node. A network of 2–15 source nodes are assumed to be randomly located in a 1500 m cubic space and some of the nodes are moving in random directions at 2–4 m/s speed. The simulation results show that the asynchronous MAC protocols achieve much higher throughput than the synchronous protocols by allowing time slots to be much shorter than the maximum propagation delay among nodes and allowing asynchronous transmission time. High mobility of a few mobile nodes also favors asynchronous protocols and improves the network throughput in a manner similar to an AI agent.

Algorithm Design and Performance Analysis of Target Localization Using Mobile Underwater Acoustic Array Networks

Space-air-ground-sea integrated network, as a promising networking paradigm for the sixth generation (6 G) communications, connects satellite networks, aerial networks, terrestrial networks, and marine networks. As a fundamental application of marine networks, efficient target localization in the ocean is significant for many marine and underwater applications, including oceanic environmental monitoring, subsea resource exploration, and navigation safety. In this paper, to bring more scalability and feasibility of underwater localization, a mobile underwater acoustic array network is utilized to locate underwater moving targets by leveraging linear frequency modulated (LFM) signals. In the mobile underwater acoustic network, one node is constantly broadcasting LFM signals. Based on the reflected signals received by other nodes, a method that jointly utilizes the propagation delay and the Doppler effect is proposed to simultaneously estimate the position and the velocity of the moving target. Specifically, a two-phase iterative algorithm with low computational complexity is designed to improve the estimation accuracy. Closed-form expressions of positioning and velocity estimation error are also presented. Performance evaluation shows that the proposed method clearly outperforms the least squares based approach. Moreover, the estimation accuracy of the proposed method can approach the Cramér-Rao low bound (CRLB) within two iterations. Decently good localization and velocity estimation error performance can be achieved even with an array network formed by a small number of nodes.

IATLR: Improved ACO and TOPSIS-Based Layering Routing Protocol for Underwater Acoustic Networks

Aiming at the challenges of underwater acoustic networks (UANs) such as low bandwidth, long propagation delay, dynamic network topology, and energy limitation, an improved ant colony optimization (IACO) and technique for order preference by similarity to an ideal solution (TOPSIS)-based layering routing (IATLR) protocol for UANs is proposed. In the IATLR protocol, the transfer probability of the ant colony optimization (ACO) is optimized by comprehensively considering multiple factors such as energy consumption, propagation distance, and forwarding angle. Moreover, the ACO is improved and the optimized ACO is combined with the TOPSIS method by using the pheromone concentration of ACO as the decision basis of TOPSIS. Furthermore, the multifactor decision ranking of the TOPSIS method is optimized by the transfer probability of the ACO. Consequently, the best next-hop node is determined. In addition, the energy consumption is balanced through the whole network by the node silence mechanism in the IATLR protocol. Simulation results show that the IATLR protocol has significant advantages compared with the depth-based routing for underwater sensor networks (DBR), layer-based energy-efficient routing (LEER), and depth and distance based layering routing protocol for underwater sensor networks (DDLR) routing protocols in terms of packet delivery rate (PDR), energy consumption, and end-to-end delay (EED). The PDR increases by 5%–30%, the EED decreases by about 1–7 s, and the average energy consumption (AEC) reduces by 0.5–6 J.

Research on Underwater Wireless Acoustic Communication Routing Protocol

Due to the limitation of the communication range of sensor nodes, underwater nodes must transmit data to the water surface through routing mechanism. Therefore, the design of routing algorithm is related to the performance of the network, and the research of routing algorithm is necessary. However, underwater nodes are vulnerable to ocean turbulence and biological factors. The underwater environment is dynamic and complex, which greatly affects the acoustic channel, making the improvement of routing protocol a challenge. These factors lead to problems in underwater acoustic communication network, such as empty nodes, packet delivery rate, energy consumption, delay and other problems, and in the dynamic and complex seawater environment, the performance of acoustic network will be further reduced. This paper introduces some main routing algorithms, such as hollow node awareness algorithm, layer-based routing protocol; Opportunistic routing algorithm; Double-hop routing protocol, etc. These routing algorithms can solve some problems. Simulation shows that they have certain advantages in packet delivery rate, delay, network lifetime, etc.

Space/Frequency-Division-Based Full-Duplex Data Transmission Method for Multihop Underwater Acoustic Communication Networks

Underwater acoustic communication networks (UACNs) have been widely utilized in recent years because of the growing interest in interactive information in the deep ocean. Compared with traditional radio wireless networks, UACNs are characterized by complex and dynamic 3-D network topology and longer signal propagation delay. Therefore, recent studies on UACNs usually apply dynamic routes in data communication to adapt to complex UACN structure. However, the approaches are hardly adequate for UACN scenarios with high-traffic requirements. This is because dynamic routing methods, such as opportunistic routing, usually require external contention costs to control the routing paths, which leads to decreased network throughput. Accordingly, this article focuses on enabling high-speed acoustic communications for underwater application scenarios with high-traffic requirements, and proposes an underwater data transmission method using the multichannel full-duplex (FD) communication technique. The proposed method applies the underwater orthogonal frequency division multiple access (OFDM) technique, that uses collision-free channels to relay data in multihop routes for simultaneous transmission and reception. Unlike the traditional communication methods of UACNs with dynamic routing, the proposed one uses static routes when transporting data over hop-by-hop paths to achieve stable and uninterrupted FD communication. The approach also includes a directional forwarding-based route request method and an elimination-based channel evaluation proposal, which purpose to reduce the overheads from exploring routes and enable collision-free FD communications. The performance analysis of the proposed method is under simulated conditions of high-traffic UACN scenarios, and the results show that it has superior performance compare to the classical underwater data transmission methods.

FL-SDUAN: A Fuzzy Logic-Based Routing Scheme for Software-Defined Underwater Acoustic Networks

In underwater acoustic networks, the accurate estimation of routing weights is NP-hard due to the time-varying environment. Fuzzy logic is a powerful tool for dealing with vague problems. Software-defined networking (SDN) is a promising technology that enables flexible management by decoupling the data plane from the control plane. Inspired by this, we proposed a fuzzy logic-based software-defined routing scheme for underwater acoustic networks (FL-SDUAN). Specifically, we designed a software-defined underwater acoustic network architecture. Based on fuzzy path optimization (FPO-MST) and fuzzy cut-set optimization (FCO-MST), two minimum spanning tree algorithms under different network scales were proposed. In addition, we compared the proposed algorithms to state-of-the-art methods regarding packet delivery rate, end-to-end latency, and throughput in different underwater acoustic network scenarios. Extensive experiments demonstrated that a trade-off between performance and complexity was achieved in our work.

Secret Key Generation From Route Propagation Delays for Underwater Acoustic Networks

With the growing use of underwater acoustic communications and the recent adoption of standards in this field, it is becoming increasingly important to secure messages against eavesdroppers. In this paper, we focus on a physical-layer security solution to generate sequences of random bits (keys) between two devices (Alice and Bob) belonging to an underwater acoustic network (UWAN); the key must remain secret to a passive eavesdropper (Eve) not belonging to the UWAN. Our method is based on measuring the propagation delay of the underwater acoustic channel over multiple hops of the UWAN: this harvests the randomness in the UWAN topology and turns the slow sound propagation in water into an advantage against eavesdropping. Our key generation protocol includes a route discovery handshake, whereby all UWAN devices at intermediate hops accumulate their message processing delays. This enables Alice and Bob to compute the actual propagation delays along each route and to map such information to a sequence of bits. Finally, from these bit sequences, Alice and Bob obtain a secret key. We analyze the performance of the protocol theoretically and assess it via extensive simulations and field experiments.

Direct-Conversion Spectrum Sensor Impaired by Symmetric α-Stable and α-Sub-Gaussian Noises

Spectrum sensing in underwater cognitive acoustic networks or in underwater acoustic sensor networks can be impaired by impulsive noise generated by snapping shrimps. In mathematical analysis or simulations, the amplitude variations of this noise are commonly modeled by the symmetric alpha-stable (SαS) distribution. As an alternative, the alpha-sub-Gaussian (αSG) distribution can model both temporal correlation and amplitude variations. This article assesses the performance of underwater spectrum sensing with a direct-conversion receiver (DCR) under impulsive noise modeled by the SαS and αSG distributions. Several recent test statistics are compared, demonstrating that they have different degrees of robustness against impulsive noise and that the DCR is significantly less sensitive to this noise, compared to the conventional receiver model that does not take into account the influences of hardware characteristics into the performance of spectrum sensing.

A Survey of Sybil Attack Countermeasures in Underwater Sensor and Acoustic Networks

A Survey of Sybil Attack Countermeasures in Underwater Sensor and Acoustic Networks

Autonomous Underwater Vehicle: 5G Network Design and Simulation Based on Mimetic Technique Control System

The Internet of Underwater Things (IoUT) exhibits promising advancement with underwater acoustic wireless network communication (UWSN). Conventionally, IoUT has been utilized for the offshore monitoring and exploration of the environment within the underwater region. The data exchange between the IoUT has been performed with the 5G enabled-communication to establish the connection with the futuristic underwater monitoring. However, the acoustic waves in underwater communication are subjected to longer propagation delay and higher transmission energy. To overcome those issues autonomous underwater vehicle (AUV) is implemented for the data collection and routing based on cluster formation. This paper developed a memetic algorithm-based AUV monitoring system for the underwater environment. The proposed Autonomous 5G Memetic (A5GMEMETIC) model performs the data collection and transmission to increase the USAN performance. The A5GMEMETIC model data collection through the dynamic unaware clustering model minimizes energy consumption. The A5GMemetic optimizes the location of the nodes in the underwater environment for the optimal data path estimation for the data transmission in the network. Simulation analysis is performed comparatively with the proposed A5Gmemetic with the conventional AEDG, DGS, and HAMA models. The comparative analysis expressed that the proposed A5GMeMEMETIC model exhibits the ~12% increased packet delivery ratio (PDR), ~9% reduced delay and ~8% improved network lifetime.

Coverage Enhancement of Underwater Internet of Things Using Multilevel Acoustic Communication Networks

Underwater acoustic communication networks (UACNs) are considered a key enabler to the Underwater Internet of Things (UIoT). UACN is regarded as essential for various marine applications, such as monitoring, exploration, and trading. However, a large part of existing literature disregards the 3-D nature of the underwater communication system. In this article, we propose a <inline-formula xmlns:mml="http://www.w3.org/1998/Math/MathML" xmlns:xlink="http://www.w3.org/1999/xlink"> <tex-math notation="LaTeX">$K$ </tex-math></inline-formula> -tier UACN that acts as a gateway that connects the UIoT with the space–air–ground–sea integrated system (SAGSIS). The proposed network architecture consists of several tiers along the vertical direction with adjustable depths. On the horizontal dimension, the best coverage probability (CP) is computed and maximized by optimizing the densities of surface stations (SSs) in each tier. On the vertical dimension, the depth of each tier is also optimized to minimize intertier interference and maximize overall system performance. Using tools from stochastic geometry, the total CP of the proposed <inline-formula xmlns:mml="http://www.w3.org/1998/Math/MathML" xmlns:xlink="http://www.w3.org/1999/xlink"> <tex-math notation="LaTeX">$K$ </tex-math></inline-formula> -tier network is analyzed. For given spatial distribution of UIoT device’s depth, the best CP can be achieved by optimizing the depths of the transceivers connected to the SSs through a tether. We verify the accuracy of the analysis using Monte Carlo simulations. In addition, we draw multiple useful system-level insights that help optimize the design of underwater 3-D networks based on the given distribution of UIoT device’s depths.