OFDM-MIMO receiver performance in underwater MISO networks

Multicarrier code division multiple access (MC-CDMA) can be applied in underwater acoustic communication networks to combat the narrow bandwidth of the underwater acoustic channel and multipath fading. Power control is one of the key technologies for the MC-CDMA communication networks. In this paper, we propose a multi-objective power control scheme based on improved particle swarm optimization (PSO) algorithm for underwater acoustic MC-CDMA communication networks. The distance of different nodes to base station (BS) is not same, which can cause near-far effect. So we propose a fitness function which is consisted of power consumption and SINR (the signal to interference plus noise ratio) on the receiver. The method effective reduces the power consumption of nodes and decreases the near-far effect. Comparing with the scheme without power control, our results show that the proposed power control algorithm can be used in underwater acoustic channel. Not only the power consumption is lower, but also the bit error rate (BER) performances are better.

In the last ten years several simulation studies on Autonomous Underwater Vehicle (AUV) swarm fleet formation have been performed, and some preliminary sea demonstrations of proof-of-concept prototypes were carried out. However, their actual realization is hindered by the challenges imposed by the underwater acoustic channel and the difficulties of keeping track of the vehicles’ positions due to the long latency required by traditional Two-Way Travel-Time (TWTT) ranging measurements, that require a specific signaling, hence limiting the throughput of the underwater network. Although One-Way Travel-Time (OWTT) halves the latency, it requires a high precision oscillator, such as an atomic clock or an oven controlled crystal oscillator (OCXO), to be installed in each modem processing unit: while atomic clocks are still very expensive, OCXO are very power demanding, making their application to underwater acoustic networks not always possible, especially in the case of low cost vehicle swarms.In this paper we present a network protocol stack able to perform ranging and localization within the communication task in underwater acoustic networks, limiting the network overhead. Specifically, new layers have been added to the preexisting DESERT Underwater protocol stack to perform the ranging tasks without compromising the correct operation of the communication network. A ranging layer is placed on top of the Medium Access Control (MAC) scheme, allowing the latter to be changed according to the network topology and requirements. This MAC-agnostic ranging layer is further optimized by adapting the amount of data transmitted according to the channel state, and the ranging entries inserted in the data packets according to the least recent information transmitted, hence minimizing the Age of Information. Simulation results obtained with the DESERT Underwater Framework show how this layer allows all AUVs in the swarm to know their distance from every other node in the network, thus limiting the probability of vehicle collisions and allowing better mission coordination.

The potential of exploiting large propagation delays in underwater acoustic (UWA) networks to maximize the network throughput is established in the recent past. Transmission scheduling strategies have been proposed to take advantage of large propagation delay. Super-TDMA is one among such Medium Access Control (MAC) strategies proposed. It is a form of Time Division Multiple Access (TDMA) protocol in which multiple transmissions are allowed in the same time slot and hence concurrently propagate in the medium. We present the implementation challenges of Super-TDMA on underwater acoustic modems and the experimental results demonstrating interference alignment, the crossing of simultaneously transmitted packets in water, and the time synchronization among the deployed nodes in the network.

This paper investigates the problem of distributed resource management in underwater acoustic communication networks (UACNs) involving multiple transmitters and receivers. In this setting, each transmitter autonomously selects a power allocation strategy based solely on local observations, without reliance on a central controller. Given that the optimization problem incorporating fairness and quality of service (QoS) constraints is non-convex and NP-hard, it is reformulated as a Markov Decision Process (MDP). To address the high complexity of underwater networks and the large state and action spaces, we propose a distributed learning framework based on a multi-agent dueling deep Q-network (MAD3QN). The proposed scheme enables each transmitter to dynamically adjust its transmission power based on local observations by integrating the Jain fairness index, QoS interruption penalty, and energy consumption constraints. Furthermore, by incorporating a dueling network architecture and a neighborhood cooperation mechanism, the learning efficiency is significantly enhanced, leading to a stable and effective resource optimization policy. Simulation results demonstrate that the proposed distributed learning algorithm outperforms existing approaches in terms of convergence speed, network fairness, and communication rate.

Time synchronization is a supporting technology and necessary precondition for underwater acoustic (UWA) networks. Sensation and actuation in UWA networks need coordination across nodes. Under normal circumstances, the deployment of UWA networks is large, and the energy resources are limited. The existing protocols can’t achieve an accuracy high enough and consume overmuch energy, so they could not well adapt to UWA networks yet. Although many protocols are dedicated to improving accuracy, they often work on the perspective of ameliorating the exchanged mechanism of information and ignore the propagation delay with the greatest impact on accuracy that affected by channel quality. In this paper, we propose a fault tolerant time synchronization protocol. It dedicated to enhancing accuracy by improving the processing method of exchanged synchronization messages and enables the synchronization process adapt to unstable channel quality. The simulation results show that the protocol achieves a high accuracy with low energy cost, and as channel quality deteriorates, compared with existing protocols, its accuracy declines flatter and fluctuates in a smaller range.

Given a middle-scale underwater acoustic network, to collect data from the multiple underwater nodes, the surface destination node need to be working on mobile data collection mechanism. In this paper, compared to traditional automatic-repeat-request (ARQ) protocol, we proposed node cooperation (NC) to increase the data collection efficiency for the surface node, utilizing the fact that underwater nodes can overhear the transmission of the others. However, different data collection paths can lead to different data collection efficiency for the middle-scale network when employing NC protocol. For one specific node cooperative underwater acoustic network, the underwater nodes are distributed at random within a circle planar region. As the restriction of underwater transmission power, the planar region is divided into several sub-zones according to different mobile collection paths. And then we present several different data collection path examples and show their data collection efficiency. The numerical results show that the optimal mobile collection path should consider both the cooperative zone and the distribution of the underwater nodes.

Underwater Acoustic Networks and related energy based lifetime enhancement is one of the key domain of research in marine based engineering. A number of algorithms, protocols and approaches are developed so far for effective optimization of acoustic resources still a huge scope of research is there. In this research work, an effective and novel algorithm for energy harvesting is proposed using which the effective lifetime of the network can be enhanced. Using this approach, the solar based energy harvesting and optimization can be done with overall cost reduction.

Underwa ter Acoustic Networks (UANs) have become a focus of interest for emerging scientific research and military applications. Recent work has shown that performance of existing security attacks are sensitive to network topology. In this paper, we utilize the mobility of Autonomous Underwater Vehicles (AUVs) to discover the topology of UANs by monitoring the broadcast patterns of geographic routing protocols. In this way, a mobile attacker can take advantage ofthe geographic information used in UANs to improve attack performance. We evaluate our approach in Aqua-Sim and results show that attack performance of jamming is significantly improved. Index Terms-Underwater Acoustic Networks, Localization, Security, Network Discovery

Underwater acoustic (UWA) networks are a key form of communications for human exploration and activities in the oceanographic space of the earth. A fundamental issue of UWA communications is large propagation delays due to water medium, which has posed a grand challenge in UWA network protocol design. Conventional wisdom of addressing this issue is to live with this disadvantage by inserting a guard interval to introduce immunity to propagation delays. Recent advances in interference alignment (IA) open up a new direction to address this issue and promise a great potential to improve network throughput by exploiting large propagation delays. In this paper, we investigate propagation delay-based IA (PD-IA) in multi-hop UWA networks. We first develop a set of simple constraints to characterize PD-IA feasible region at the physical layer. Based on the set of PD-IA constraints, we develop a distributed PD-IA scheduling algorithm to greedily maximize interference overlapping possibilities in a multi-hop UWA network. Simulation results show that the proposed PD-IA algorithm yields higher throughput than an idealized benchmark algorithm without propagation delays, indicating that large propagation delays are not adversarial but beneficial for network throughput performance.

Simulation forms an important part of the development and empirical evaluation of underwater acoustic network (UAN) protocols. The key feature of a credible network simulation model is a realistic channel model. A common approach to simulating realistic underwater acoustic (UWA) channels is by using specialised beam tracing software such as BELLHOP. However, BELLHOP and similar modeling software typically require knowledge of ocean acoustics and a substantial programming effort from UAN protocol designers to integrate it into their research. This paper is a distilled tutorial on UWA channel modeling with a focus on network simulation, providing a trade-off between the flexibility of low level channel modeling via beam tracing and the convenience of automated channel modeling, e.g. via the World Ocean Simulation System (WOSS). The tutorial is accompanied by our MATLAB simulation code that interfaces with BELLHOP to produce channel data for UAN simulations. As part of the tutorial, we describe two methods of incorporating such channel data into network simulations, including a case study for each of them: 1) directly importing the data as a look-up table, 2) using the data to create a statistical channel model. The primary aim of this paper is to provide a useful learning resource and modeling tool for UAN protocol researchers. Initial insights into the UAN protocol design and performance provided by the statistical channel modeling approach presented in this paper demonstrate its potential as a powerful modeling tool for future UAN research.

Many acoustic channels suffer from interference which is neither narrowband nor impulsive. This relatively long duration partial band interference can be particularly detrimental to system performance. We survey recent work in interference mitigation and orthogonal frequency division multiplexing (OFDM) as background motivation to develop a spatial diversity receiver for use in underwater networks. The network consists of multiple distributed cabled hydrophones that receive data transmitted over a time-varying multipath channel in the presence of partial band interference produced by interfering active sonar signals as well as marine mammal vocalizations. In operational networks, many dropped messages are lost due to partial band interference which corrupts different portions of the received signal depending on the relative position of the interferers, information source and receivers due to the slow speed of propagation.

Underwater acoustic communications systems are significantly challenged by the acoustic propagation characteristics of the underwater environment. There are a wide range of physical processes that impact underwater acoustic communications and the relative importance of these processes are different in different environments. In this paper some relevant propagation phenomena are described in the context of how they impact the development and/or performance of underwater acoustic communications networks. The speed of sound and channel latency, absorption and spreading losses, waveguide effects and multipath, surface scattering, bubbles, and ambient noise are all briefly discussed.

Time synchronization is an important part of any distributed networked embedded system. It is essentially the process of achieving and maintaining common time base among all network nodes of the system. This task is quite challenging for the systems or applications like sensor networks, since these systems are highly resource constrained, yet need to process time-sensitive data in collaborative manner. Though many protocols have been suggested for terrestrial sensor networks (RSB, TPSN, FTSP and LTS) and they perform reasonably well, very few protocols (THSL, Tri-message) have been suggested for the high-latency underwater acoustic networks, since achieving time-synchronization for high-latency networks is even more challenging issue. Here we describe a very simple extension and implementation of Tri-message time synchronization protocol for multi-hop Underwater Acoustic Sensor Network (UASN) on the miniature test-bed setup.

In this chapter, we focus on a novel network architecture, UASN-MG, which has multiple surface gateways for underwater acoustic sensor networks. The surface gateways communicate with each other using surface radio and form a radio network on the water surface. Thus, two networks, an underwater acoustic network formed by underwater sensor nodes and a surface radio network formed by the surface gateways, are involved. Such a network architecture can bring about many benefits such as high throughput and energy efficiency. However, integrating multiple surface gateways into underwater acoustic sensor networks also incurs many new design challenges. In this chapter, we describe this new network architecture and its benefits in detail. Then we discuss the design challenges in this new architecture. Afterwards, three design examples are given, from different perspectives, to illustrate the techniques that cope with these challenges and optimize the network’s performance. Finally, we conclude the chapter with discussions on possible future research directions.

Underwater acoustic sensor networks (UWASNs) is an emerging technology, comprising of sensor nodes and unattended automated vehicles (AUVs), all working in a collaboration to sense various phenomenon, process digital information, store processed data and communicate among each other and base stations. Acoustic propagation in water is characterized by high and variable delays, fading effect, Doppler spread and multi path which in turn lead to a limited bandwidth and high error rates. Also, battery life and storage capacity of nodes is limited. So there is a need of suitable routing protocol that takes all these limitations into consideration and makes communication in underwater networks viable. This is the first attempt to analyze the performance of ad-hoc routing protocols in underwater acoustic network environment. We used performance metrics like packet delivery ratio, average end-to-end delay, throughput, routing overhead and energy consumption of the sensor nodes. AODV, DSDV, DSR and OLSR are compared for their performance at different traffic conditions, number of nodes and depths. By analyzing our simulation results, we found that among the discussed protocols, AODV may be used for denser networks but with less traffic and DSDV is suitable for higher traffic conditions with optimal number of nodes.