Underwater sensor nodes will find applications in oceanographic data collection, pollution monitoring, o#shore exploration, disaster prevention, assisted navigation and tactical surveillance applications. Moreover, unmanned or autonomous underwater vehicles (UUVs, AUVs), equipped with sensors, will enable the exploration of natural undersea resources and gathering of scientific data in collaborative monitoring missions. Underwater acoustic networking is the enabling technology for these applications. Underwater networks consist of a variable number of sensors and vehicles that are deployed to perform collaborative monitoring tasks over a given area. In this

In this paper we present a novel platform for underwater sensor networks to be used for long-term monitoring of coral reefs and fisheries. The sensor network consists of static and mobile underwater sensor nodes. The nodes communicate point-to-point using a novel high-speed optical communication system integrated into the TinyOS stack, and they broadcast using an acoustic protocol integrated in the TinyOS stack. The nodes have a variety of sensing capabilities, including cameras, water temperature, and pressure. The mobile nodes can locate and hover above the static nodes for data muling, and they can perform network maintenance functions such as deployment, relocation, and recovery. In this paper we describe the hardware and software architecture of this underwater sensor network. We then describe the optical and acoustic networking protocols and present experimental networking and data collected in a pool, in rivers, and in the ocean. Finally, we describe our experiments with mobility for data muling in this network.

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Large-scale mobile Underwater Wireless Sensor Network (UWSN) is a novel networking paradigm to explore aqueous environments. However, the characteristics of mobile UWSNs, such as low communication bandwidth, large propagation delay, floating node mobility, and high error probability, are significantly different from ground-based wireless sensor networks. The novel networking paradigm poses inter-disciplinary challenges that will require new technological solutions. In particular, in this article we adopt a top-down approach to explore the research challenges in mobile UWSN design. Along the layered protocol stack, we roughly go down from the top application layer to the bottom physical layer. At each layer, a set of new design intricacies are studied. The conclusion is that building scalable mobile UWSNs is a challenge that must be answered by inter-disciplinary efforts of acoustic communications, signal processing and mobile acoustic network protocol design.

Underwater Sensor Networks (UWSNs) are significantly different from land-based sensor networks. In UWSNs, the new features: low bandwidth, high latency, high network dynamics, high error probability, and 3-dimensional space, bring big challenges to network protocol design. In this technical report, we tackle one fundamental problem in UWSNs: scalable and energy efficient routing. We propose a novel routing protocol, called vector-based forwarding (VBF) to address these new challenges. VBF is scalable and energy efficient. In VBF, no state information is required on the sensor nodes and only a small fraction of the nodes are involved in routing. Moreover, we develop a localized and distributed self-adaptation algorithm to enhance the performance of VBF. The self-adaptation algorithm allows the nodes to weigh the benefit to forward packets and reduce energy consumption by discarding the low benefit packets. We evaluate the performance of VBF through extensive simulations. Our experiment results show that for networks with small or medium node mobility (2 m/s-10 m/s), VBF can effectively accomplish the goals of energy efficiency, high success of data delivery and low end-to-end delay.

Abstract—Reliable wireless communications often requires accurate knowledge of the underlying multipath channel. This typically involves probing of the channel with a known training waveform and linear processing of the input probe and channel output to estimate the impulse response. Many real-world channels of practical interest tend to exhibit impulse responses characterized by a relatively small number of nonzero channel coefficients. Conventional linear channel estimation strategies, such as the least squares, are ill-suited to fully exploiting the inherent low-dimensionality of these sparse channels. In contrast, this paper proposes sparse channel estimation methods based on convex/linear programming. Quantitative error bounds for the proposed schemes are derived by adapting recent advances from the theory of compressed sensing. The bounds come within a logarithmic factor of the performance of an ideal channel

Undersea observatories connected to shore with fiber-optic cable will provide scientists with long-term measurements from deep-ocean sensors. Proposed regional observatories include NEPTUNE which will traverse a three thousand kilometer path on the Juan de Fuca plate in the North Pacific. The NEPTUNE backbone includes nodes spaced approximately 100 km apart where additional branches may be added, and a variety of sensors supporting different scientific disciplines will located at each node and along the branches. The fiber optic and power cable creates a backbone that easily supports many smaller regions (cells) covered by wireless communication. An acoustic system extends the reach of the observatory in the area around each cell, allowing additional instruments to be added without installing dedicated cables. The utility of the wireless extension is highly dependent upon the range of the link, its energy efficiency and the total capacity of a cell. The objective of this paper is to explore these issues and discuss design, implementation, and performance of the wireless network. I.

The past 30 years have seen a growing interest in underwater acoustic communications because of its applications in marine research, oceanography, marine commercial operations, the offshore oil industry and defense. Continued research over the years has resulted in improved performance and robustness as compared to the initial communication systems. In this paper, we aim to provide an overview of the key developments in point-to-point communication techniques as well as underwater networking protocols since the beginning of this decade. We also provide an insight into some of the open problems and challenges facing researchers in this field in the near future.

In this paper, we investigate the reliable data transport problem in underwater sensor networks. Underwater sensor networks are significantly different from terrestrial sensor networks in two aspects: acoustic channels are used for communication and most sensor nodes are mobile due to water current. These distinctions feature underwater sensor networks with low available bandwidth, large propagation delay, highly dynamic topology, and high error probability, which pose many new challenges for reliable data transport in underwater sensor networks. In this paper, we propose a protocol, called segmented data reliable transport (SDRT), to achieve reliable data transfer in underwater sensor network scenarios. SDRT is essentially a hybrid approach of ARQ and FEC. It adopts efficient erasure codes, random forward-error correction codes transferring encoded packets block by block and hop by hop. Compared with traditional reliable data transport protocols, SDRT can reduce the total number of transmitted packets significantly, improve channel utilization, and simplify protocol management. In addition, we develop a mathematic model to estimate the expected number of packets actually needed in both of the single-receiver and multiple-receiver cases. Based on this model, we can set the block size appropriately to enable SDRT to address the mobile nodes. We conduct simulations to evaluate our model and SDRT. The results show that our model can closely predict the number of packets actually needed, and SDRT is energy efficient, and can achieve high channel utilization. I.

For communication over doubly dispersive channels, we consider the design of multicarrier modulation (MCM) schemes based on time–frequency shifts of prototype pulses. We consider the case where the receiver knows the channel state and the transmitter knows the channel statistics (e.g., delay spread and Doppler spread) but not the channel state. Previous work has examined MCM pulses designed for suppression of inter-symbol/inter-carrier interference (ISI/ICI) subject to orthogonal or biorthogonal constraints. In doubly dispersive channels, however, complete suppression of ISI/ICI is impossible, and the ISI/ICI pattern generated by these (bi)orthogonal schemes can be difficult to equalize, especially when operating at high bandwidth efficiency. We propose a different approach to MCM pulse design, whereby a limited expanse of ISI/ICI is tolerated in modulation/demodulation and treated near-optimally by a downstream equalizer. Specifically, we propose MCM pulse designs that maximize a signal-to-interference-plus-noise ratio (SINR) which suppresses ISI/ICI outside a target pattern. In addition, we propose two low-complexity turbo equalizers, based on minimum mean-squared error and maximum likelihood criteria, respectively, that leverage the structure of the target ISI/ICI pattern. The resulting system exhibits an excellent combination of low complexity, low bit-error rate, and high spectral efficiency.