The Underwater Wireless Communications Information Technology Essay

Wireless communication technology today has become part of our daily life; the idea of wireless undersea communications may still seem far-fetched. However, research has been active for over a decade on designing the methods for wireless information transmission underwater. The major discoveries of the past decades, has motivated researches to carry out better and efficient ways to enable unexplored applications and to enhance our ability to observe and predict the ocean. The purpose of this paper is to introduce to the readers the basic concepts, architecture, protocols and modems used in underwater wireless communications. The paper also presents the difficulties faced in terms of power management and security, and the latest developments in the underwater wireless industry. Towards the end, we also discuss a wide range of applications of underwater wireless communication.

Index Terms: Underwater Wireless Communication (UWCs), Medium Access Control (MAC), Underwater Acoustic Sensor Networks (UAWSNs).


In last several years, underwater sensor network (UWSN) has found an increasing use in a wide range of applications, such as coastal surveillance systems, environmental research, autonomous underwater vehicle (AUV) operation, many civilian and military applications such as oceanographic data collection, scientific ocean sampling, pollution, environmental monitoring, climate recording, offshore exploration, disaster prevention, assisted navigation, distributed tactical surveillance, and mine reconnaissance. By deploying a distributed and scalable sensor network in a 3-dimensional underwater space, each underwater sensor can monitor and detect environmental parameters and events locally. Hence, compared with remote sensing, UWSNs provide a better sensing and surveillance technology to acquire better data to understand the spatial and temporal complexities of underwater environments.

Some of these applications can be supported by underwater acoustic sensor networks (UWASNs), which consist of devices with sensing, processing, and communication capabilities that are deployed to perform collaborative monitoring tasks. Fig 1 gives a generalized diagram of an UWASN. Wireless signal transmission is also crucial to remotely control instruments in ocean observatories and to enable coordination of swarms of autonomous underwater vehicles (AUVs) and robots, which will play the role of mobile nodes in future ocean observation networks by virtue of their flexibility and reconfigurability. Present underwater communication systems involve the transmission of information in the form of sound, electromagnetic (EM), or optical waves. Each of these techniques has advantages and limitations.

Acoustic communication is the most versatile and widely used technique in underwater environments due to the low attenuation (signal reduction) of sound in water. This is especially true in thermally stable, deep water settings. On the other hand, the use of acoustic waves in shallow water can be adversely affected by temperature gradients, surface ambient noise, and multipath propagation due to reflection and refraction. The much slower speed of acoustic propagation in water, about 1500 m/s (meters per second), compared with that of electromagnetic and optical waves, is another limiting factor for efficient communication and networking. Nevertheless, the currently favorable technology for underwater communication is upon acoustics.

On the front of using electromagnetic (EM) waves in radio frequencies, conventional radio

Figure1. Scenario of a UW-ASN composed of underwater and surface vehicles

does not work well in an underwater environment due to the conducting nature of the medium, especially in the case of seawater. However, if EM could be working underwater, even in a short distance, its much faster propagating speed is definitely a great advantage for faster and efficient communication among nodes.

Free-space optical (FSO) waves used as wireless communication carriers are generally limited to very short distances because the severe water absorption at the optical frequency band and strong backscatter from suspending particles. Even the clearest water has 1000 times the attenuation of clear air, and turbid water has more than 100 times the attenuation of the densest fog. Nevertheless, underwater FSO, especially in the blue-green wavelengths, offers a practical choice for high-bandwidth communication (10-150 Mbps, bits per second) over moderate ranges (10-100 meters). This communication range is much needed in harbor inspection, oil-rig maintenance, and linking submarines to land, just name a few of the demands on this front.

In this paper we discuss the physical fundamentals and the implications of using acoustic waves as the wireless communication carrier in underwater environments in Section II, then we discuss an Overview of Routing Protocols for Underwater Wireless Communications in Section III. Section IV we discuss about the two networking architectures of UWSNS. Section V we discuss about acoustic modem technology and will describe Link Quest Inc’s Cutting-Edge Acoustic Modems in detail.. Section VI gives a comparison between ground based sensors with that of a Mobile UWSNs, Section VII we throw some light on the various applications of UWC. And finally we conclude the paper in Section VIII followed by references.

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Among the three types of waves, acoustic waves are used as the primary carrier for underwater wireless communication systems due to the relatively low absorption in underwater environments. We start the discussion with the physical fundamentals and the implications of using acoustic waves as the wireless communication carrier in underwater environments.

Propagation velocity: The extremely slow propagation speed of sound through water is an important factor that differentiates it from electromagnetic propagation. The speed of sound in water depends on the water properties of temperature, salinity and pressure (directly related to the depth). A typical speed of sound in water near the ocean surface is about 1520 m/s, which is more than 4 times faster than the speed of sound in air, but five orders of magnitude smaller than the speed of light. The speed of sound in water increases with increasing water temperature, increasing salinity and increasing depth. Most of the changes in sound speed in the surface ocean are due to the changes in temperature. Approximately, the sound speed increases 4.0 m/s for water temperature arising 1C. When salinity increases 1 practical salinity unit (PSU), the sound speed in water increases 1.4 m/s. As the depth of water (therefore also the pressure) increases 1 km, the sound speed increases roughly 17 m/s. It is noteworthy to point out that the above assessments are only for rough quantitative or qualitative discussions, and the variations in sound speed for a given property are not linear in general.

Fig.2. a vertical profile of sound speed in seawater as the lump-sum function of depth

Absorption: The absorptive energy loss is directly controlled by the material imperfection for the type of physical wave propagating through it. For acoustic waves, this material imperfection is the inelasticity, which converts the wave energy into heat. The absorptive loss for acoustic wave propagation is frequency-dependent, and can be expressed as e®(f)d, where d is the propagation distance and ®(f) is the absorption coefficient at frequency f. For seawater, the absorption coefficient at frequency f in kHz can be written as the sum of chemical relaxation processes and absorption from pure water

where the first term on the right side is the contribution from boric acid, the second term is from the contribution of magnesium sulphate, and the third term is from the contribution of pure water; A1, A2, and A3 are constants; the pressure dependencies are given by parameters P1, P2 and P3; and the relaxation frequencies f1 and f2 are for the relaxation process in boric acid and magnesium sulphate, respectively. Fig. 3 shows the relative contribution from the different sources of absorption as a function of frequency.

Fig.3. Absorption in generic seawater

Multipath: An acoustic wave can reach a certain point through multiple paths. In a shallow water environment, where the transmission distance is larger than the water depth, wave reflections from the surface and the bottom generate multiple arrivals of the same signal. The Fig 4 illustrates the adverse effects of Multipath Propagation. In deep water, it occurs due to ray

Fig 4: Shallow water multipath propagation: in addition to the direct path, the signal propagates via reflections from the surface and bottom.

bending, i.e. the tendency of acoustic waves to travel along the axis of lowest sound speed. The channel response varies in time, and also changes if the receiver moves. Regardless of its origin, multipath propagation creates signal echoes, resulting in intersymbol interference in a digital communication system. While in a cellular radio system multipath spans a few symbol intervals, in an underwater acoustic channel it can spans few tens, or even hundreds of symbol intervals! To avoid the intersymbol interference, a guard time, of length at least equal to the multipath spread, must be inserted between successively transmitted symbols. However, this will reduce the overall symbol rate, which is already limited by the system bandwidth. To maximize the symbol rate, a receiver must be designed to counteract very long intersymbol interference.

Path Loss: Path loss that occurs in an acoustic channel over a distance d is given as A= dka (f) d, where k is the path loss exponent whose value is usually between 1 and 2, and a(f) is the absorption factor that depends on the frequency f. This dependence severely limits the available bandwidth: for example, at distances on the order of 100 km, the available bandwidth is only on the order of 1 kHz. At shorter distances, a larger bandwidth is available, but in practice it is limited by that of the transducer. Also in contrast to the radio systems, an acoustic signal is rarely narrowband, i.e., its bandwidth is not negligible with respect to the center frequency. Within this limited bandwidth, the signal is subject to multipath propagation, which is particularly pronounced on horizontal channels.

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There are several drawbacks with respect to the suitability of the existing terrestrial routing solutions for underwater wireless communications. Routing protocols can be divided into three categories, namely, proactive, reactive, and geographical.

Proactive protocols provoke a large signaling overhead to establish routes for the first time and each time the network topology is modified because of mobility, node failures, or channel state changes because updated topology information must be propagated to all network devices. In this way, each device can establish a path to any other node in the network, which may not be required in underwater networks.

Also, scalability is an important issue for this family of routing schemes. For these reasons, proactive protocols may not be suitable for underwater networks.

Reactive protocols are more appropriate for dynamic environments but incur a higher latency and still require source-initiated flooding of control packets to establish paths. Reactive protocols may be unsuitable for underwater networks because they also cause a high latency in the establishment of paths, which is amplified underwater by the slow propagation of acoustic signals.

Geographical routing protocols are very promising for their scalability feature and limited signaling requirements. However, global positioning system (GPS) radio receivers do not work properly in the underwater environment. Still, underwater sensing devices must estimate their current position, irrespective of the chosen routing approach, to associate the sampled data with their 3D position.


In general, depending on the permanent vs on-demand placement of the sensors, the time constraints imposed by the applications and the volume of data being retrieved, we could roughly classify the aquatic application scenarios into two broad categories: long-term non-time-critical aquatic monitoring and short-term time-critical aquatic exploration.

Fig 5: An illustration of the mobile UWSN architecture for long-term non-time-critical aquatic monitoring applications

Fig. 5 illustrates the mobile UWSN architecture for long-term non-time-critical aquatic monitoring applications. In this type of network, sensor nodes are densely deployed to cover a spacial continuous monitoring area. Data are collected by local sensors, related by intermediate sensors, and finally reach the surface nodes (equipped with both acoustic and RF (Radio Frequency) modems), which can transmit data to the on-shore command center by radio. Since this type of network is designed for long-term monitoring task, then energy saving is a central issue to consider in the protocol design. Moreover, depending on the data sampling frequency, we may need mechanisms to dynamically control the mode of sensors (switching between sleeping modes, wake-up mode, and working mode). In this way, we may save more energy. Further, when sensors are running out of battery, they should be able to pop up to the water surface for recharge, for which a simple air-bladder-like device would suffice.

Clearly, in the mobile UWSNs for long-term aquatic monitoring, localization is a must-do task to locate mobile sensors, since usually only location-aware data is useful in aquatic monitoring. In addition, the sensor location information can be utilized to assist data forwarding since geo-routing proves to be more efficient than pure flooding. Furthermore, location can help to determine if the sensors float crossing the boundary of the interested area.

Fig 6: An illustration of the mobile UWSN architecture for short-term time-critical aquatic exploration applications

In Fig. 6, we show a civilian scenario of the mobile UWSN architecture for short-term time-critical aquatic exploration applications. Assume a ship wreckage & accident investigation team wants to identify the target venue. When the cable is damaged the ROV is out-of-control or not recoverable. In contrast, by deploying a mobile underwater wireless sensor network, as shown in Fig. 2, the investigation team can control the ROV remotely. The self-reconfigurable underwater sensor network tolerates more faults than the existing tethered solution. After investigation, the underwater sensors can be recovered by issuing a command to trigger air-bladder devices. As limited by acoustic physics and coding technology, high data rate networking can only be realized in high-frequency acoustic band in underwater communication. It was demonstrated by empirical implementations that the link bandwidth can reach up to 0.5Mbps at the distance of 60 meters. Such high data rate is suitable to deliver even multimedia data. Compared with the first type of mobile UWSN for long-term non-time-critical aquatic monitoring, the mobile UWSN for short-term time-critical aquatic exploration presents the following differences in the protocol design.

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Real-time data transfer is more of concern

Energy saving becomes a secondary issue.

Localization is not a must-do task.

However, reliable, resilient, and secure data transfer is always a desired advanced feature for both types of mobile UWSNs.


Acoustic modem technology offers two types of modulation/detection: frequency shift keying (FSK) with non-coherent detection and phase-shift keying (PSK) with coherent detection. FSK has traditionally been used for robust acoustic communications at low bit rates (typically on the order of 100 bps). To achieve bandwidth efficiency, i.e. to transmit at a bit rate greater than the available bandwidth, the information must be encoded into the phase or the amplitude of the signal, as it is done in PSK or Quadrature Amplitude Modulation (QAM). The symbol stream modulates the carrier, and the so-obtained signal is transmitted over the channel. To detect this type of signal on a multipath-distorted acoustic channel, a receiver must employ an equalizer whose task is to unravel the intersymbol interference. A block diagram of an adaptive decision-feedback equalizer (DFE) is shown in Figure 7. In this configuration, multiple input signals, obtained

Fig 7: Multichannel adaptive decision-feedback equalizer (DFE) is used for high-speed underwater acoustic communications. It supports any linear modulation format, such as M-ary PSK or M-ary QAM.

from spatially diverse receiving hydrophones, can be used to enhance the system performance. The receiver parameters are optimized to minimize the mean squared error in the detected data stream. After the initial training period, during which a known symbol sequence is transmitted, the equalizer is adjusted adaptively, using the output symbol decisions. An integrated Doppler tracking algorithm enables the equalizer to operate in a mobile scenario. This receiver structure has been used on various types of acoustic channels. Current achievements include transmission at bit rates on the order of one kbps over long ranges (10-100 nautical miles) and several tens of kbps over short ranges (few km) as the highest rates reported to date.

VI Mobile UWSNs and Ground-

Based Sensor Networks

A mobile UWSN is significantly different from any ground-based sensor network in terms of the following aspects:

Communication Method: Electromagnetic waves cannot propagate over a long distance in underwater environments. Therefore, underwater sensor networks have to rely on other physical means, such as acoustic sounds, to transmit signals. Unlike wireless links among ground-based sensors, each underwater wireless link features large latency and low-bandwidth. Due to such distinct network dynamics, communication protocols used in ground-based sensor networks may not be suitable in underwater sensor networks. Specially, low-bandwidth and large-latency usually result in long end-to-end delay, which brings big challenges in reliable data transfer and traffic congestion control. The large latency also significantly affects multiple access protocols. Traditional random access approaches in RF wireless networks might not work efficiently in underwater scenarios.

Node Mobility Most sensor nodes in ground-based sensor networks are typically static, though it is possible to implement interactions between these static sensor nodes and a limit amount of mobile nodes (e.g., mobile data collecting entities like “mules” which may or may not be sensor nodes). In contrast, the majority of underwater sensor nodes, except some fixed nodes equipped on surface-level buoys, are with low or medium mobility due to water current and other underwater activities. From empirical observations, underwater objects may move at the speed of 2-3 knots (or 3-6 kilometers per hour) in a typical underwater condition [2]. Therefore, if a network protocol proposed for ground-based sensor networks does not consider mobility for the majority of sensor nodes, it would likely fail when directly cloned for aquatic applications. Although there have been extensive research in groundbased sensor networks, due to the unique features of mobile UWSNs, new research at almost every level of the protocol suite is required.


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