**Short-Range Underwater Acoustic Communication Networks**

Gunilla Burrowes and Jamil Y. Khan *The University of Newcastle Australia*

## **1. Introduction**

This chapter discusses the development of a short range acoustic communication channel model and its properties for the design and evaluation of MAC (Medium Access Control) and routing protocols, to support network enabled Autonomous Underwater Vehicles (AUV). The growth of underwater operations has required data communication between various heterogeneous underwater and surface based communication nodes. AUVs are one such node, however, in the future, AUV's will be expected to be deployed in a swarm fashion operating as an ad-hoc sensor network. In this case, the swarm network itself will be developed with homogeneous nodes, that is each being identical, as shown in Figure 1, with the swarm network then interfacing with other fixed underwater communication nodes. The focus of this chapter is on the reliable data communication between AUVs that is essential to exploit the collective behaviour of a swarm network.

A simple 2-dimensional (2D) topology, as shown in Figure 1(b), will be used to investigated swarm based operations of AUVs. The vehicles within the swarm will move together, in a decentralised, self organising, ad-hoc network with all vehicles hovering at the same depth. Figure 1(b) shows the vehicles arranged in a 2D horizontal pattern above the ocean floor

(a) AUV Swarm demonstrating stylised SeaVision©vehicles

(b) 2D AUV Swarm Topology

Fig. 1. Swarm Architecture

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Short-Range Underwater Acoustic Communication Networks 175

a transmitter and a receiver, including any natural motion present in the oceans from waves,

Noise in the ocean is frequency dependent. There are three major contributors to noise underwater: ambient noise which represents the noise in the far field; self noise of the vehicle (considered out of band noise); and intermittent noise sources including noises from biological sources such as snapping shrimp, ice cracking and rain. Ambient noise is therefore the component of noise taken into account in acoustic communication performance calculations. It is characterised as a Gaussian Distribution but it is not white as it does not display a constant power spectral density. For the frequencies of interest for underwater acoustic data communication, from 10 to 100 kHz, the ambient noise value decreases with increasing frequency. Therefore, using higher signal frequencies, which show potential for use in shorter

Short range underwater communication systems have two key advantages over longer range operations; a lower end-to-end delay and a lower signal attenuation. End-to-end propagation at 500 m for example is approximately 0.3 sec which is considerable lower than the 2 sec at 3 km but still critical as a design parameter for shorter range underwater MAC protocols. The lower signal attenuation means potentially lower transmitter power requirements which will result in reduced energy consumption which is critical for AUVs that rely on battery power. Battery recharge or replacement during a mission is difficult and costly. The dynamics associated with attenuation also changes at short range where the spreading component dominates over the absorption component, which means less dependency on temperature, salinity and depth (pressure). This also signifies less emphasis on frequency as the frequency dependent part of attenuation is in the absorption component and thus will allow the use of higher signal frequencies and higher bandwidths at short ranges. This potential needs to be exploited to significantly improve the performance of an underwater swarm network

A significant challenge for data transmission underwater is multipath fading. The effect of multipath fading depends on channel geometry and the presence of various objects in the propagation channel. Multipath's occur due to reflections (predominately in shallow water), refractions and acoustic ducting (deep water channels), which create a number of additional propagation paths, and depending on their relative strengths and delay values can impact on the error rates at the receiver. The bit error is generated as a result of inter symbol interference (ISI) caused by these multipath signals. For very short range single transmitter-receiver systems, there could be some minimisation of multipath signals (Hajenko & Benson, 2010; Waite, 2005). For swarm operations, however, there is potentially a different mix of multipath signals that need to be taken into account, in particular, those generated due to the other

Careful consideration of the physical layer parameters and their appropriate design will help maximise the advantages of a short range communications system that needs to utilise the

The following section will introduce the parameters associated with acoustic data transmission underwater. The underwater data transmission channel characteristics will be presented in Section 3 with a discussion of the advantages and disadvantages of the short range channel. Section 4 will show how these will impact on AUV swarm communications and the development of a short range channel model for the design and evaluation of MAC and routing protocols. This is followed in Section 5 by a discussion of the protocol techniques

limited resources available in an underwater acoustic networking environment.

range communication, will be less vulnerable to the impact of ambient noise.

currents and tides.

communication system.

vehicles in the swarm.

required for AUV swarm network design.

giving the swarm the maximum coverage area at a single depth, while forming a multi-hop communication network. The coverage area will depend on application. For example, the exploration of oil and gas deposits underwater using hydrocarbon sensing would initially require a broad structure scanning a large ocean footprint before narrowing the range between vehicles as the sensing begins to target an area. Thus vehicles may need to work as closely as 10 m with inter-node communication distance extending out to 500 m. These operating distances are substantially shorter than the more traditional operations of submarines and underwater sensor to surface nodes that have generally operated at greater than 1km. Thus, the modelling and equipment development for the communication needs of these operations has focused on longer range data transmission and channel modelling. To exploit the full benefits of short range communication systems it is necessary to study the properties of short range communication channels.

Most AUV development work has concentrated on the vehicles themselves and their operations as a single unit (Dunbabin et al., 2005; Holmes et al., 2005), without giving much attention to the development of the swarm architecture which requires wireless communication networking infrastructure. To develop swarm architectures it is necessary to research effective communication and networking techniques in an underwater environment. Swarm operation has many benefits over single vehicle use. The ability to scan or 'sense' a wider area and to work collaboratively has the potential to vastly improve the efficiency and effectiveness of mission operations. Collaboration within the swarm structure will facilitate improved operations by building on the ability to operate as a team which will result in emergent behaviours that are not exhibited by individual vehicles. A swarm working collaboratively can also help to mitigate the problem of high propagation delay and lack of bandwidth available in underwater communication environments. Swarm topology will facilitate improved communication performance by utilising the inherent spatial diversity that exists in a large structure. For example, information can be transmitted more reliably within a swarm architecture by using multi-hop networking techniques. In such cases, loss of an individual AUV, which can be expected at times in the unforgiving ocean environment, will have less detrimental effect compared to a structure where multiple vehicles operate on their own. (Stojanovic, 2008).

The underwater acoustic communication channel is recognised as one of the harshest environments for data communication, with long range calculations of optimal channel capacity of less than 50kbps for SNR (Signal-to-Nosie Ratio) of 20dB (Stojanovic, 2006) with current modem capacities of less than 10kbps (Walree, 2007). Predictability of the channel is very difficult with the conditions constantly changing due to seasons, weather, and the physical surroundings of sea floor, depth, salinity and temperature. Therefore, it must be recognised that any channel model needs to be adaptable so that the model can simulate the channel dynamics to be able to fully analyse the performance of underwater networks.

In general, the performance of an acoustic communication system underwater is characterised by various losses that are both range and frequency dependent, background noise that is frequency dependent and bandwidth and transmitter power that are both range dependent. The constraints imposed on the performance of a communication system when using an acoustic channel are the high latency due to the slow speed of the acoustic signal propagation, at 0.67 ms/m (compared with RF (Radio Frequency) in air at 3.3 ns/m), and the signal fading properties due to absorption and multipath. Specific constraints on the performance due to the mobility of AUV swarms is the Doppler effect resulting from any relative motion between 2 Will-be-set-by-IN-TECH

giving the swarm the maximum coverage area at a single depth, while forming a multi-hop communication network. The coverage area will depend on application. For example, the exploration of oil and gas deposits underwater using hydrocarbon sensing would initially require a broad structure scanning a large ocean footprint before narrowing the range between vehicles as the sensing begins to target an area. Thus vehicles may need to work as closely as 10 m with inter-node communication distance extending out to 500 m. These operating distances are substantially shorter than the more traditional operations of submarines and underwater sensor to surface nodes that have generally operated at greater than 1km. Thus, the modelling and equipment development for the communication needs of these operations has focused on longer range data transmission and channel modelling. To exploit the full benefits of short range communication systems it is necessary to study the properties of short

Most AUV development work has concentrated on the vehicles themselves and their operations as a single unit (Dunbabin et al., 2005; Holmes et al., 2005), without giving much attention to the development of the swarm architecture which requires wireless communication networking infrastructure. To develop swarm architectures it is necessary to research effective communication and networking techniques in an underwater environment. Swarm operation has many benefits over single vehicle use. The ability to scan or 'sense' a wider area and to work collaboratively has the potential to vastly improve the efficiency and effectiveness of mission operations. Collaboration within the swarm structure will facilitate improved operations by building on the ability to operate as a team which will result in emergent behaviours that are not exhibited by individual vehicles. A swarm working collaboratively can also help to mitigate the problem of high propagation delay and lack of bandwidth available in underwater communication environments. Swarm topology will facilitate improved communication performance by utilising the inherent spatial diversity that exists in a large structure. For example, information can be transmitted more reliably within a swarm architecture by using multi-hop networking techniques. In such cases, loss of an individual AUV, which can be expected at times in the unforgiving ocean environment, will have less detrimental effect compared to a structure where multiple vehicles operate on

The underwater acoustic communication channel is recognised as one of the harshest environments for data communication, with long range calculations of optimal channel capacity of less than 50kbps for SNR (Signal-to-Nosie Ratio) of 20dB (Stojanovic, 2006) with current modem capacities of less than 10kbps (Walree, 2007). Predictability of the channel is very difficult with the conditions constantly changing due to seasons, weather, and the physical surroundings of sea floor, depth, salinity and temperature. Therefore, it must be recognised that any channel model needs to be adaptable so that the model can simulate the channel dynamics to be able to fully analyse the performance of underwater networks. In general, the performance of an acoustic communication system underwater is characterised by various losses that are both range and frequency dependent, background noise that is frequency dependent and bandwidth and transmitter power that are both range dependent. The constraints imposed on the performance of a communication system when using an acoustic channel are the high latency due to the slow speed of the acoustic signal propagation, at 0.67 ms/m (compared with RF (Radio Frequency) in air at 3.3 ns/m), and the signal fading properties due to absorption and multipath. Specific constraints on the performance due to the mobility of AUV swarms is the Doppler effect resulting from any relative motion between

range communication channels.

their own. (Stojanovic, 2008).

a transmitter and a receiver, including any natural motion present in the oceans from waves, currents and tides.

Noise in the ocean is frequency dependent. There are three major contributors to noise underwater: ambient noise which represents the noise in the far field; self noise of the vehicle (considered out of band noise); and intermittent noise sources including noises from biological sources such as snapping shrimp, ice cracking and rain. Ambient noise is therefore the component of noise taken into account in acoustic communication performance calculations. It is characterised as a Gaussian Distribution but it is not white as it does not display a constant power spectral density. For the frequencies of interest for underwater acoustic data communication, from 10 to 100 kHz, the ambient noise value decreases with increasing frequency. Therefore, using higher signal frequencies, which show potential for use in shorter range communication, will be less vulnerable to the impact of ambient noise.

Short range underwater communication systems have two key advantages over longer range operations; a lower end-to-end delay and a lower signal attenuation. End-to-end propagation at 500 m for example is approximately 0.3 sec which is considerable lower than the 2 sec at 3 km but still critical as a design parameter for shorter range underwater MAC protocols. The lower signal attenuation means potentially lower transmitter power requirements which will result in reduced energy consumption which is critical for AUVs that rely on battery power. Battery recharge or replacement during a mission is difficult and costly. The dynamics associated with attenuation also changes at short range where the spreading component dominates over the absorption component, which means less dependency on temperature, salinity and depth (pressure). This also signifies less emphasis on frequency as the frequency dependent part of attenuation is in the absorption component and thus will allow the use of higher signal frequencies and higher bandwidths at short ranges. This potential needs to be exploited to significantly improve the performance of an underwater swarm network communication system.

A significant challenge for data transmission underwater is multipath fading. The effect of multipath fading depends on channel geometry and the presence of various objects in the propagation channel. Multipath's occur due to reflections (predominately in shallow water), refractions and acoustic ducting (deep water channels), which create a number of additional propagation paths, and depending on their relative strengths and delay values can impact on the error rates at the receiver. The bit error is generated as a result of inter symbol interference (ISI) caused by these multipath signals. For very short range single transmitter-receiver systems, there could be some minimisation of multipath signals (Hajenko & Benson, 2010; Waite, 2005). For swarm operations, however, there is potentially a different mix of multipath signals that need to be taken into account, in particular, those generated due to the other vehicles in the swarm.

Careful consideration of the physical layer parameters and their appropriate design will help maximise the advantages of a short range communications system that needs to utilise the limited resources available in an underwater acoustic networking environment.

The following section will introduce the parameters associated with acoustic data transmission underwater. The underwater data transmission channel characteristics will be presented in Section 3 with a discussion of the advantages and disadvantages of the short range channel. Section 4 will show how these will impact on AUV swarm communications and the development of a short range channel model for the design and evaluation of MAC and routing protocols. This is followed in Section 5 by a discussion of the protocol techniques required for AUV swarm network design.

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Short-Range Underwater Acoustic Communication Networks 177

cover longer transmission ranges. For an AUV swarm network, use of the above techniques could be crucial to design an effective underwater network. To develop a multi-node swarm network it is necessary to manage all point to point links using a medium access control (MAC) protocol. In a multi-access communication system like a swarm network a transmission channel is shared by many transceivers in an orderly fashion to transmit data in an interference free mode. Figure 2 shows a point to point communication link with two AUVs. When a network is scaled up to support N number of AUVs then it becomes necessary

PROJECTOR HYDROPHONE

Data Storage/ Reuse

Carrier Signal

Demodu lation

Signal Detection and Amplification

Receiver

Acoustic to Electrical conversion

Transmitter Receiver

Electrical to Acoustic conversion

Range (m)

To control the transmission of data it is necessary to design an effective MAC protocol which can control transmission of information from different AUVs. The design of a MAC protocol in a swarm network could be more complex if a multi-hop communication technique is used. The multi-hop communication technique will allow a scalable network design as well as it can support long distance transmission without the need of high power transmitter and receiver circuits. For example, using a multi-hop communication technique if AUV3 in Figure 1(b) wants to transmit packets to AUV7 then it can potentially use a number of communication paths to transmit packets. Some of the possible paths from AUV3 to AUV7 are: AUV3-AUV2-AUV1-AUV4-AUV7 or AUV3-AUV6-AUV9-AUV8-AUV7. The path selection in a network is controlled by the routing protocols. Optimum routing protocols generally select transmission paths based on a number of factors. However, the main factor used to select an optimum path in a wireless network is the SNR which indicates the quality of a link. Similarly the MAC protocol will use the transmission channel state information to develop an optimum packet access technique. To effectively design these protocols it is necessary to understand the properties of short range underwater channel characteristics. Before moving into the protocol design issues we will first evaluate the short

This section will focus on the parameters of the ocean channel that will affect the acoustic signal propagation from the projector to the hydrophone. There are well established

to control multiple point to point or point to multi-point links.

Power Amplifier

range underwater channel characteristics in the following Sections.

**3. Underwater data transmission channel characteristics**

Receiver

Carrier Signal

Fig. 3. Block Diagram of Projector and Hydrophone

Modula tion

Data Source

## **2. Introduction to acoustic underwater communication network**

The underwater data communication link and networking environment presents a substantially different channel to the RF data communication channel in the terrestrial atmosphere. Figure 2 illustrates a typical underwater environment for data transmission using a single transmitter-receiver pair.

Fig. 2. Underwater Acoustic Environment

A simple schematic of the data transmission scheme involving a projector (transmitter) and a hydrophone (receiver) is presented in Figure 3. The projector takes the collected sensor and navigational data and formats it into packets at the Data Source and this is then modulated with the carrier frequency. The modulated signal is amplified to a level sufficient for signal reception at the receiver. There is an optimum amplification level as there is a trade-off between error free transmission and conservation of battery energy. The acoustic power radiated from the projector as a ratio to the electrical power supplied to it, is the efficiency *ηtx* of the projector and represented by the Electrical to Acoustic conversion block. On the receiver side, the sensitivity of the hydrophone converts the sound pressure that hits the hydrophone to electrical energy, calculated in dB/V. Signal detection, includes amplification and shaping of the input to determine a discernible signal. Here a detection threshold needs to be reached and is evaluated as the ratio of the mean signal power to mean noise power (SNR). The carrier frequency is then supplied for demodulation, before the transmitted data is available for use within the vehicle for either data storage or for input into the vehicles control and navigation requirements.

Underwater data communication links generally support low data rates mainly due to the constraints of the communication channel. The main constraints are the high propagation delay, lower effective SNR and lower bandwidth. The effects of these constraints could be reduced by using short distance links and the use of multi-hop communication techniques to 4 Will-be-set-by-IN-TECH

The underwater data communication link and networking environment presents a substantially different channel to the RF data communication channel in the terrestrial atmosphere. Figure 2 illustrates a typical underwater environment for data transmission using

A simple schematic of the data transmission scheme involving a projector (transmitter) and a hydrophone (receiver) is presented in Figure 3. The projector takes the collected sensor and navigational data and formats it into packets at the Data Source and this is then modulated with the carrier frequency. The modulated signal is amplified to a level sufficient for signal reception at the receiver. There is an optimum amplification level as there is a trade-off between error free transmission and conservation of battery energy. The acoustic power radiated from the projector as a ratio to the electrical power supplied to it, is the efficiency *ηtx* of the projector and represented by the Electrical to Acoustic conversion block. On the receiver side, the sensitivity of the hydrophone converts the sound pressure that hits the hydrophone to electrical energy, calculated in dB/V. Signal detection, includes amplification and shaping of the input to determine a discernible signal. Here a detection threshold needs to be reached and is evaluated as the ratio of the mean signal power to mean noise power (SNR). The carrier frequency is then supplied for demodulation, before the transmitted data is available for use within the vehicle for either data storage or for input into the vehicles control and navigation

Underwater data communication links generally support low data rates mainly due to the constraints of the communication channel. The main constraints are the high propagation delay, lower effective SNR and lower bandwidth. The effects of these constraints could be reduced by using short distance links and the use of multi-hop communication techniques to

**2. Introduction to acoustic underwater communication network**

a single transmitter-receiver pair.

Fig. 2. Underwater Acoustic Environment

requirements.

cover longer transmission ranges. For an AUV swarm network, use of the above techniques could be crucial to design an effective underwater network. To develop a multi-node swarm network it is necessary to manage all point to point links using a medium access control (MAC) protocol. In a multi-access communication system like a swarm network a transmission channel is shared by many transceivers in an orderly fashion to transmit data in an interference free mode. Figure 2 shows a point to point communication link with two AUVs. When a network is scaled up to support N number of AUVs then it becomes necessary to control multiple point to point or point to multi-point links.

Fig. 3. Block Diagram of Projector and Hydrophone

To control the transmission of data it is necessary to design an effective MAC protocol which can control transmission of information from different AUVs. The design of a MAC protocol in a swarm network could be more complex if a multi-hop communication technique is used. The multi-hop communication technique will allow a scalable network design as well as it can support long distance transmission without the need of high power transmitter and receiver circuits. For example, using a multi-hop communication technique if AUV3 in Figure 1(b) wants to transmit packets to AUV7 then it can potentially use a number of communication paths to transmit packets. Some of the possible paths from AUV3 to AUV7 are: AUV3-AUV2-AUV1-AUV4-AUV7 or AUV3-AUV6-AUV9-AUV8-AUV7. The path selection in a network is controlled by the routing protocols. Optimum routing protocols generally select transmission paths based on a number of factors. However, the main factor used to select an optimum path in a wireless network is the SNR which indicates the quality of a link. Similarly the MAC protocol will use the transmission channel state information to develop an optimum packet access technique. To effectively design these protocols it is necessary to understand the properties of short range underwater channel characteristics. Before moving into the protocol design issues we will first evaluate the short range underwater channel characteristics in the following Sections.
