**3. Underwater data transmission channel characteristics**

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

Communication Networks 7

Short-Range Underwater Acoustic Communication Networks 179

at short range it is likely that spherical spreading will need to be considered which means a higher attenuation value. Spreading loss is a logarithmic relationship with range and its impacts on the signal is most significant at very short range up to approximately 50m as seen in Figure 5(a). At these shorter ranges spreading loss plays a proportionally larger part

The absorption loss is a representation of the energy loss in the form of heat due to the viscous friction and ionic relaxation that occurs as the wave generated by an acoustic signal

More specifically the absorption of sound in seawater is caused by three dominant effects; viscosity (shear and volume) , ionic relaxation of boric acid and magnesium sulphate (*MgSO*4) molecules and the relaxation time. The effect of viscosity is significant at high frequencies above 100 kHz, whereas the ionic relaxation effects of magnesium affect the mid frequency range from 10 kHz up to 100 kHz and boric acid at low frequencies up to a few kHz. In general, the absorption coefficient, *α*, increases with increasing frequency and decreases as depth increases (Domingo, 2008; Sehgal et al., 2009) and is significantly higher in the sea

Extensive measurements of absorption losses over the last half century has lead to several empirical formulae which take into account frequency, salinity, temperature, pH, depth and speed of sound. A popular version is Thorp's expression (Thorp, 1965), Equation 5, which is based on his initial investigations in the 60's and has since been converted into metric units (shown here). It is valid for frequencies from 100Hz to 1MHz and is based on seawater with salinity of 35% ppt, pH of 8, temp of 4◦C and depth of 0 m (atmospheric pressure) which is

Fisher and Simmons (1977) and others (Francois & Garrison, 1982) have since proposed other variations of *α*. In particular, Fisher and Simmons in the late 70's found the effect associated with the relaxation of boric acid on absorption and provided a more detailed form of absorption coefficient *α* in dB/km which varies with frequency, pressure (depth) and temperature (also valid for 100 Hz to 1 MHz with salinity 35% ppt and acidity 8 pH)(Fisher &

> *A*2*P*<sup>2</sup> *f*<sup>2</sup> *f* <sup>2</sup> *f* 2

where d is depth in meters and t is temperature in ◦C. The 'A' coefficients represent the effects of temperature, while the 'P' coefficients represent ocean depth (pressure) and *f*1, *f*<sup>2</sup> represent the relaxation frequencies of Boric acid and (*MgSO*4) molecules. These terms were developed by Fisher and Simmons (1977) and presented more recently by (Domingo, 2008; Sehgal et al.,

*PLabsorption*(*r*, *f*) = 10*log*(*α*(*f*)) ∗ *r dB* (4)

<sup>4100</sup> <sup>+</sup> *<sup>f</sup>* <sup>2</sup> <sup>+</sup> 2.75 <sup>×</sup> <sup>10</sup>−<sup>4</sup> *<sup>f</sup>* <sup>2</sup> <sup>+</sup> 0.0033 *dB*/*km* (5)

<sup>2</sup> <sup>+</sup> *<sup>f</sup>* <sup>2</sup> <sup>+</sup> *<sup>A</sup>*3*P*<sup>3</sup> *<sup>f</sup>* <sup>2</sup> *dB*/*km* (6)

compared with the absorption term (which has a linear relationship with range).

propagates outwards and this loss varies linearly with range as follows:

compared with fresh water due predominately to the ionic relaxation factor.

44 *f* <sup>2</sup>

where r is range in kilometres and *α* is the absorption coefficient.

**3.2.2 Absorption loss**

assumed but not stated by Thorp.

2009).

*<sup>α</sup>*(*f*) = 0.11 *<sup>f</sup>* <sup>2</sup>

<sup>1</sup> <sup>+</sup> *<sup>f</sup>* <sup>2</sup> <sup>+</sup>

Simmons, 1977; Sehgal et al., 2009), given in Equation 6.

*<sup>α</sup>*(*<sup>f</sup>* , *<sup>d</sup>*, *<sup>t</sup>*) = *<sup>A</sup>*<sup>1</sup> *<sup>f</sup>*<sup>1</sup> *<sup>f</sup>* <sup>2</sup> *f* 2 <sup>1</sup> <sup>+</sup> *<sup>f</sup>* <sup>2</sup> <sup>+</sup>

underwater channel models that will be used to derive and present the data transmission characteristics for a short-range link.

#### **3.1 Acoustic signal level**

The projector source level, *SLtprojector*, is generally defined in terms of the sound pressure level at a reference distance of 1 m from its acoustic centre. The source intensity at this reference range is *I* = *Ptx*/*Area* (*W*/*m*2) and measured in dB 're 1 *μPa*' but strictly meaning 're the intensity due to a pressure of 1 *μPa*'. For an omni directional projector the surface area is a sphere (4*πr*<sup>2</sup> = 12.6*m*2). Thus, *SLprojector* = 10*log*((*Ptx*/12.6)/*Iref*) dB, where *Ptx* is the total acoustic power consumed by projector and the reference wave has an intensity: *Iref* = (*Paref*)2/*<sup>ρ</sup>* <sup>∗</sup> *<sup>c</sup>* (*Wm*−2) where reference pressure level; *Paref* is 1 *<sup>μ</sup>Pa*, *<sup>ρ</sup>* is the density of the medium and; c is the speed of sound (averages for sea water: *ρ* = 1025 *kg*/*m*<sup>3</sup> and c=1500 m/s) (Coates, 1989; Urick, 1967).

The equation for the transmitter acoustic signal level (*SLprojector*) at 1 m for an omni-directional projector can be written:

$$SL\_{project}(P) = 170.8 + 10 \log P\_{\text{lx}} \qquad \text{dB} \tag{1}$$

If the projector is directional, then the projector directivity index is *D Itx* = 10*log*( *Idir Iomni* ) where *Iomni* is the intensity if spread spherically and *Idir* is the intensity along the axis of the beam pattern. Directivity can increase the source level by 20dB (Waite, 2005). The more general equation for the transmitter acoustic signal level (*SLprojector*) can be written:

$$SL\_{project}(P, \eta, DI) = 170.8 + 10 \log P\_{\rm tx} + 10 \log \eta\_{\rm tx} + DI\_{\rm tx} \tag{2}$$

where the efficiency of the projector *ηtx* takes into account the losses associated with the electrical to acoustic conversion as shown in Figure 3, thus reducing the actual SL radiated by the projector. This efficiency is bandwidth dependent and can vary from 0.2 to 0.7 for a tuned projector (Waite, 2005).

#### **3.2 Signal attenuation**

Sound propagation in the ocean is influenced by the physical and chemical properties of seawater and by the geometry of the channel itself. An acoustic signal underwater experiences attenuation due to spreading and absorption. In addition, depending on channel geometry multipath fading may be experienced at the hydrophone. Path loss is the measure of the lost signal intensity from projector to hydrophone. Understanding and establishing a accurate path loss model is critical to the calculations of Signal-to-Noise ratio (SNR).

#### **3.2.1 Spreading loss**

Spreading loss is due to the expanding area that the sound signal encompasses as it geometrically spreads outward from the source.

$$PL\_{spending}(r) = k \ast 10 \log(r) \qquad \qquad dB \tag{3}$$

where r is the range in meters and k is the spreading factor.

When the medium in which signal transmission occurs is unbounded, the spreading is spherical and the spreading factor k=2 whereas in bounded spreading, considered as cylindrical k=1. Urick (1967) suggested that spherical spreading was a rare occurrence in the ocean but recognised it may exist at short ranges. As AUV swarm operations will occur at short range it is likely that spherical spreading will need to be considered which means a higher attenuation value. Spreading loss is a logarithmic relationship with range and its impacts on the signal is most significant at very short range up to approximately 50m as seen in Figure 5(a). At these shorter ranges spreading loss plays a proportionally larger part compared with the absorption term (which has a linear relationship with range).

#### **3.2.2 Absorption loss**

6 Will-be-set-by-IN-TECH

underwater channel models that will be used to derive and present the data transmission

The projector source level, *SLtprojector*, is generally defined in terms of the sound pressure level at a reference distance of 1 m from its acoustic centre. The source intensity at this reference range is *I* = *Ptx*/*Area* (*W*/*m*2) and measured in dB 're 1 *μPa*' but strictly meaning 're the intensity due to a pressure of 1 *μPa*'. For an omni directional projector the surface area is a sphere (4*πr*<sup>2</sup> = 12.6*m*2). Thus, *SLprojector* = 10*log*((*Ptx*/12.6)/*Iref*) dB, where *Ptx* is the total acoustic power consumed by projector and the reference wave has an intensity: *Iref* = (*Paref*)2/*<sup>ρ</sup>* <sup>∗</sup> *<sup>c</sup>* (*Wm*−2) where reference pressure level; *Paref* is 1 *<sup>μ</sup>Pa*, *<sup>ρ</sup>* is the density of the medium and; c is the speed of sound (averages for sea water: *ρ* = 1025 *kg*/*m*<sup>3</sup> and

The equation for the transmitter acoustic signal level (*SLprojector*) at 1 m for an

*Iomni* is the intensity if spread spherically and *Idir* is the intensity along the axis of the beam pattern. Directivity can increase the source level by 20dB (Waite, 2005). The more general

where the efficiency of the projector *ηtx* takes into account the losses associated with the electrical to acoustic conversion as shown in Figure 3, thus reducing the actual SL radiated by the projector. This efficiency is bandwidth dependent and can vary from 0.2 to 0.7 for a

Sound propagation in the ocean is influenced by the physical and chemical properties of seawater and by the geometry of the channel itself. An acoustic signal underwater experiences attenuation due to spreading and absorption. In addition, depending on channel geometry multipath fading may be experienced at the hydrophone. Path loss is the measure of the lost signal intensity from projector to hydrophone. Understanding and establishing a accurate

Spreading loss is due to the expanding area that the sound signal encompasses as it

When the medium in which signal transmission occurs is unbounded, the spreading is spherical and the spreading factor k=2 whereas in bounded spreading, considered as cylindrical k=1. Urick (1967) suggested that spherical spreading was a rare occurrence in the ocean but recognised it may exist at short ranges. As AUV swarm operations will occur

*PLspreading*(*r*) = *k* ∗ 10*log*(*r*) *dB* (3)

*SLprojector*(*P*, *η*, *D I*) = 170.8 + 10*logPtx* + 10*logηtx* + *D Itx dB* (2)

If the projector is directional, then the projector directivity index is *D Itx* = 10*log*( *Idir*

equation for the transmitter acoustic signal level (*SLprojector*) can be written:

path loss model is critical to the calculations of Signal-to-Noise ratio (SNR).

*SLprojector*(*P*) = 170.8 + 10*logPtx dB* (1)

*Iomni* ) where

characteristics for a short-range link.

c=1500 m/s) (Coates, 1989; Urick, 1967).

omni-directional projector can be written:

tuned projector (Waite, 2005).

**3.2 Signal attenuation**

**3.2.1 Spreading loss**

geometrically spreads outward from the source.

where r is the range in meters and k is the spreading factor.

**3.1 Acoustic signal level**

The absorption loss is a representation of the energy loss in the form of heat due to the viscous friction and ionic relaxation that occurs as the wave generated by an acoustic signal propagates outwards and this loss varies linearly with range as follows:

$$PL\_{\text{absorption}}(r, f) = 10 \log(a(f)) \ast r \qquad \qquad dB \tag{4}$$

where r is range in kilometres and *α* is the absorption coefficient.

More specifically the absorption of sound in seawater is caused by three dominant effects; viscosity (shear and volume) , ionic relaxation of boric acid and magnesium sulphate (*MgSO*4) molecules and the relaxation time. The effect of viscosity is significant at high frequencies above 100 kHz, whereas the ionic relaxation effects of magnesium affect the mid frequency range from 10 kHz up to 100 kHz and boric acid at low frequencies up to a few kHz. In general, the absorption coefficient, *α*, increases with increasing frequency and decreases as depth increases (Domingo, 2008; Sehgal et al., 2009) and is significantly higher in the sea compared with fresh water due predominately to the ionic relaxation factor.

Extensive measurements of absorption losses over the last half century has lead to several empirical formulae which take into account frequency, salinity, temperature, pH, depth and speed of sound. A popular version is Thorp's expression (Thorp, 1965), Equation 5, which is based on his initial investigations in the 60's and has since been converted into metric units (shown here). It is valid for frequencies from 100Hz to 1MHz and is based on seawater with salinity of 35% ppt, pH of 8, temp of 4◦C and depth of 0 m (atmospheric pressure) which is assumed but not stated by Thorp.

$$a(f) = \frac{0.11f^2}{1+f^2} + \frac{44f^2}{4100+f^2} + 2.75 \times 10^{-4}f^2 + 0.0033 \qquad \text{dB/km} \tag{5}$$

Fisher and Simmons (1977) and others (Francois & Garrison, 1982) have since proposed other variations of *α*. In particular, Fisher and Simmons in the late 70's found the effect associated with the relaxation of boric acid on absorption and provided a more detailed form of absorption coefficient *α* in dB/km which varies with frequency, pressure (depth) and temperature (also valid for 100 Hz to 1 MHz with salinity 35% ppt and acidity 8 pH)(Fisher & Simmons, 1977; Sehgal et al., 2009), given in Equation 6.

$$a(f,d,t) = \frac{A\_1f\_1f^2}{f\_1^2 + f^2} + \frac{A\_2P\_2f\_2f^2}{f\_2^2 + f^2} + A\_3P\_3f^2 \tag{6}$$

where d is depth in meters and t is temperature in ◦C. The 'A' coefficients represent the effects of temperature, while the 'P' coefficients represent ocean depth (pressure) and *f*1, *f*<sup>2</sup> represent the relaxation frequencies of Boric acid and (*MgSO*4) molecules. These terms were developed by Fisher and Simmons (1977) and presented more recently by (Domingo, 2008; Sehgal et al., 2009).

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Short-Range Underwater Acoustic Communication Networks 181

For very short range communication (below 50 m), see Figure 5(a), the contribution of the absorption term is less significant than the spreading term. It can be seen in Figure 5(b) that the Thorp model shows a conservative or worst case value for the ranges of interest up to 500 m. The Fisher and Simmons model for a particular frequency however provides some insight into the variations due to depth and temperature. However, the spreading factor k has the most significant affect on Path Loss, seen in Figure 5(a), at these shorter ranges according

As range increases and the absorption term begins to dominate, any variations in *α* also becomes more significant. For data communication, the changes in the attenuation due to signal frequency are particularly important as the use of higher frequencies will potentially

In summary using the two models, Thorp and Fisher and Simmons, the two important characteristics that can be drawn from Path Loss at the short ranges of interest for AUV swarm

• spreading loss dominates over absorption loss, and thus the 'k' term has a significant impact on the attenuation of the signal at shorter ranges as illustrated in Figure 5 (a). For AUV swarm operations and while the range between vehicles is much less than depth

• at the ranges below 500 m the frequency component of absorption loss is most significant compared with the possible temperature and pressure (depth) changes as seen in Figure 5(b) and as range increases the difference also increases, effectively meaning that the communication channel is band-limited and available bandwidth is a decreasing function

*PathLoss*(*r*, *<sup>f</sup>* , *<sup>d</sup>*, *<sup>t</sup>*) = *<sup>k</sup>* <sup>∗</sup> <sup>10</sup>*log*(*r*) + *<sup>α</sup>*(*<sup>f</sup>* , *<sup>d</sup>*, *<sup>t</sup>*) <sup>∗</sup> *<sup>r</sup>* <sup>∗</sup> <sup>10</sup>−<sup>3</sup> (7)

(b) Comparing Absorption Models using spherical spreading. Frequency change shown using Thorp Model and Temperature ◦'C' and Depth 'm' changes

shown in Fisher and Simmons Model.

agreement with long range observations.

(a) Signal Attenuation showing spherical

spherical spreading can be assumed, and

spreading and absorption factors

Fig. 5. Path Loss vs Range

provide higher data rates.

to these models.

operation are:

of range.

Fig. 4. Absorption Coefficient vs Frequency

Figure 4 shows the absorption coefficients in dB/km vs signal frequency for both Thorp and Fisher and Simmons coefficients and shows that in general *α* increases with increasing frequency at any fixed temperature and depth. Up until around 80kHz temperature change has a more significant affect on *α* than depth (Waite, 2005), but above these frequencies depth begins to dominate (Domingo, 2008; Sehgal et al., 2009). In any case, Thorps 'approximation' is quite close to Fisher and Simmons and is clearly more conservative at the frequencies shown. Sehgal (2009) shows that at higher frequencies above 300kHz, Thorps model predicts lower losses as it does not take into account the relaxation frequencies found by Fisher and Simmons. If depth and frequency are fixed and temperature varied from 0 to 27 ◦C, there is a decrease in *α* of approximately 4 dB/km for frequencies in the range of 30 to 60kHz which correlates to work presented by Urick (Urick, 1967)(Fig5.3 pg 89). If we consider where AUV swarms are most likely to operate, in the 'mixed surface layer', where temperature varies considerable due to latitude (but has an average temp of 17◦C (Johnson, 2011)), temperature may be an important factor. It should be noted that if operating in lower temperatures *α* is higher and thus using 0◦C will be a conservative alternative. At shorter ranges, the significance of *α* is expected to be less due to the linear relationship with range which will be discussed further in this chapter.

As mentioned, depth (pressure) has less of an effect on *α* than temperature at these lower frequencies. Domingo (Domingo, 2008) investigates the effect of depth (pressure) on absorption and confirms that for lower frequencies of less than 100kHz there is less change in *<sup>α</sup>*. More specifically Urick (1967) defined the variation by: *<sup>α</sup><sup>d</sup>* <sup>=</sup> *<sup>α</sup>* <sup>∗</sup> <sup>10</sup>−3(<sup>1</sup> <sup>−</sup> 5.9 <sup>∗</sup> <sup>10</sup>−6) <sup>∗</sup> *<sup>d</sup>* dB/m (where d = depth in meters) but has also suggested an approximation of a 2% decrease for every 300 m depth. Thus, depth (pressure) variations are not expected to play a significant role in short range AUV swarm operations especially those that use a 2D horizontal topology as described in this chapter.

#### **3.3 Path loss**

Total path loss is the combined contribution of both the spreading and absorption losses. Urick (1967) established that this formula of spreading plus absorption yields a reasonable agreement with long range observations.

8 Will-be-set-by-IN-TECH

Figure 4 shows the absorption coefficients in dB/km vs signal frequency for both Thorp and Fisher and Simmons coefficients and shows that in general *α* increases with increasing frequency at any fixed temperature and depth. Up until around 80kHz temperature change has a more significant affect on *α* than depth (Waite, 2005), but above these frequencies depth begins to dominate (Domingo, 2008; Sehgal et al., 2009). In any case, Thorps 'approximation' is quite close to Fisher and Simmons and is clearly more conservative at the frequencies shown. Sehgal (2009) shows that at higher frequencies above 300kHz, Thorps model predicts lower losses as it does not take into account the relaxation frequencies found by Fisher and Simmons. If depth and frequency are fixed and temperature varied from 0 to 27 ◦C, there is a decrease in *α* of approximately 4 dB/km for frequencies in the range of 30 to 60kHz which correlates to work presented by Urick (Urick, 1967)(Fig5.3 pg 89). If we consider where AUV swarms are most likely to operate, in the 'mixed surface layer', where temperature varies considerable due to latitude (but has an average temp of 17◦C (Johnson, 2011)), temperature may be an important factor. It should be noted that if operating in lower temperatures *α* is higher and thus using 0◦C will be a conservative alternative. At shorter ranges, the significance of *α* is expected to be less due to the linear relationship with range which will be discussed further

As mentioned, depth (pressure) has less of an effect on *α* than temperature at these lower frequencies. Domingo (Domingo, 2008) investigates the effect of depth (pressure) on absorption and confirms that for lower frequencies of less than 100kHz there is less change in *<sup>α</sup>*. More specifically Urick (1967) defined the variation by: *<sup>α</sup><sup>d</sup>* <sup>=</sup> *<sup>α</sup>* <sup>∗</sup> <sup>10</sup>−3(<sup>1</sup> <sup>−</sup> 5.9 <sup>∗</sup> <sup>10</sup>−6) <sup>∗</sup> *<sup>d</sup>* dB/m (where d = depth in meters) but has also suggested an approximation of a 2% decrease for every 300 m depth. Thus, depth (pressure) variations are not expected to play a significant role in short range AUV swarm operations especially those that use a 2D horizontal topology

Total path loss is the combined contribution of both the spreading and absorption losses. Urick (1967) established that this formula of spreading plus absorption yields a reasonable

Fig. 4. Absorption Coefficient vs Frequency

in this chapter.

**3.3 Path loss**

as described in this chapter.

*PathLoss*(*r*, *<sup>f</sup>* , *<sup>d</sup>*, *<sup>t</sup>*) = *<sup>k</sup>* <sup>∗</sup> <sup>10</sup>*log*(*r*) + *<sup>α</sup>*(*<sup>f</sup>* , *<sup>d</sup>*, *<sup>t</sup>*) <sup>∗</sup> *<sup>r</sup>* <sup>∗</sup> <sup>10</sup>−<sup>3</sup> (7)

(a) Signal Attenuation showing spherical spreading and absorption factors

(b) Comparing Absorption Models using spherical spreading. Frequency change shown using Thorp Model and Temperature ◦'C' and Depth 'm' changes shown in Fisher and Simmons Model.

Fig. 5. Path Loss vs Range

For very short range communication (below 50 m), see Figure 5(a), the contribution of the absorption term is less significant than the spreading term. It can be seen in Figure 5(b) that the Thorp model shows a conservative or worst case value for the ranges of interest up to 500 m. The Fisher and Simmons model for a particular frequency however provides some insight into the variations due to depth and temperature. However, the spreading factor k has the most significant affect on Path Loss, seen in Figure 5(a), at these shorter ranges according to these models.

As range increases and the absorption term begins to dominate, any variations in *α* also becomes more significant. For data communication, the changes in the attenuation due to signal frequency are particularly important as the use of higher frequencies will potentially provide higher data rates.

In summary using the two models, Thorp and Fisher and Simmons, the two important characteristics that can be drawn from Path Loss at the short ranges of interest for AUV swarm operation are:


Communication Networks 11

Short-Range Underwater Acoustic Communication Networks 183

**Speed of Sound** 

• Reliable acoustic path, which occurs when the transmitter is located in very deep water and receiver in shallow water. Referred to as reliable as it is not generally affected by

• Shadow zones that are considered a special case, as these 'zones' are void from any signal propagation. This means that in Shadow zones a hydrophone may not receive any signal

Thus the geometry of the channel being used is a major determinate of the number of significant propagation paths and their relative strengths and delays. Apart from the Shadow Zones where no signal or multipath components of the signal can reach the hydrophone, the hydrophone may receive the direct signal and a combination of various multipath signals that have been reflected, scattered or bent. It is these multiple components of the signal that are delayed in time due to the various path lengths that may create ISI and errors in symbol

Reliable Acoustic Path

Path

Projector Hydrophone Deep Ocean

(b) Convergence Zone and Reliable Acoustic

Ocean Surface

Convergence Zone

Surface Layer (Changing conditions) Seasonal Changes Main Thermocline (Temperature decreases rapidly)

Deep Isothermal Layer (Constant temperature 4°C)

1480 m/s 1495 m/s 1510 m/s 1525 m/s

**Depth** 

Fig. 6. Typical Sound Speed Profile in the Ocean Cox (1974)

at all.

detection.

Surface Duct

Ocean Surface

Deep Ocean

Deep Sound Channel

bottom or surface reflections, as shown in Figure 7(b) and

Projector Hydrophone

(a) Surface Duct and Deep Sound Channel

Fig. 7. Ray Bending Path Loss Mechanisms

1800

2700

100 200 900

0

### **3.4 Underwater multipath characteristics**

Multipath signals, in general, represent acoustic energy loss, however, for communication systems it is the Inter Symbol Interference (ISI) that will also be detrimental at the receiver as it can significantly increase the error rate of the received signal. Multipath signals are created underwater through various mechanisms described in this section, so that, at the receiver many components of the original signal will arrive at different times due to the different length of propagation paths the multipath signals have taken. It is this delay spread of the signal component arrivals that can cause ISI to occur if they overlap with previous or future signal arrivals which will cause symbol corruption or loss and therefore bit errors. As the speed of sound propagation is very slow in an acoustic channel this delay spread can be significant.

There are two major mechanisms responsible for creating multi-path signals and these are: reverberation, which refers to the reflections and scattering of the sound signal; and ray bending, which is a result of the unique sound speed structure in the oceans which create temperature gradient channels that trap acoustic signals. Multi-path signal formation is therefore determined by the geometry of the channel in which transmission is taking place, the location of the transmitter and receiver, and importantly the depth at which it is occurring. In shallow water, multi-path is due predominately to reverberation whereas in deep water it is dominated by ray bending, although reverberation will occur in deep water if the transmitter and receiver are located near the surface or bottom (Coates, 1989; Domingo, 2008; Etter, 2003; Urick, 1967).

There are several physical effects which create reverberation underwater;


Ray bending, causes various propagation path loss mechanisms in deep water depending on the placement of transmitter and receivers. The propagating acoustic signal bends according to Snell's Law, to lower signal speed zones. Figure 6 shows a typical ocean Sound Speed Profile, although variations occur with location and seasons. The profile is depth dependent, where sound speed is influenced more by temperature in the surface layers and by pressure at greater depths.

The various path loss mechanisms include; (Domingo, 2008)


10 Will-be-set-by-IN-TECH

Multipath signals, in general, represent acoustic energy loss, however, for communication systems it is the Inter Symbol Interference (ISI) that will also be detrimental at the receiver as it can significantly increase the error rate of the received signal. Multipath signals are created underwater through various mechanisms described in this section, so that, at the receiver many components of the original signal will arrive at different times due to the different length of propagation paths the multipath signals have taken. It is this delay spread of the signal component arrivals that can cause ISI to occur if they overlap with previous or future signal arrivals which will cause symbol corruption or loss and therefore bit errors. As the speed of sound propagation is very slow in an acoustic channel this delay spread can be significant. There are two major mechanisms responsible for creating multi-path signals and these are: reverberation, which refers to the reflections and scattering of the sound signal; and ray bending, which is a result of the unique sound speed structure in the oceans which create temperature gradient channels that trap acoustic signals. Multi-path signal formation is therefore determined by the geometry of the channel in which transmission is taking place, the location of the transmitter and receiver, and importantly the depth at which it is occurring. In shallow water, multi-path is due predominately to reverberation whereas in deep water it is dominated by ray bending, although reverberation will occur in deep water if the transmitter and receiver are located near the surface or bottom (Coates, 1989; Domingo, 2008; Etter, 2003;

There are several physical effects which create reverberation underwater;

animals or plants or bubbles in the path of the transmitted signal

absorption, particularly on the sea bottom depending on material

The various path loss mechanisms include; (Domingo, 2008)

• Volume scattering caused by refractive off objects suspended in the signal path

• Multi-path propagation caused by boundary reflections at the sea-floor or sea-surface, seen

• Multi-path propagation caused by reflection from objects suspended in the water, marine

• Surface scattering caused by sea-surface (waves) or sea-floor roughness or surface

Ray bending, causes various propagation path loss mechanisms in deep water depending on the placement of transmitter and receivers. The propagating acoustic signal bends according to Snell's Law, to lower signal speed zones. Figure 6 shows a typical ocean Sound Speed Profile, although variations occur with location and seasons. The profile is depth dependent, where sound speed is influenced more by temperature in the surface layers and by pressure

• Surface duct, Figure 7(a) occurs when the surface layer has a positive temperature gradient, the acoustic signals can bend back towards the surface, then reflect back into the layer off

• Deep Sound Channel, sometimes referred to as the SOFAR (Sound Fixing and Ranging) channel, where acoustic propagation occurs above and below the level of minimum sound speed, when the sound rays continually are bent towards the depth of minimum speed,

• Convergence zone, in deep water areas when the transmitter is located quite close to the surface and the sound rays bend downwards as a result of decreasing temperatures until the increase in pressure forces the rays back towards the surface, as shown in Figure 7(b)

**3.4 Underwater multipath characteristics**

Urick, 1967).

in Figure 2.

at greater depths.

the surface

shown in Figure 7(a)

Fig. 6. Typical Sound Speed Profile in the Ocean Cox (1974)


Thus the geometry of the channel being used is a major determinate of the number of significant propagation paths and their relative strengths and delays. Apart from the Shadow Zones where no signal or multipath components of the signal can reach the hydrophone, the hydrophone may receive the direct signal and a combination of various multipath signals that have been reflected, scattered or bent. It is these multiple components of the signal that are delayed in time due to the various path lengths that may create ISI and errors in symbol detection.

(a) Surface Duct and Deep Sound Channel

(b) Convergence Zone and Reliable Acoustic Path

Fig. 7. Ray Bending Path Loss Mechanisms

Communication Networks 13

Short-Range Underwater Acoustic Communication Networks 185

Ambient Noise in the ocean has been well defined (Urick, 1967). It can be represented as Gaussian and having a continuous power spectrum density (psd). It is made up of four components (outlined below), each having a dominating influence in different portions of

Fig. 8. Power Spectral density of the Ambient Noise, W - wind, S - shipping

of interest for AUV communication particularly as the wind speed increases.

of s whose value ranges from 0 to 1 for low to high activity respectively:

frequency region of 100Hz - 100kHz where wind speed is given by w in m/s:

where wind speed is given by w in m/s (1m/s is approximately 2 knots) and f is in kHz. Ambient Noise power also decreases with increasing depth as the distance from the surface and therefore shipping and wind noise becomes more distant. Ambient noise has been shown to be 9dB higher in shallow water than deep water (Caruthers, 1977). Swarm operations, as well as other underwater networking operations will mean that communication nodes including AUV's will be working in relatively close proximity to other nodes which will add an additional level of ambient noise to their operations due to the noise of the other vehicles in

10*logNship*(*f*) = 40 + 20(*s* − 0.5) + 26*log*(*f*) − 60*log*(*f* + 0.03)

<sup>10</sup>*logNwind*(*f*) = <sup>50</sup> <sup>+</sup> 7.5*w*1/2 <sup>+</sup> <sup>20</sup>*log*(*f*) <sup>−</sup> <sup>40</sup>*log*(*<sup>f</sup>* <sup>+</sup> 0.4)

• Thermal noise becomes dominate over 100kHz:

10*logNturb*(*f*) = 17 − 30*log*(*f*)

10*logNth*(*f*) = −15 + 20*log*(*f*)

For the frequency region of interest for AUV swarm communication systems (10 kHz to 100 kHz), the ambient noise psd decreases with increasing frequency, refer to Figure 8. At a frequency over 100kHz the ambient thermal noise component begins to dominate and the overall noise psd begins to increase, but this point moves further away from the frequencies

• Turbulence noise influences only the very low frequency regions *f* < 10*Hz*

• Shipping noise dominates the 10 - 100Hz region and has defined a shipping activity factor

• Wave and other surface motion caused by wind and rain is a major factor in the mid

**3.6.1 Ambient noise**

the frequency spectrum.

For very short range channels that will be used in AUV swarm operations, multipath will be influenced also by the range-depth ratio, which is expected to produce fewer multipath signals at the hydrophone (Hajenko & Benson, 2010; Parrish et al., 2007). In addition some improvement can be gained through directing the beam of the transmitted signal and the directional properties of the receiver (Essebbar et al., 1994), however this will require an additional level of complexity for mobile AUV's due to the need for vehicle positioning before sending or when receiving a signal.

Most of the discussion so far has focused on time-invariant acoustic channel multipath where deterministic propagation path models have been developed for the various reflective and ray bending path options. These are significant in themselves with multipath spreads in the order of 10 to 100 ms. Take Figure 2, where projector and hydrophone are separated by 100m and are at a depth of 100m, the delay spread between the direct path and the first surface reflection is ≈ 28 ms. Multipath in an underwater channel, however, also has time-varying components caused by the surface or volume scattering or by internal waves in deep water that are responsible for random signal fluctuations. Unlike in radio channels, the statistical characterisation of these random processes in the underwater channel are in their early development stages. Experimental results have shown that depending on the day, the location and the depth of communication link, the results of multipath can follow one of the deterministic models discussed here to worst case coherence times in the order of seconds(Stojanovic, 2006). Another source of time variability in an underwater communication channel occurs when there is relative motion between the transmitter and receiver as will be briefly discussed in the following sub-section.

#### **3.5 The doppler effect**

The motion of AUV's relative to each other will cause two possible forms of Doppler distortion in the received signal, Doppler Shifting caused by an apparent shift in frequency as the vehicles move towards or away from each other and Doppler Spreading or its time domain dual coherence time, which is the measure of the time varying nature of the frequency dispersiveness in the doppler spectrum (Rappaport, 1996). The doppler shift (Δ*f*) of a received signal is *fc* Δ*v <sup>c</sup>* where *fc* is the original signal frequency and Δ*v* is the relative velocity between the moving vehicles. As an example, if the vehicles were moving at a moderately slow speed of 1 m/s (2 knots) relative to each other and *fc* = 40*kHz* the Δ*f* ≈ 27*Hz*. Doppler spread or coherence time measurements as mentioned above can be as long as 1 s. Thus doppler shifting and spreading cause complications for the receiver to track the time varying changes in the channel which need to be designed into the channel estimation algorithms and explicit delay synchronisation approach within communication protocols. As swarm operations for exploration require rigid topology where there is minimal relative speed differences between vehicles, the impact of doppler effects diminished somewhat in this context and thus will not be considered further.

#### **3.6 Noise**

There are three major contributors to noise underwater: ambient or background noise of the ocean; self noise of the vehicle; and intermittent noise including biological noises such as snapping shrimp, ice cracking and rain. An accurate noise model is critical to the evaluate the SNR at the hydrophone so that the bit error rates (BER) can be establish to evaluate protocol performance.

### **3.6.1 Ambient noise**

12 Will-be-set-by-IN-TECH

For very short range channels that will be used in AUV swarm operations, multipath will be influenced also by the range-depth ratio, which is expected to produce fewer multipath signals at the hydrophone (Hajenko & Benson, 2010; Parrish et al., 2007). In addition some improvement can be gained through directing the beam of the transmitted signal and the directional properties of the receiver (Essebbar et al., 1994), however this will require an additional level of complexity for mobile AUV's due to the need for vehicle positioning before

Most of the discussion so far has focused on time-invariant acoustic channel multipath where deterministic propagation path models have been developed for the various reflective and ray bending path options. These are significant in themselves with multipath spreads in the order of 10 to 100 ms. Take Figure 2, where projector and hydrophone are separated by 100m and are at a depth of 100m, the delay spread between the direct path and the first surface reflection is ≈ 28 ms. Multipath in an underwater channel, however, also has time-varying components caused by the surface or volume scattering or by internal waves in deep water that are responsible for random signal fluctuations. Unlike in radio channels, the statistical characterisation of these random processes in the underwater channel are in their early development stages. Experimental results have shown that depending on the day, the location and the depth of communication link, the results of multipath can follow one of the deterministic models discussed here to worst case coherence times in the order of seconds(Stojanovic, 2006). Another source of time variability in an underwater communication channel occurs when there is relative motion between the transmitter and

The motion of AUV's relative to each other will cause two possible forms of Doppler distortion in the received signal, Doppler Shifting caused by an apparent shift in frequency as the vehicles move towards or away from each other and Doppler Spreading or its time domain dual coherence time, which is the measure of the time varying nature of the frequency dispersiveness in the doppler spectrum (Rappaport, 1996). The doppler shift (Δ*f*) of a received

the moving vehicles. As an example, if the vehicles were moving at a moderately slow speed of 1 m/s (2 knots) relative to each other and *fc* = 40*kHz* the Δ*f* ≈ 27*Hz*. Doppler spread or coherence time measurements as mentioned above can be as long as 1 s. Thus doppler shifting and spreading cause complications for the receiver to track the time varying changes in the channel which need to be designed into the channel estimation algorithms and explicit delay synchronisation approach within communication protocols. As swarm operations for exploration require rigid topology where there is minimal relative speed differences between vehicles, the impact of doppler effects diminished somewhat in this context and thus will not

There are three major contributors to noise underwater: ambient or background noise of the ocean; self noise of the vehicle; and intermittent noise including biological noises such as snapping shrimp, ice cracking and rain. An accurate noise model is critical to the evaluate the SNR at the hydrophone so that the bit error rates (BER) can be establish to evaluate protocol

*<sup>c</sup>* where *fc* is the original signal frequency and Δ*v* is the relative velocity between

receiver as will be briefly discussed in the following sub-section.

sending or when receiving a signal.

**3.5 The doppler effect**

Δ*v*

be considered further.

signal is *fc*

**3.6 Noise**

performance.

Ambient Noise in the ocean has been well defined (Urick, 1967). It can be represented as Gaussian and having a continuous power spectrum density (psd). It is made up of four components (outlined below), each having a dominating influence in different portions of the frequency spectrum.

Fig. 8. Power Spectral density of the Ambient Noise, W - wind, S - shipping

For the frequency region of interest for AUV swarm communication systems (10 kHz to 100 kHz), the ambient noise psd decreases with increasing frequency, refer to Figure 8. At a frequency over 100kHz the ambient thermal noise component begins to dominate and the overall noise psd begins to increase, but this point moves further away from the frequencies of interest for AUV communication particularly as the wind speed increases.


where wind speed is given by w in m/s (1m/s is approximately 2 knots) and f is in kHz. Ambient Noise power also decreases with increasing depth as the distance from the surface and therefore shipping and wind noise becomes more distant. Ambient noise has been shown to be 9dB higher in shallow water than deep water (Caruthers, 1977). Swarm operations, as well as other underwater networking operations will mean that communication nodes including AUV's will be working in relatively close proximity to other nodes which will add an additional level of ambient noise to their operations due to the noise of the other vehicles in

Communication Networks 15

Short-Range Underwater Acoustic Communication Networks 187

As the operating frequencies of the communication system is likely to be higher than most self noise, and the vehicles will operate relatively slowly, the expected contribution of self noise

The sources of intermittent noise can become very significant in locations or times that they occur close to operating AUV swarms. The two major areas where research has been undertaken are in the marine bio-acoustic fields and also the effect of rain and water bubbles

• Shellfish - Crustacea - most important here are the snapping scrimp who produce a broad

Rain creates different noise spectrum to wind and needs to be dealt with separately as it is not a constant source of noise. Urick (1967) showed examples of increases of almost 30dB in the 5 to 10kHz portion of spectrum in heavy rain, with steady rain increasing noise by 10dB or sea state equivalent increase from 2 to 6. Eckart (1952) presented average value of rain at the

These main contributors to intermittent sources predominate in the lower frequency ranges up to 20kHz. Thus, interference in the operating frequencies of communication data signals is

Utilising the full capacity of the underwater acoustic channel is extremely important as the channel exhibits such challenging and limited resources as has been discussed. For short range data transmission operations there are a number of benefits that can be gained over current longer range underwater acoustic transmission. These will now be explored further in terms of data communication protocol design and development. In particular, finding the optimum signal frequency and bandwidth at different ranges and under various channel conditions will be evaluated on the basis of using the best Signal-to-Noise ratio (SNR) possible at the hydrophone. Investigation into channel capacity and BER for various possible modulation schemes will also be analysed to set up the background to the challenges for MAC and routing

The narrowband Signal-to-Noise-Ratio (SNR) observed at the receiver, assuming no

where B is the receiver bandwidth and the Signal Level (SL), PathLoss and Noise terms have

Taking the frequency dependent portion of the SNR from Equation 8, as developed by Stojanovic (2006), is the *PathLoss*(*r*, *f* , *d*, *t*) ∑ *Noise*(*f* , *w*,*s*) product. Since SNR is inversely

*SLprojector*(*Ptx*, *η*, *D I*)

*PathLoss*(*r*, *<sup>f</sup>* , *<sup>d</sup>*, *<sup>t</sup>*) <sup>∑</sup> *Noise*(*<sup>f</sup>* , *<sup>w</sup>*,*s*) <sup>×</sup> *<sup>B</sup>* (8)

on the hydrophone reception will be low.

Major contributors to underwater bio-acoustic noise include;

spectrum of noise between 500Hz and 20kHz

• Marine mammals - Cetacea - porpoises 20 to 120Hz

surface from 100Hz to 10kHz of -17 to 9dB.

**4. Short range channel modelling**

**4.1 Frequency dependent component of SNR**

*SNR*(*r*, *f* , *d*, *t*, *w*,*s*, *Ptx*) =

multi-path or doppler losses is given by:

been previously developed.

**3.6.3 Intermittent sources of noise**

created by raindrops.

considered low.

protocol design.

• Fish - toadfish 10 to 50Hz

the swarm, irrespective of the operating depth. As will be discussed in the next section on Self Noise, the expectation is that this additional 'ambient noise' which relates to the 'Shipping Noise' component of ambient noise will have limited affect on the acoustic communication which generally uses frequencies above 10kHz.

#### **3.6.2 Self noise**

Self noise is defined as the noise generated by the vehicle itself as the platform for receiving signals. This noise can reach the hydrophone mounted on the AUV either through the mechanical structure or through the water passing over the hydrophone. The degree to which turbulent flows cause transducer self noise depends on the location (mounting) of the transducer and its directivity characteristics (Sullivan & Taroudakis, 2008). Self Noise can also be seen as an equivalent isotropic noise spectrum as presented by Urick from work done during WWII on submarines. In general, as with ambient noise, there is decreasing levels of self noise with increases in frequency however self noise is also significantly affected by speed with decreasing noise spectra when the vessels are travelling at slower speeds or are stationary (Eckart, 1952; Kinsler et al., 1982; Urick, 1967).

Kinsler (1982) notes that at low frequencies (<1kHz) and slow speeds machinery noise dominates and at very slow speeds self noise is usually less important than ambient noise. Whereas at higher frequencies (10kHz) propeller and flow noise begins to dominate and as speed increases the hydrodynamic noise around the hydrophone increases strongly and becomes more significant than the machinery noise. This is due to the cavitation from the propeller due to the entrainment of air bubbles under or on the blade tip of the propeller. At higher speeds, self noise can be much more significant than ambient noise and can become the limiting factor.

The self noise of different size and types of vehicles are as varied as there are vehicle designs and there is little recent published values. Each vehicle itself produces large variations in self noise with speed and operating conditions (Eckart, 1952). Self noise can be controlled by selection of motor type, configuration, mounting and motor drivers. The trend for most AUV's will be the use of small brush-less DC electric motors which have been used on the development of the SeaVision vehicle (Mare, 2010). Preliminary testing of self noise on these vehicles shows an increase in noise due to increases in speed, as has been predicted, but there was no way to distinguish between machinery and hydrodynamic affects. Higher frequency components (up to 20kHz) were present as the speed increased due to the increased work from the thrusters. When the SeaVision vehicle hovered in a stationary position the frequency of the noise psd centred around 2kHz, which is out of band noise.

Holmes (Holmes et al., 2005) at WHOI recently investigated the self noise of REMUS, their torpedo shape AUV, used as a towed array. At the maximum RPM of the AUV, the 1/3rd octave noise level, when converted to source level by the calibrated transmission factor, was 130 dB re 1*μPa* at 1m directly aft of the vehicle for a centre frequency of 1000 Hz. This would represent the radiated noise source level for a vehicle moving at 3 knots (1.5m/s). Vehicles typically radiate less noise in free operating conditions than in tethered conditions, so the second trail on the REMUS was measuring the radiated noise of the vehicle to examine the power spectral density of the noise as recorded on the hydrophone array as it was towed behind the vehicle. The results showed the RPM dependent radiated noise in the aft direction at a distance of 14.6 m behind the vehicle looking at frequency range up to 2500Hz which is again out of band noise.

As the operating frequencies of the communication system is likely to be higher than most self noise, and the vehicles will operate relatively slowly, the expected contribution of self noise on the hydrophone reception will be low.
