AquaNode: A Solution for Wireless Underwater Communication

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AquaNode A Solution for Wireless Underwater
Communication

• Ryan Kastner
• Department of Electrical and Computer Engineering
• University of California, Santa Barbara
• CREON GLEON Workshop
• March 30, 2006

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Monitoring in Moorea

• Establish monitoring sites in lagoons and on fore
  reefs surrounding Moorea
• Response variables measured
• Weather
• Tides, Currents and Flows
• Ocean Temperature Color
• Salinity, Turbidity pH
• Nutrients
• Recruitment Settlement
• Size Age Structure
• Species Abundance
• Community Diversity

Underwater wireless enabling technology for Moorea
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Why Use Wireless Underwater?

• Wired underwater not feasible in all situations
• Temporary experiments
• Tampering/breaking of wires
• Significant cost for deployment
• Experiments over longer distances
• Ocean observatories
• ORION, LOOKING, MARS, NEPTUNE
• Not ideal for coral reefs, lakes
• AquaNode can easily be used in conjunction with
  observatories
• Why not use radios and buoys?
• Common use is buoy with mooring commercial
  radio on buoy to satellite, shore,
• Buoys/equipment get stolen
• Cable breakage, ice damage

Underwater wireless will enable new experiments
complement existing technologies
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Scenario for WetNet for Eco-Surveillance

• Deploy Ad hoc wireless (acoustic) network in
  lagoon
• Network consists of AquaNodes with Conductivity,
  Temperature, Depth (CTD) sensors (and many
  others)
• Ad hoc network allows AquaNodes to relay data to
  a dockside collector
• AquaNode requirements
• Low cost, low power wireless modems
• Integral router
• Integral CTD sensor suite
• Additional nitrate, oxygen chemical sensors
• Real-time data from Moorea available on Web

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Underwater Acoustic Channel

• Severe multipath - 1 to 10 msec for shallow water
  at up to 1 km range
• Doppler Shifts
• Long latencies speed of sound underwater approx
  1500 m/sec

Dock
AquaNodes with acoustic modems/routers, sensors.
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WetNet using Aquanodes
CTD, currents, nutrient data to Internet.
Adaptive sampling commands to AquaNodes.
Wi-Fi or Wi-Max link
Dockside acoustic/RF comms and signal processing.
Cabled hydrophone array
Dock
Data collection sites with acoustic
modems/routers, sensors, mooring and underwater
floats
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AquaNode
Software Defined Acoustic Modem
Transducer
Float
Router
Modem Circuitry
Batteries
Sensor Interface
Sensors
Mooring
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Hardware Platform

• Ideal One piece of hardware for all sensor nodes
• Hardware is wirelessly updatable no need to
  retrieve equipment to update hardware for
  changing communication protocols, sampling,
  sensing strategies

Transducer
CTD Sensor
Reconfigurable Hardware Platform
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Hardware Platform Interfaces

• Sensor Interface
• Must develop common interface with different
  sensors (CTD, chemical, optical, etc.) and
  communication elements (transducer)
• Wide (constantly changing) variety of sensors,
  sampling strategies

• Communication Interface
• Amplifiers, Transducers
• Signal modulation
• Hardware
• Software Defined Acoustic Modem (SDAM)
• Reconfigurable hardware known to provide,
  flexible, high performance implementations for
  DSP applications

Transducer
CTD Sensor
Reconfigurable Hardware Platform
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Acoustic Modem Requirements

• Complex, computationally intensive communication
  protocols
• Limited power/energy
• Ease of use Good design tools, plug-n-play,
  reprogrammable

Transducer
Communication Protocol
CTD Sensor
Reconfigurable Hardware Platform
Plug-N-Play
Mapping
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Design Considerations for SDAM

• Multipath Spread Range of 1 to 10 milliseconds
  for shallow water at up to 1 km range
• Larger bandwidths reduce frequency dependent
  multipaths
• Transducers
• Size/weight/cost proportional to wavelength
• Acceptable propagation losses at 100 meter ranges
• Waveform
• M-FSK signaling
• Datasonics/Benthos modems (used in Seaweb, FRONT)
• Narrowband thus sensitive to frequency-selective
  fading.
• Use more tones increasing sensitivity to
  Doppler spread.
• Walsh/m-sequence signaling (Direct-sequence)
• Provides frequency diversity due to wide
  bandwidth
• Can be detected noncoherently

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What about existing modems?

• Commercial modems (Benthos, Linkquest)
• Too expensive, power hungry for Eco-Sensing.
  Proprietary algorithms, hardware.
• M-FSK (Scussel, Rice 97, Proakis 00) does use
  frequency diversity, but requires coding to
  erase/correct fades.
• Navy modems
• Need open architecture for international LTER
  community precludes military products.
• Direct-sequence, QPSK, QAM, coherent OFDM
• Great deal of work on DS, QPSK for underwater
  comms. But equalization, channel estimation are
  difficult. (Stojanovic 97, Freitag, Stojanovic
  2001, 2003.)
• MicroModem (WHOI)
• Best available solution for WetNet.
• FSK/Freq. Hopping relies on coding to correct bad
  hops.

But can we do better? Less power? Wider
bandwidth?
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AquaModem Data Sheet
Signal and Data Parameters Data rate 133 bps Chip duration Tc .2 msec. Symbol duration Tsym 11.2 msec. Time guard interval Tc 11.2 msec. M-sequence length Lpn 7 chips. Walsh sequence length Nw 8 Bandwidth 5 kHz Carrier Frequency fc 25 kHz Nominal range 100 300 m.
Power Consumption Overview Load Tx State Rx State Sleep State CPU 440 mW 440 mW .30 mW CPU I/O 420 mW 420 mW .15 mW Flash Memory 165 mW 165 mW .10 mW Power Amp. 7.2 W .05 mW .05 mW Battery Total 9.3 W 2.1 W 10 mW
Battery Life (Based on 20 amp-hours) Tx Duty Cycle Rx Duty Cycle Days .1 .2 624 .5 1 189 1 2 101
Sonatech Transducer
lt 1 meter
TI 2812 DSP with CompactFlash, ADC, DAC
Power Amp and Transducer Matching Network
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Walsh/m-Sequence Waveforms
Chip rate 5 kcps, approx. 5 kHz bandwidth.
Uses 25 kHz carrier. Use 7 chip m-sequence c per
Walsh symbol, 8 bits per Walsh symbol bi.
Composite symbol duration is thus T 11.2 msec.
(Longer than maximum multipath spread.) Symbol
rate is 266 bps, or 133 bps using 11.2 msec. time
guard band for channel clearing.
11 msec.
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Transmitted Signal
1
1
-1
1
-1
-1
-1
1
1
-1
1
-1
-1
-1
-1
-1
1
-1
1
1
1
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Walsh/m-sequence Signal Parameters
1
1
-1
1
-1
-1
-1
1
1
-1
1
-1
-1
-1
-1
-1
1
-1
1
1
1
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8 Walsh Symbols
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UWA Walsh/m-sequence GMHT-MP Modem
Generalized multiple hypothesis test (GMHT)
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Acoustic Modem Performance

• True multipath intensity profile (MIP)

• Nf paths assumed by MP estimation
• N? Number of paths present

MP identifies major paths using one symbol of
information
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Acoustic Modem Performance

• Symbol Error Rate (SER)
• Signal to noise ratio (Es/N0)
• Nf paths assumed by MP estimation
• N? Number of paths present

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Required Transmit Power

• Transmit power control
• Adapt automatically to field conditions, Use only
  enough to get reliable links
• Often use small of amplifier capacity ?
  Significant reduction in system energy use

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Energy Usage
In most cases CPU power dominates (when using low
transmit power)
For all links up to 400 meters, projected energy
use is 50 mJ per bit
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Battery life

• System example uses alkaline D cells
• (low self discharge, good J / )
• 16 or 32 cells 1.3 or 2.6 MJ respectively
• At 50 mJ per bit, with 16 cell battery,
• endurance days 300 / rate bps

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AquaModem Air Tests
UCSB Engineering 1 Hallway
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6
Symbols Sent 144 Packets Sent 36 Symbol
Error 1.4 Packet Error 5.6
7
10
18
5
5
11
7
233
7
6
Symbols Sent 360 Packets Sent 90 Symbol
Error 1.1 Packet Error 4.4
7
10
18
5
5
11
7
233
7
6
Symbols Sent 192 Packets Sent 48 Symbol
Error 10 Packet Error 20.1
7
10
18
5
5
11
7
233
Transmitter Location
Receiver Location
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Challenges

• Power
• Communication
• Transducer size/weight/cost proportional to
  wavelength
• Adaptive power control
• Computation
• Microprocessors extremely power hungry
• Move towards FPGA, ASIC
• Cost
• Communication
• Current transducer 3K US
• Fish finders? (lt 100 US )
• Computation
• Data rates arent particularly high ? simple
  microprocessors
• Communication protocols complex ? DSP, FPGAs
• Low power/energy will cost money ? FPGA, ASIC
• Ease of use
• Plug-n-play interfaces to sensors
• Change network/communication protocols
• Adjust sampling strategies

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Credits

• Investigators Ron Iltis, Hua Lee, Ryan Kastner
• ExPRESS Lab http//express.ece.ucsb.edu/
• Telemetry Lab http//telemetry.ece.ucsb.edu/
• AquaNode Research Team
• Research Tech Maurice Chin
• PhD Students Bridget Benson, Daniel Doonan,
  Tricia Fu, Chris Utley
• Undergrads Brian Graham
• http//aquanode.ece.ucsb.edu/
• Sponsor