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AquaNode: A Solution for Wireless Underwater Communication

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. Lagoon. Fore reef. Monitoring in Moorea.

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AquaNode: A Solution for Wireless Underwater Communication

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  1. 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

  2. Lagoon Fore reef 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

  3. 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

  4. Aquanodes Lab MOOREA Ad hoc network between Aquanode sensors. lagoon Collection station with acoustic sensor array 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

  5. 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.

  6. 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

  7. AquaNode Software Defined Acoustic Modem Transducer Float Router Modem Circuitry Batteries Sensor Interface Sensors Mooring

  8. 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

  9. 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

  10. 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

  11. 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

  12. 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?

  13. AquaModem Data Sheet Sonatech Transducer < 1 meter TI 2812 DSP with CompactFlash, ADC, DAC Power Amp and Transducer Matching Network

  14. 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.

  15. Transmitted Signal 1 1 -1 1 -1 -1 -1 -1 -1 1 -1 1 1 1 1 1 -1 1 -1 -1 -1

  16. 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

  17. 8 Walsh Symbols

  18. Matching Pursuit Core Matching Pursuit Core arg min i Matching Pursuit Core Note: 112 Nyquist samples/symbol + 112 samples for channel clearing. Matching Pursuit Core UWA Walsh/m-sequence GMHT-MP Modem Generalized multiple hypothesis test (GMHT)

  19. Acoustic Modem Performance • Nf: # paths assumed by MP estimation • N: Number of paths present • True multipath intensity profile (MIP) MP identifies major paths using one symbol of information

  20. > 4 dB gain over FSK @ .5 x 10-3 SER Acoustic Modem Performance • Symbol Error Rate (SER) • Signal to noise ratio (Es/N0) • Nf: # paths assumed by MP estimation • N: Number of paths present

  21. 10dB = 90% reduction in amplifier power for all links less than 450 meters 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

  22. Energy used per bit transceived ≈ constant Energy used while “asleep” < 10% of total 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

  23. 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]

  24. AquaModem Air Tests UCSB Engineering 1 Hallway 7’ 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

  25. 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? (< 100 US $) • Computation • Data rates aren’t 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

  26. 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:

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