Towards large scale underwater communication networks miniature, low cost, low power acoustic transceiver design Jeff Neasham, Senior Lecturer, School of Electrical & Electronic Engineering
Outline Background. Spread spectrum transmission schemes Hardware efficient implementation Miniature platforms Seatrac, Nanotrac Positioning capabilities The future EPSRC USMART project
School of Electrical and Electronic Engineering SEAlab Sensors, electromagnetics and acoustics laboratory Main activities Acoustic and electromagnetic signal processing. Expertise (20 years +) Underwater acoustic communication and navigation. Sonar systems and transducer design. Low power wireless sensor network development. Acoustic and electromagnetic sensor development. Through metal communications. Medical ultrasound imaging. Successful commercialisation Underwater acoustic modem technology. Underwater positioning technology. Wireless environmental sensor networks. RECENT PROJECTS CADDY - Cognitive Autonomous Diving Buddy NEWTON Novel sensing network for intelligent monitoring USMART Underwater smart dust for distributed sensing Development of affordable ultrasound imaging FP7-ICT UK - EPSRC EPSRC CORDAID 3
Facilities - SEAlab Anechoic test tank. 3 ROVs Acoustic transducers & instrumentation. Access to research vessel.
Underwater acoustic communication Pioneers in: spatial and frequency diversity adaptive receiver structures advanced Doppler correction techniques Licencing technologies to industrial partners e.g. Tritech, Blueprint Subsea, Nautronix.
So what have we achieved? 0-10km Ship/surface noise Rx Array + Tx projector 20-1000bits/s V High integrity multipath Simultaneous positioning multipath 1-40kbits/s high integrity Tx/Rx omni 0-5000m Thruster noise +/-15m/s Van Walree PA, Neasham JA, Schrijver MC. Coherent acoustic communication in a tidal estuary with busy shipping traffic. Journal of the Acoustical Society of America 2007, 122(6), 3495-3506.
Adaptive multichannel receivers Array signal 0 BP Filter Downconverter (I-Q) Linear interpolator ( s 0.8 s) x0 Forward filter h0 (N taps) K Array signal K-1 BP Filter Downconverter (I-Q) Linear interpolator ( s 0.8 s) xk-1 Forward filter hk-1 (N taps) Training sequence (frame-synchronised by correlation) y Bandpass signal @ s= 100kHz Complex baseband signal @ s= 2.5/T Complex baseband signal @ s= 2/T d Feedback filter g (M taps) Complex baseband signal @ s= 1/T Shah CP, Tsimenidis CC, Sharif BS, Neasham JA. Low Complexity Iterative Receiver Structure for Time Varying Frequency Selective Shallow Underwater Acoustic Channels using BICM-ID: Design and Experimental Results. IEEE Journal of Oceanic Engineering 2011, 36(3), 406-421.
Adaptive multichannel receivers Channel response 8 6 4 Array response Array Gain (db) 2 0-20 -10 0 10 20-2 0 1000 2000 3000 2 1 t ime (us) Input constellation 2 1-4 -6-8 Vertical Angle (Deg) Array receiver output 0-2 -1 0 1 2 0-2 -1 0 1 2-1 -1-2 -2
Spread spectrum transmission Information signal spectrum spread f Transmitted signal spectrum De-spread f De-spread signal spectrum Spreading averages noise and channel effects over wide spectrum Channel frequency response Acoustic noise spectrum f f If we transmit a narrow band signal at these frequencies performance will be very poor
Linear FM (chirp) techniques Binary orthogonal chirp (BOK) Sweep spread carrier freq freq fmax fmax fmin 1 0 1 1 0 0 Simple matched filter receiver. Highly multipath & Doppler tolerant. Poor bandwidth utilisation (<100bps for B = 8kHz) time fmin time Swept carrier with PSK / FSK modulation. Good multipath tolerance. Bandwidth utilisation still low.
Aperiodic direct sequence spreading Source data (bytes) (N, K) RS encoder QPSK mapping f chip /L f chip f chip e jωct (carrier) Tx 8191 chip binary M- sequence 255 chip QPSK training LFM chirp e -jωct Rx resample & correct CFO (ω d ) f chip*2 x Adaptive LMS filter (h) f chip y de-spread (L chips) f chip / L QPSK hard decision LFM correlator (frame synch) 255 chip QPSK training e - + d f chip re-spread (L chips) (N, K) RS decoder
Aperiodic DSSS results (L = 8, 1.5 kbps) 2 2 2 1.5 1.5 1.5 1 0.5 0-0.5-1 -1.5 1 0.5 0-0.5-1 -1.5 Estimated velocity (m/s) 1 0.5 0-0.5-1 -1.5-2 -2-1.5-1 -0.5 0 0.5 1 1.5 2 Constellation before de-spreading -2-2 -1.5-1 -0.5 0 0.5 1 1.5 2 Constellation after de-spreading -2 0 100 200 300 400 500 600 700 800 900 1000 Symbol number Estimated velocity from Doppler correction Reduction of inter-symbol interference is independent of channel timespread (in this case >100ms). Residual symbol errors are corrected by channel code.
Lower probability of detection communication systems (eco-friendly?) Using the spread spectrum concept with very high BT product (>1000). Received signal-noise ratio as low as -20dB (noise power = 100x signal power). Pseudo-noise signals more difficult to discriminate from background noise. Audible range << receivable range.
M-ary orthogonal code keying Data symbols consist of a family of near orthogonal PN codes. Vastly outperforms QAM-DSSS for large BT products. Receiver complexity high but simplifications are possible.
M-OCK receiver structure
Received spectrum during 100bps transmission at 10km (SL < 170dB) Extremely hard to detect by ear. Extremely hard to detect signal analysis without entire code family. Minimises interference with other acoustic systems. Sherlock B, Tsimenidis CC, Neasham JA. Signal and Receiver Design for Low-Power Acoustic Communications Using M-ary Orthogonal Code Keying. IEEE OCEANS 2015 - Genova. 2015.
Efficient implementation of spread spectrum receivers Sparse signal processing is used to reduce computational load of correlation receiver. Bandpass sampling - reduces sampling rate. Simplified arithmetic 1xN bit and 1x1 bit convolution eliminate multipliers. Overall much lower processor power and cost.
What is the performance penalty? 1 0.9 0.8 0.7 0.6 0.5 0.4 0.3 0.2 0.1 0 0 1000 2000 3000 4000 5000 6000 7000 8000 9000 10000 f s = 96kHz, 16-bit, 16 x16 MAC 1 0.9 0.8 0.7 0.6 0.5 0.4 0.3 0.2 0.1 0 0 100 200 300 400 500 600 700 800 900 f s = 8kHz, 16-bit, 1 x16 MAC 1 0.9 0.8 0.7 0.6 0.5 0.4 0.3 0.2 0.1 0 0 100 200 300 400 500 600 700 800 900 f s = 8kHz, 1-bit, binary MAC 1 x 16 bit correlator has almost no penalty in PN code detection. Binary (1x1) correlator only starts to degrade severely as SNR approaches 0 db (due to hard-limiting effect).
Seatrac miniature hardware platform Miniature transponder with integrated USBL array (160mm x 50mm) Simultaneous positioning and data exchange. Spread spectrum data rates from 100 1500 bits/s (chirp and DSSS). Reliable operation to 2km range in hostile multipath channels. Licensed to Blueprint Subsea: http://www.blueprintsubsea.com/ Neasham JA, Goodfellow G, Sharphouse R. Development of the "Seatrac" miniature acoustic modem and USBL positioning units for subsea robotics and diver applications, IEEE OCEANS 2015 - Genova. 2015.
Ultra low cost/power Nanomodems transducer circuit Transducer and electronics can be separated by cable or encapsulated together (inset)
Nanomodem specification Supply voltage Supply current (5V supply) Acoustic signals 3 6.5V dc Receiving: < 2mA Transmitting: ~ 300mA 24-28kHz, SPL = 168 db Acoustic data rate 40 160 bps BOK, unicast and broadcast messages. Addressing up to 255 nodes (programmable) Ranging (ping command) Maximum Range 9.375 cm (c=1500m/s) increment, ~20 cm variance 2 km RS232 interface 9600 Baud, 8-bit, no parity, 1 stop bit, no flow control Manufacturing cost < 40 for assembled PCB and transducer
USBL positioning (Seatrac platform) Tiny in-built USBL array (20mm spacing). Repeatability of bearing < 1 deg, absolute accuracy < 5 deg. Ranging within 20cm given accurate VOS. White = USBL fix, blue = GPS, USBL fixed at yellow marker
LBL positioning with Nanomodems Multiple nanomodems in known reference locations. Position calculated by long baseline method (white) and compared to GPS (red).
EPSRC USMART ( 1.3M, 06/17 05/20) Step change in efficiency/cost of subsea data gathering. Enhanced Nanomodems up to 500bps using MOK/DSSS. Smart distributed sensing algorithms + efficient network protocols
Thank you for listening Any questions? Email: jeff.neasham@ncl.ac.uk