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Simulation of Communication for Power constrained Embedded Systems By Samir Govilkar Under the guidance of Dr. Alex Dean.

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Presentation on theme: "Simulation of Communication for Power constrained Embedded Systems By Samir Govilkar Under the guidance of Dr. Alex Dean."— Presentation transcript:

1 Simulation of Communication for Power constrained Embedded Systems By Samir Govilkar Under the guidance of Dr. Alex Dean

2 The RaPTEX Project  Rapid Prototyping Tool for Embedded Communication Systems  Aid development of embedded communication systems by non- specialists  Targeted at study of crabs using acoustic biotelemetry and health monitoring of bridges using wireless sensor networks

3 Studying Crabs using acoustic biotelemetry  Blue crabs, Callinectes sapidus, are robust enough to carry a transmitter  Allows study of physiological and biological parameters  Power efficiency required because of weight restrictions on the battery  Ideal evaluation platform for RaPTEX

4 Underwater communication  Electromagnetic waves cannot be used because of a conductive medium and high scattering  Acoustic waves provide a good solution Lesser dissipation Lower scattering Communication over hundreds of kilometres possible

5 A simulation environment  Testing of underwater communication systems requires frequent trips to a water body  Simulation environment to cut down on the number of such trips by providing a good estimation to the actual conditions  Provide RaPTEX with performance estimation data

6 Propagation Losses  Spreading Losses Geometrical divergence loss Effect of the Law of Conservation of Energy Dependent on range  Absorption Losses Viscosity of pure water Molecular relaxation of Magnesium Sulphate and Boric Acid Dependent on temperature, depth and frequency of the acoustic wave

7 Multiple Paths  Multiple paths are followed by the acoustic wave from Tx to Rx Reflections from air-water boundary Reflections from the water body bed  Gives rise to multipath fading Echoes Interference patterns  The delayed paths have lesser power than the LOS component

8 Modeling Multiple Paths  Multipath fading is simulated using a tapped delay line channel model The first tap is the LOS component The other taps have a gain given by a Rice process

9 Ambient Noise  Surface Agitation Noise caused by wind Bursting of bubbles of air at the air- water boundary Dependent on wind speed and frequency of the acoustic wave  Thermal Noise caused by random motion of molecules in water Dependent on the frequency

10 Intermittent Noise  Snapping Shrimp cause noise by the snapping of their claws No mathematical model Model was built using observed data Dependent on frequency  Rain Noise caused by impact of rain drops on surface of water Dependent on rate of rainfall and wind speed

11 Sampling rate conversion  Enables use of different sources of data  For this thesis, two sources are the simulator and data from the field data capture unit

12 Related Work  Avrora – AVR Simulator Cycle accurate simulator for AVR microcontrollers Highly extensible Relatively fast compared to other AVR simulators  IT++ - Signal Processing Library Multipath fading channel classes Channel profiles

13 System Block Diagram

14 Embedded System Simulator (ESS)  Based on the Avrora simulator  Platform consisting of AVR microcontroller, DAC and Ultrasonic Transducer  Generates and transmits acoustic signal  Works as a server, to which other programs can connect to, for obtaining data

15 ESS Block Diagram  Input is a program in assembly or the output of the avr-objdump facility  Output is streamed over a TCP connection as pairs of data and timing information

16 Water Channel Simulator (WCS)  Attempts to simulate the effects of propagation losses, noise and multipath fading.  The carrier frequencies are selectively attenuated according to the appropriate noise models  Noise is filtered and added to the carrier frequency components  Multipath fading simulation is done using complex numbers

17 WCS Block Diagram  The input to the WCS is from the ESS via a TCP connection or from a file  The output is to standard output which can be redirected to a file  The WCS can record data received over the TCP connection for later playback

18 Receiver Simulator  Consists of the Sampling Rate Converter, Receiver Filter array and the demodulator array  The sampling rate converter will resample the input file to the required sampling frequency  The receiver filters are 6 th order elliptic IIR filters with a 2 kHz bandwidth centered around the carrier frequencies  The default demodulation scheme is Amplitude Shift Keying (ASK)

19 RS Block Diagram

20 Visualization Module  Used to display the RS output waveforms and the demodulated data  Can be launched from the RS via a command line switch  Can be launched independently and file can be loaded using the GUI

21 VM Graph Window  This window displays the plots and the corresponding demodulated data

22 Amplitude Shift Keying (ASK)  Simple modulation scheme Uses amplitude of the carrier wave to encode the binary data  Special case is On-Off Keying (OOK) Uses presence or absence of the carrier wave to signify a binary ‘1’ and binary ‘0’ respectively.  Highly susceptible to noise  Simplicity allows for easier debugging of the system

23 Implementation  Transmission of carrier wave Uses a timer interrupt based routine in assembly to ensure operation at 5 MHz sampling rate  Profile settings Wind Speed Rainfall Rate Temperature Salinity Depth Range

24 Multipath profiles  Sample underwater multipath profiles to be used by the tapped delay line model Underwater 1 Taps1234 Delay(ms)0246 Power (dB)0-20-30-40 Underwater 2 Taps1234 Delay(ms)0246 Power (dB)0-20-30-40

25 Simulation Speed Comparison

26 Results  Clear advantage observed in using ‘Recorded’ mode for the WCS over the ‘Live’ mode  Correlation observed as expected between the channel profiles and the simulation speeds, based on their computational complexity.

27 Waveforms and Power Spectra

28 Observations  Aim of thesis was to provide a simulation solution for underwater acoustic communication by embedded systems  Effect of various factors were explored  Models based on recent research were used to simulate the system

29 Future Work  Integration with RaPTEX needs to be performed in order to use this system efficiently.  Water body profiles need to be built up by performing measurements of the relevant parameters for the target water bodies  The Visualization Module can be improved to include more information about the received signal, based on the modulation scheme used.  Support for multiple modulation schemes can be added to the receiver, in order to evaluate their pros and cons.  Support for a network of ESS platforms simultaneuously talking to a single WCS.

30 Thank You


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