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Underwater Acoustic Channel Estimation and Statistical Analysis from Experimental Data

Underwater Acoustic Channel Estimation and Statistical Analysis from Experimental Data. Missouri University of Science and Technology Department of Electrical and Computer Engineering Student: Jesse Cross Advisor: Dr. Rosa Zheng. RESULTS

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Underwater Acoustic Channel Estimation and Statistical Analysis from Experimental Data

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  1. Underwater Acoustic Channel Estimation and Statistical Analysis from Experimental Data Missouri University of Science and Technology Department of Electrical and Computer Engineering Student: Jesse Cross Advisor: Dr. Rosa Zheng • RESULTS • The CIR estimation plot shows how the CIR can change with time. • The autocorrelation function is a measure of how likely the next coefficient values are related to the current coefficient. • OBJECTIVES • Estimate the channel impulse response (CIR) of the acoustic underwater channel • Compare the PDF of the channel coefficients to known distributions • Analyze statistical properties such as the correlation, coherence time, and scattering function • BACKGROUND • Acoustic communication in shallow water is more complicated than in air radio communication due to the excessive pass loss, scattering, and time varying nature of the channel. Underwater Multipath • APPROACH • Experimental data from the Reschedule Acoustic Communications Experiment in March 2008 (RACE08) has been analyzed. • The CIR of the channel has been estimated many times using the sliding window least squares estimation technique in the time domain. • The coefficients of the CIRs calculated were used to plot the PDF of the underwater channel and to calculate the other statistical properties • FUTURE WORK • Data from other environments will be analyzed. • The knowledge gained from this experiment will be used to create a transceiver design that improves upon the speed of current transceivers. • DISCUSSION • Rayleigh PDF does not describe the experimental PDF • Channel coherence time is .12 seconds. Therefore, the channel is time invariant for about 470 symbols. • Doppler spread is very low in this channel since both the receivers and transmitters were fixed. • Observed Doppler spread is due to the movement of the channel medium, itself. Acknowledgements NSF grant ECCS-0846486 ONR grant N00014-10-1-0174 Intelligent Systems Center

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