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Proceedings Paper

Carrier frequency offset estimation for an acoustic-electric channel using 16 QAM modulation
Author(s): Michael T. Cunningham; Leonard A. Anderson; Kyle R. Wilt; Soumya Chakraborty; Gary J. Saulnier; Henry A. Scarton
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Paper Abstract

Acoustic-electric channels can be used to send data through metallic barriers, enabling communications where electromagnetic signals are ineffective. This paper considers an acoustic-electric channel that is formed by mounting piezoelectric transducers on metallic barriers that are separated by a thin water layer. The transducers are coupled to the barriers using epoxy and the barriers are positioned to axially-align the PZTs, maximizing energy transfer efficiency. The electrical signals are converted by the transmitting transducers into acoustic waves, which propagate through the elastic walls and water medium to the receiving transducers. The reverberation of the acoustic signals in these channels can produce multipath distortion with a significant delay spread that introduces inter-symbol interference (ISI) into the received signal. While the multipath effects can be severe, the channel does not change rapidly which makes equalization easier. Here we implement a 16-QAM system on this channel, including a method for obtaining accurate carrier frequency offset (CFO) estimates in the presence of the quasi-static multipath propagation. A raised-power approach is considered but found to suffer from excessive data noise resulting from the ISI. An alternative approach that utilizes a pilot tone burst at the start of a data packet is used for CFO estimation and found to be effective. The autocorrelation method is used to estimate the frequency of the received burst. A real-time prototype of the 16 QAM system that uses a Texas Instruments MSP430 microcontroller-based transmitter and a personal computer-based receiver is presented along with performance results.

Paper Details

Date Published: 12 May 2016
PDF: 12 pages
Proc. SPIE 9825, Sensors, and Command, Control, Communications, and Intelligence (C3I) Technologies for Homeland Security, Defense, and Law Enforcement Applications XV, 98250P (12 May 2016); doi: 10.1117/12.2224366
Show Author Affiliations
Michael T. Cunningham, Rensselaer Polytechnic Institute (United States)
Leonard A. Anderson, Rensselaer Polytechnic Institute (United States)
Kyle R. Wilt, Rensselaer Polytechnic Institute (United States)
Soumya Chakraborty, Rensselaer Polytechnic Institute (United States)
Gary J. Saulnier, Rensselaer Polytechnic Institute (United States)
Henry A. Scarton, Rensselaer Polytechnic Institute (United States)


Published in SPIE Proceedings Vol. 9825:
Sensors, and Command, Control, Communications, and Intelligence (C3I) Technologies for Homeland Security, Defense, and Law Enforcement Applications XV
Edward M. Carapezza, Editor(s)

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