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Low-Complexity Superresolution Frequency Offset Estimation for High Data Rate Acoustic OFDM Systems

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This paper addresses the problem of compensating for motion-induced Doppler frequency offset in multicarrier acoustic communication systems based on orthogonal frequency-division multiplexing (OFDM). In mobile acoustic systems, Doppler effect can… Click to show full abstract

This paper addresses the problem of compensating for motion-induced Doppler frequency offset in multicarrier acoustic communication systems based on orthogonal frequency-division multiplexing (OFDM). In mobile acoustic systems, Doppler effect can be severe enough that the received OFDM signal experiences nonnegligible frequency offsets even after initial resampling. To target these offsets, a superresolution, yet low-complexity method based on a stochastic gradient approach is proposed. The method relies on differentially coherent detection that keeps the receiver complexity at a minimum and requires only a small pilot overhead. Differential encoding is applied across carriers, promoting the use of a large number of closely spaced carriers within a given bandwidth. This approach simultaneously supports frequency-domain coherence and efficient use of bandwidth for achieving high bit rates. While frequency synchronization capitalizes on differentially coherent detection, it can also be used as a preprocessing stage in coherent receivers without creating undue complexity. Using simulation, as well as the experimental data transmitted over a 3–7-km shallow-water channel in the 10.5–15.5-kHz acoustic band, we study the system performance in terms of data detection mean squared error and bit error rate, and show that the proposed method provides excellent performance at low computational cost. Such advantages are of paramount importance for practical implementation of high data rate acoustic OFDM systems.

Keywords: low complexity; frequency; high data; frequency offset; rate; complexity

Journal Title: IEEE Journal of Oceanic Engineering
Year Published: 2019

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