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Efficient Equalization and Carrier Frequency Offset Compensation for Underwater Wireless Communication Systems

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Abstract

Underwater Acoustic (UWA) wireless communication systems are plagued by a slew of flaws that restrict their performance. This includes factors such as high attenuation in seawater, sediment type, acidity concentration, water temperature, and sound speed propagation. One of the available solutions is Orthogonal Frequency Division Multiplexing (OFDM). Unfortunately, the OFDM systems suffer from the Carrier Frequency Offset (CFO) phenomenon that causes Inter-Carrier-Interference. One of the means to overcome this problem is joint equalization and CFO compensation. In this paper, the conventional OFDM system is adapted for Multiple-Input-Multiple Output (MIMO)-OFDM communication utilizing Discrete Wavelet Transform (DWT) rather than Discrete Fourier Transform (DFT). The DWT-based OFDM system has certain benefits over the comparable DFT. The trade-off, on the other hand, is the necessity for an extra DFT/IDFT to complete the Frequency-Domain equalization procedure, which increases the total computational complexity. In addition, we present a Joint Low Regularized Linear Zero Forcing equalizer for MIMO-OFDM based on DWT that employs the banded-matrix approximation approach. The suggested approach avoids signal-to-noise ratio estimation. Simulation results show that the proposed scheme outperforms different schemes at the same UWA channel conditions spatially in the case of estimation errors.

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Data sharing not applicable to this article as no datasets were generated or analyzed during the current study.

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The authors confirm contribution to the paper as follows: study conception, design, analysis, and interpretation of results: Khaled Ramadan data collection, and draft manuscript preparation: Mohamed S. Bakry All authors reviewed the results and approved the final version of the manuscript.

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Ramadan, K., Elbakry, M.S. Efficient Equalization and Carrier Frequency Offset Compensation for Underwater Wireless Communication Systems. Ann. Data. Sci. 9, 1201–1221 (2022). https://doi.org/10.1007/s40745-022-00449-x

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