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Performance improvement of data transmission using a hybrid underwater and terrestrial system
Author(s) -
Ramadan Khalil F.,
Ramadan Khaled,
Taha Taha E.,
Dessouky Moawad I.,
Abd ElSamie Fathi E.
Publication year - 2021
Publication title -
transactions on emerging telecommunications technologies
Language(s) - English
Resource type - Journals
SCImago Journal Rank - 0.366
H-Index - 47
ISSN - 2161-3915
DOI - 10.1002/ett.4247
Subject(s) - adaptive equalizer , computer science , equalization (audio) , underwater acoustic communication , orthogonal frequency division multiplexing , minimum mean square error , bit error rate , transmission (telecommunications) , algorithm , turbo equalizer , computational complexity theory , electronic engineering , underwater , channel (broadcasting) , control theory (sociology) , estimator , mathematics , decoding methods , telecommunications , engineering , block code , statistics , artificial intelligence , oceanography , control (management) , geology , error floor
In this paper, we investigate and enhance the performance of data transmission using a hybrid underwater and terrestrial system with low‐complexity linear equalization. Due to the low speed, salinity, water depth, pH degree, and water temperature variations, underwater acoustic communication has become one of the most challenging technologies in the world. The most common linear equalizers are the Linear Zero Forcing (LZF), and Linear Minimum Mean Square Error (LMMSE) equalizers. The LZF equalizer suffers from the noise enhancement problem, while the LMMSE equalizer requires the value of the operating Signal‐to‐Noise Ratio ( SNR ) to work, correctly, which increases the computational complexity. In addition, this paper presents a low‐complexity equalization scheme to overcome the drawbacks associated with the LZF, and LMMSE equalizers. The proposed equalizer is called the Joint Low‐Complexity Regularized LZF equalizer, which depends on a fixed regularization parameter to minimize the noise enhancement phenomenon caused by the LZF equalizer. The proposed equalizer does not need the estimation of the SNR, and the computational complexity is reduced due to the utilization of the banded‐matrix approximation. The proposed equalizer is implemented based on the Single‐Input‐Single‐Output configuration for Orthogonal Frequency Division Multiplexing (OFDM) using the Discrete Cosine Transform. The obtained simulation results show that the proposed equalizer outperforms different equalizers for the same channel conditions.