Iterative adaptive estimation of underwater channel transfer function based on soft information using turbo equalization

Underwater acoustic communication has a rising interest in recent years as a result of increasing use of autonomous underwater vehicles. Underwater communication creates a difficult challenge because of different reasons such as ISI, Doppler and time variant channels, in addition to lack of research in compare to RF. In order to overcome the channel distortion problems, it is common to use equalizers for diminishing the channel effect. The state of the art equalizer today is a DFE followed by a standard decoding scheme. In this project, we suggest a new decoding scheme which combines the equalization and decoding stages through multiple iterations between them while using soft information, and thus achieving better performance. For showing proof of concept, we created a modular environment implementation of the communication chain while using different encoding schemes and different equalizers. We simulated on various ISI channels taken from literature and showed a significant better error floor than other state of the art equalizers. Finally, we use our system in order to decipher recordings taken from an underwater experiment in the Mediterranean sea, and showed a significant improvement over the DFE that was originally used.

Underwater communication

Iterative adaptive estimation of underwater channel transfer function based on soft information using turbo equalization

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