# In-network Collaboration for CDMA-based Reliable Underwater Acoustic   Communications

**Authors:** Mehdi Rahmati, Roberto Petroccia, and Dario Pompili

arXiv: 1904.09539 · 2019-04-23

## TL;DR

This paper presents an adaptive collaborative strategy for CDMA-based underwater acoustic networks that dynamically adjusts physical and link-layer parameters to enhance reliability and throughput in challenging underwater environments.

## Contribution

It introduces a novel in-network collaboration approach combining adaptive parameter adjustment with HARQ to improve underwater communication reliability.

## Key findings

- Validated with real sea trial data and testbed experiments.
- Achieved improved reliability in poor channel conditions.
- Demonstrated effectiveness of collaborative resource allocation.

## Abstract

Achieving high throughput and reliability in underwater acoustic networks for transmitting distributed and large volume of data is a challenging task due to the bandwidth-limited and unpredictable nature of the acoustic channel. In a multi-node network, such as in the Internet of Underwater Things (IoUT), communication link efficiency varies dynamically: if the channel is not in good condition, e.g., when in deep fade, channel coding techniques may fail to deliver the information even with multiple retransmissions. Hence, an efficient and agile collaborative strategy is required to allocate appropriate resources to the communication links based on their status. The proposed solution adjusts the physical and link-layer parameters collaboratively for a Code Division Multiple Access (CDMA)-based underwater network. An adaptive Hybrid Automatic Repeat Request (HARQ) solution is employed to guarantee reliable communications against errors in poor links. Results were validated using data collected from the LOON testbed-hosted at the NATO STO Centre for Maritime Research and Experimentation (CMRE) in La Spezia, Italy-and from the REP18-Atlantic sea trial conducted in Sept'18 in Portuguese water.

## Full text

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## Figures

13 figures with captions in the complete paper: https://tomesphere.com/paper/1904.09539/full.md

## References

32 references — full list in the complete paper: https://tomesphere.com/paper/1904.09539/full.md

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Source: https://tomesphere.com/paper/1904.09539