Author Identifier

Kazi Yasin Islam

ORCID : 0000-0002-3969-034X

Iftekhar Ahmad

ORCID : 0000-0003-4441-9631

Daryoush Habibi

ORCID : 0000-0002-7662-6830

Document Type

Journal Article

Publication Title

IEEE Access




School of Engineering




Edith Cowan University - Open Access Support Scheme 2021

Department of Jobs, Tourism, Science and Innovation - Defence Science Centre, Australia


Islam, K. Y., Ahmad, I., Habibi, D., Zahed, M. I. A., & Kamruzzaman, J. (2021). Green underwater wireless communications using hybrid optical-acoustic technologies. IEEE Access, 9, 85109-85123.


Underwater wireless communication is a rapidly growing field, especially with the recent emergence of technologies such as autonomous underwater vehicles (AUVs) and remotely operated vehicles (ROVs). To support the high-bandwidth applications using these technologies, underwater optics has attracted significant attention, alongside its complementary technology – underwater acoustics. In this paper, we propose a hybrid opto-acoustic underwater wireless communication model that reduces network power consumption and supports high-data rate underwater applications by selecting appropriate communication links in response to varying traffic loads and dynamic weather conditions. Underwater optics offers high data rates and consumes less power. However, due to the severe absorption of light in the medium, the communication range is short in underwater optics. Conversely, acoustics suffers from low data rate and high power consumption, but provides longer communication ranges. Since most underwater equipment relies on battery power, energy-efficient communication is critical for reliable underwater communications. In this work, we derive analytical models for both underwater acoustics and optics, and calculate the required transmit power for reliable communications in various underwater communication environments. We then formulate an optimization problem that minimizes the network power consumption for carrying data from underwater nodes to surface sinks under varying traffic loads and weather conditions. The proposed optimization model can be solved offline periodically, hence the additional computational complexity to find the optimum solution for larger networks is not a limiting factor for practical applications. Our results indicate that the proposed technique yields up to 35% power savings compared to existing opto-acoustic solutions.



Creative Commons License

Creative Commons Attribution 4.0 License
This work is licensed under a Creative Commons Attribution 4.0 License.