The oceans remain mostly unexplored despite covering more than 70% of Earth’s surface. The cause is undeniably dangerous and challenging underwater environments that pose hindrances to researchers and scientists due to extreme pressure, temperature, and limited accessibility. Unlike terrestrial communication, where wireless signals can travel effectively through the air, underwater environments induce significant challenges such as high attenuation, limited bandwidth, and propagation delays to wireless signal propagation due to the high conductivity of seawater. This challenge intensifies the need for resource-efficient and reliable communication protocols, especially in mission-critical applications such as monitoring telecommunication cables, oil reserves, and gas pipelines.
In her doctoral dissertation, M.Sc. Rabia Qadar elaborates on the benefits of using multi-modal communication to improve reliability, enhance energy efficiency, and reduce delays for dense underwater networks with high data traffic.
“The incorporation of machine learning and multi-modal communication can efficiently address the challenges of dynamic, resource-constrained underwater networks and achieve optimal performance,” proposes Qadar.
The strategic use of multi-modal communication as a solution
Multi-modal underwater communications have emerged as a means of solving the inherent challenges of underwater networks. A multi-modal device contains more than one communication subsystem.
“Developing a robust communication protocol that retains less delays in communication and achieves high energy efficiency in the dynamic underwater environment is possible through the strategic use of multi-modal communication,” says Qadar.
She explores dual aspects of underwater communication, spanning wireless optical channels to acoustic links. Her initial studies showed that the practical limitations of alignment and multipath attenuation of optical communication, particularly in large-scale and long-range underwater networks, can hinder its deployment in multi-modal communication infrastructure.
“This groundwork analysis laid the foundation for the transition to acoustics-based multi-modal communication. The empirical results from this analysis provided valuable insights into designing Underwater Optical Communication (UOC) module,” says Qadar.
The research addresses the most critical and widely applicable challenges
The UOC class is an integral module for network simulator (ns-3) for the design and evaluation of large-scale underwater optical networks. It is capable of efficiently simulating characteristics such as optical channel losses and packet collisions in underwater networks.
The proposed framework, DREAM, helps improve the efficiency, robustness, and adaptability of underwater communication systems, particularly through multi-modal acoustic communication.
“Underwater devices can learn optimal routes that consume less energy by considering factors such as distance, device energy levels, and wireless channel conditions. This enables the selection of energy-efficient paths, thus minimizing unnecessary energy consumption, reducing time delays, and avoiding congested paths,” explains Qadar.
With the adaptive use of two different frequency modems and machine learning, DREAM, enables an even distribution of the traffic among all the nodes, even when the traffic scenarios change and the
number of underwater devices increases. The valuable insights from the framework are intended to report future extensions of the framework to hybrid multi-modal systems.
Public defence on Thursday 11 September
The doctoral dissertation of M.Sc. Rabia Qadar in the field of electrical engineering titled Multi-modal Communication Approaches to Underwater Wireless Networking will be publicly examined at the Faculty of Information Technology and Communication Sciences at Tampere University at 12 o’clock on Thursday 11 September 2025 at Hervanta campus, Rakennustalo, auditorium RG202 (Korkeakoulunkatu 5, Tampere).
The Opponent will be Assistant Professor Hemani Kaushal University of North Florida USA. The Custos will be Professor Jari Nurmi from Tampere University, Finland. The work has been co-supervised by Associate Professor Bo Tan from University College London.
The doctoral dissertation is available online
The public defence can be followed via remote connection