Intelligent & Adaptive Underwater Acoustic Networking

Abstract

Underwater acoustic communication is a critical component of various applications, including oceanography, marine biology, environmental monitoring, and offshore industries. This dissertation presents a comprehensive exploration of the challenges and advancements in the development of protocols and algorithms for underwater acoustic communication systems.The research encompasses a thorough review of the unique characteristics of the underwater acoustic channel, including limited bandwidth, multipath propagation, high attenuation, and ambient noise. It identifies the existing limitations in current protocols and algorithms, emphasizing the need for tailored solutions to overcome these challenges.This work introduces novel protocols and algorithms designed to optimize data transfer efficiency in underwater environments. The proposed techniques exploit agent mobility, environmental noise, and energy-efficient routing strategies to enhance communication reliability and data throughput. The evaluation of these contributions are conducted through extensive simulations and real-world experiments that demonstrate improvement over previous techniques. Furthermore, this research explores the development of adaptive algorithms for acoustic communication systems, designed to adjust to the dynamic nature of the underwater channel. These algorithms utilize machine learning and artificial intelligence approaches to modify the behaviour of agents in underwater networks.This dissertation includes several contributions to the growing body of knowledge in underwater acoustic communication by addressing the specific challenges of the underwater acoustic channel. The proposed adaptive protocols and algorithms form a foundation for future work on reliable, efficient, and autonomous underwater communication systems.The findings offer valuable insights for researchers, engineers, and organizations seeking to deploy effective communication solutions in underwater environments.iii I would like to thank Carleton University and Defence Research and Development Canada for their financial and scholastic support. Without their contributions, this work would not have been possible.I am deeply indebted to my dear friends Dr. Abdolreza Shirvani, Dr. Ahmad Traboulsi, and Wenqian Wang. These wonderful colleagues have suffered hours of my vocal method of contemplation; without complaint. Many of the concepts discussed in this work are the fruits of our seemingly endless postulating in front of a whiteboard.