Underwater Acoustic Sensor Networks

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My research is about underwater acoustic communications and networks. Applications include subsurface activity sensors, unmanned undersea vehicles, airplane underwater locator beacons and underwater robotics. I focuss on communications, network management and collaboration between nodes. Using acoustic signals, long range underwater/under-ice communication is an important key challenge for the Canadian environment, having the longest coastlines of any country in the world often with ice cover. I believe that long range communications are possible because of the results of a few past experiments and theoretical analysis. Although, the conditions under which they happen may greatly vary according to time and location. Furthermore, we are dealing with awfully attenuated signals. My research draws on the science of extremely weak signal communications that can deal with channels with extraordinarily high attenuation. Noise, amplitude, frequency and phase variations together with multipath propagation exacerbate the problem. The focus of my research is on the design of the data link layer, which includes framing and high redundancy forward error correction. It is strengthened further with deep-search decoding. Leveraging knowledge about possible content of messages, such as their structure and addresses of nodes that have been deployed, pattern matching and rules are used to establish a relationship between a received packet and plausible messages. To deal with the variability of the conditions and select protocols elements that are adapted to the channel, I use the cognitive approach where protocols dynamically adapt to the channel quality. Network management provides the ability to remotely monitor and update the state of nodes. It is a crucial feature because of the difficulty of physical access to nodes once they have been deployed underwater/under-ice. Long range underwater/under-ice communications are very difficult to achieve. Solely very short packets can be exchanged. For such cases, non-classical network management approaches need to be investigated. I develop a bio-inspired approach that does not require management traffic. Learning-by-imitation is used to transfer the settings node-to-node. Every node learns its settings by observing and imitating its neighbors. The approach does not generate traffic overhead. It is useful in cases where it is really hard to convey information using messages, which is expected in the harsh conditions of the underwater/under-ice environment. My research provides communication links and paths to support the exchange of messages and navigation information between underwater nodes. I develop collaboration protocols between unmanned undersea vehicles. Various tasks are explored such as search and rescue and surveillance. Core functions include awareness of peers and environment and distribution of work among collaborators.