New paper on Underwater Acoustic Communication Receiver Using Deep Belief Network

Recent PhD graduate Dr. Abigail Lee-Leon, Prof Chau Yuen, and myself just published a paper on 'Underwater Acoustic Communication Receiver Using Deep Belief Network' in IEEE Transactions on Communications. Preprint link. Underwater communications is a challenging field due to the many interferences in the channel (e.g. Doppler effect, boats, fish, etc.). This paper uses a novel deep learning approach to model the receiver.

Congrats to Abigail on finishing her PhD on deep learning for underwater communication

Abigail Leon has successfully defended her PhD today with main supervisor Prof. Yuen Chau and myself as co-supervisor. Abigail has successfully explored how deep learning techniques can be used to denoise en demodulate complex underwater acoustic communication signals, and has performed some sea-trials to gather data for this. Since the PhD is under an NDA with Thales, we cannot post it, however, check out some of Abigail's papers here (more to come after the review process ends).

Talk on deep belief networks for doppler invariant demodulation - IEEE APWCS

PhD student Abigail Leon from the AMAAI lab presented a paper at the 16th IEEE Asia Pacific Wireless Communications Symposium (APWCS) on "Doppler Invariant Demodulation for Shallow Water Acoustic Communications Using Deep Belief Networks".