Prof. Youwen Zhang

Keynote Speech Title: Advanced Topics in Underwater Acoustic Communications

Speaker's Bio:
Youwen Zhang received the M.E. in signal processing and Ph.D. degrees in underwater acoustic engineering from the Harbin Engineering University, Harbin, China, in 2004 and 2005, respectively. Since 2005, he has been with the College of Underwater Acoustic Engineering, Harbin Engineering University, where he is currently an associated professor. From Dec. 2016 to Dec. 2017, he was a visiting scholar at the University of York, York, UK. His research interests include the underwater acoustic communication and networking, array signal processing for sonar, deep learning and its applications in UWA communication and target detection and tracking.



Keynote Speech Abstract:
In recent years, underwater acoustic (UWA) communications have received much attention as their applications have begun to shift from military toward commercial. The terrestrial wireless communication hasmade great achievements, however, wireless communicationunderwater, more specifically, the underwater acousticcommunication, is still facing significant challengesincurred by the harsh underwater acoustic propagationenvironment. Unlike the terrestrial radio channel,the UWA channel is featured by frequency-dependentlimited bandwidth, long delay spread and rapid time variationdue to severe Doppler effects (caused by the low speedof sound in water), leading to relatively low data ratesin a range between a few bits/s (bps) to several tens ofkilo bits/s (kbps) and often unsatisfied performance. TheUWA channel has been regarded as one of the most difficultchannels for communications. This talk presents a review of recent results in underwater acoustic communications, focusing on six advanced topics including the broadband Doppler estimation and compensation, millimeter wave (mmWave)high data rate communications, single carrier MIMO communications, AUV communications, deep learning based UWA communications, and in-band full-duplex UWA communication based on deep learning.