Acoustic Underwater Channel and Network Simulator

Wolff, Lars Michael; Szczepanski, Erik; Badri-Hoeher, Sabah

doi:10.1109/oceans-yeosu.2012.6263608

Cited by 10 publications

(7 citation statements)

References 10 publications

Supporting

Mentioning

Contrasting

Order By: Relevance

“…In particular, Bellhop can factor in, among others: the SSP at multiple points throughout the water body section that joins the transmitter to the receiver; the relevant bathymetry in the area, including abrupt changes; the shape of surface waves; and the geo-acoustic properties of the sea bottom sediments. Bellhop has been used to model acoustic channels in different communication contexts, and served as the basis for more complex models (e.g., see [87], [88]). In our context, Bellhop yields accurate time-of-arrival information for each acoustic path, and sufficiently accurate complex amplitude information, so that the outcome of correlation operations can be trusted.…”

Section: Auv Location Estimationmentioning

confidence: 99%

Underwater Direction of Arrival Estimation using Wideband Arrays of Opportunity

Dubrovinskaya

Casari

2019

OCEANS 2019 - Marseille

View full text Add to dashboard Cite

Casari knows no boundaries. He believed in me to allow me to work independently while providing all the possible support and was by my side when needed. His high standards both in research and communication have become my constant beacon in my personal and professional growth. His assistance in every aspect of research work was absolutely invaluable.Another thank you should definitely go to my tutor Prof. Albert Banchs Roca for all his help with the paperwork from the very first days of my Ph.D. I would also like to say thanks to Dr. Ivor Nissen for his introduction to the world of underwater acoustic localization research, and for always keeping an eye on my progress. I am grateful to Dr. Diamant for welcoming and hosting me at Haifa University and enduring me during numerous sea trials. All the field experience I got during my trips to Israel is still one of the most unforgettable go through during my Ph.D.Furthermore, I would like to say many thanks to Dr. Konstantin Kebkal and Evologics GmbH colleagues for hosting me at their premises in Berlin and for all the invaluable help in organizing lab and field experiments. Special thanks to Veronika Kebkal who pushed everyone to make it possible (and fun!) Also, I would like to thank Dr. Fraser Dalgleish who hosted me at Florida Atlantic University and for sharing experimental data even after I left.A huge bunch of thanks goes to all my colleagues at IMDEA Networks for all the coffee break talks, dinner drinks, board games battles, and barbeque parties. Special thanks go to the "ground-floor" team for all the evening gossip times and fun we had.Last but not least thank you goes to my wonderful family. Thanks to my parents for teaching me to value knowledge and for giving me everything I need. And the most important thanks -to my husband Sergey Samodov, who was solving all my life problems, listened to my nagging during the hardest days saying, "this too shall pass", waiting for me to come back. I couldn't have done this journey without you.

show abstract

Section: Auv Location Estimationmentioning

confidence: 99%

Underwater Direction of Arrival Estimation using Wideband Arrays of Opportunity

Dubrovinskaya

Casari

2019

OCEANS 2019 - Marseille

View full text Add to dashboard Cite

show abstract

“…These effects will cause an elongation of the path traveled, and thus a time delay. The received signal in a mutli-path environment can be generally represented as seen in [33], [34]:…”

Section: B Underwater Channelmentioning

confidence: 99%

Underwater Acoustic Communication Receiver Using Deep Belief Network

Lee-Leon¹,

Yuen²,

Herremans³

2021

Preprint

View full text Add to dashboard Cite

Underwater environments create a challenging channel for communications. In this paper, we design a novel receiver system by exploring the machine learning technique-Deep Belief Network (DBN)-to combat the signal distortion caused by the Doppler effect and multi-path propagation. We evaluate the performance of the proposed receiver system in both simulation experiments and sea trials. Our proposed receiver system comprises of DBN based de-noising and classification of the received signal. First, the received signal is segmented into frames before the each of these frames is individually pre-processed using a novel pixelization algorithm. Then, using the DBN based de-noising algorithm, features are extracted from these frames and used to reconstruct the received signal. Finally, DBN based classification of the reconstructed signal occurs. Our proposed DBN based receiver system does show better performance in channels influenced by the Doppler effect and multi-path propagation with a performance improvement of 13.2dB at 10 −3 Bit Error Rate (BER).

show abstract

“…67. AUWCN (Acoustic Underwater Channel and Network) simulator aims to alleviate the inappropriate simplifications and to reproduce most effects existing in the physical acoustic underwater channel (Wolff et al, 2012). 68.…”

Section: Records (Remote Control Framework For Underwatermentioning

confidence: 99%

Ubiquitous sensor network simulation and emulation environments: A survey

Sharif

Sadeghi‐Niaraki

2017

Journal of Network and Computer Applications

View full text Add to dashboard Cite

Recent human effort has been directed at expanding pervasive smart environments. For this, ubiquitous computing technology is introduced to provide all users with any service, anytime, anywhere, with any device, and under any network. However, high cost, long time consumption, extensive effort, and in some cases irrevocability are the main challenges and difficulties for developing ubiquitous systems. Therefore, one solution is to initially simulate, analyze, and validate practices prior to deploying sensing and computational devices in the real world. Simulation, as a performance evaluation technique, has attracted attentions due to its speed, cost-effectiveness, repeatability, scalability, flexibility, and ease of implementation. Moreover, emulation, as a hybrid method, not only offers most simulation advantages but also benefits from tight control of implementation, as well as a certain degree of realistic results. Both simulators and emulators are significant tools for enhancing the understanding of ubiquitous sensor networks (USNs) through testing and analyzing several scenarios prior to actual sensor placements. In this regard, this paper surveys 130 simulation and emulation environments and frameworks, which were originally designed and adapted for USN. Of these 130, the 22 that have been widely used, regularly updated, and well supported by their developers are compared based on multifarious criteria. Finally, several studies that had favorably compared the performance of simulators and/or emulators are examined. We believe the present research findings will be helpful for students and researchers to pick an appropriate simulator/emulator, and for software developers and those who are keen on producing their own environment.

show abstract

Acoustic Underwater Channel and Network Simulator

Cited by 10 publications

References 10 publications

Underwater Direction of Arrival Estimation using Wideband Arrays of Opportunity

Underwater Direction of Arrival Estimation using Wideband Arrays of Opportunity

Underwater Acoustic Communication Receiver Using Deep Belief Network

Ubiquitous sensor network simulation and emulation environments: A survey

Contact Info

Product

Resources

About