Next Generation Marine Wireless Communication Networks

1. Front Matter

   Pages i-xiv

   PDF

2. Introduction

   • Bin Lin, Jianli Duan, Mengqi Han, Lin X. Cai

   Pages 1-31

3. Topology Optimization of MWCN

   • Bin Lin, Jianli Duan, Mengqi Han, Lin X. Cai

   Pages 33-58

4. Autoencoder with Channel Estimation for Marine Communications

   • Bin Lin, Jianli Duan, Mengqi Han, Lin X. Cai

   Pages 59-82

5. Decentralized Reinforcement Learning-Based Access Control for Energy Sustainable Underwater Acoustic Sub-Network of MWCN

   • Bin Lin, Jianli Duan, Mengqi Han, Lin X. Cai

   Pages 83-106

6. Opportunistic Routing with Q-Learning for Marine Wireless Sensor Networks

   • Bin Lin, Jianli Duan, Mengqi Han, Lin X. Cai

   Pages 107-138

7. Conclusions and Future Directions

   • Bin Lin, Jianli Duan, Mengqi Han, Lin X. Cai

   Pages 139-143

8. Back Matter

   Pages 145-148

   PDF

This book presents a novel framework design for  the next generation Marine Wireless Communication Networks (MWCNs). The authors first provide an overview of MWCNs, followed by a discussion of challenges in the design and development of MWCNs in support of a diversity of marine services such as real-time marine monitoring, offshore oil exploration, drilling, marine tourism and fishing. The authors then propose cross layer networking solutions to achieve a high performance modern MWCN that enables efficient and reliable data transmissions under hostile marine environment, which include the network deployment, the physical layer channel coding, intelligent network access and resource management, and learning-based opportunistic routing. Finally, the authors summarize the book and present some open issues that will lead to new research directions in the next generation MWCNs.

• next generation marine wireless communication networks
• smart ocean
• network architecture
• topology optimization
• heuristic algorithms
• autoencoder
• orthogonal frequency division multiplexing
• energy harvesting

• School of Information Science and Tech, Dalian Maritime University, Dalian, China

  Bin Lin

• School of Science, Qingdao University of Technology, Qingdao, China

  Jianli Duan

• Illinois Institute of Technology, Chicago, USA

  Mengqi Han, Lin X. Cai

Bin Lin is a professor and Dean of Communication Engineering Department, School of Information Science and Technology, Dalian Maritime University. Her research interests include wireless communications, network dimensioning and optimization, resource allocation, artificial intelligence, maritime communication networks, edge/cloud computing, wireless sensor networks, and Internet of Things. She received the B.S. and M.S. degrees from Dalian Maritime University, Dalian, China, in 1999 and 2003 respectively, and the Ph.D. degree from the Broadband Communications Research Group, Department of Electrical and Computer Engineering, University of Waterloo, Waterloo, ON, Canada, in 2009. She has been a Visiting Scholar with George Washington University, Washington, DC, USA, from 2015 to 2016. She is the editor of IEEE TVT and IET Communications. She has authored/coauthored around 70 journal papers and 40 technical papers in conference proceedings. She served as a TPC member for IEEE Globecom, ICC, WCNC, and the technical reviewer for multiple IEEE Transactions including TMC, TVT, TWC, and ITS.

Jianli Duan received the M.S. and Ph.D. degrees from Dalian Maritime University, Dalian, Liaoning Province, China, in 2003 and 2020, respectively. She is currently a teacher at Qingdao University of Technology, Qingdao, Shandong Province, China. Her research direction is maritime telecommunications and networking, wireless sensor networks, and network planning and optimization.

Mengqi Han received the B.S degree from the Department of Electronic and information, Nanjing University of Science and Technology, Nanjing, China, in 2013. And she received the M.S  and the Ph.D degree from the Department of Electrical and Computer Engineering in Illinois Institute of Technology, in 2015 and 2020 respectively. Her research interests include performance analysis of MAC protocol and protocol design for next-generation wireless networks, wireless networks resource management, reinforcement learning, and deep learning.

 

Lin X. Cai received the M.A.Sc. and Ph.D. degrees in Electrical and Computer Engineering from the University of Waterloo, Waterloo, Canada, in 2005 and 2010, respectively. She is currently an Associate Professor with the Department of Electrical and Computer Engineering, Illinois Institute of Technology, Chicago, Illinois, USA. Her research interests include green communication and networking, intelligent radio resource management, and wireless Internet of Things. She received a Postdoctoral Fellowship Award from the Natural Sciences and Engineering Research Council of Canada (NSERC) in 2010, a Best Paper Award from the IEEE Globecom 2011, an NSF Career Award in 2016, and the IIT Sigma Xi Research Award in the Junior Faculty Division in 2019. She is an Associate Editor of IEEE Transaction on Wireless Communications, IEEE Network Magazine, and a co-chair for IEEE conferences. 

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