Network Coding for Engineers
Language: English
Published by Wiley-IEEE Press, 2025
- Hardcover
- New

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- Title
- Network Coding for Engineers
- Author
- Médard, Muriel; Vasudevan, Vipindev Adat; Pedersen, Morten Videbæk; Duffy, Ken R.
- Publisher
- Wiley-IEEE Press
- Publication year
- 2025
- Condition
- New
- Binding
- Hardcover
- Language
- English
- ISBN 10
- 1394217277
- ISBN 13
- 9781394217274
Understand the fundamentals of network coding from an engineering perspective with this accessible guide
Network Coding is a method of increasing network throughput and efficiency by encoding and decoding transmitted data packets instead of simply forwarding them. It was mainly a body of information theory until the rise of random linear networking coding (RLNC), a method ideally suited to wireless networks and other cooperative environments. The ease of introducing network coding to legacy systems and the resulting gains in efficiency have made this a widely applied technology with the potential to revolutionize networked communications.
Network Coding for Engineers introduces the fundamentals of this exciting subject from an engineering perspective. Beginning with the basics, including step-by-step details for implementing network coding and current applications, it also highlights potential uses of network coding in the communications technologies of the future. The result is an innovative and accessible introduction to a subject quickly becoming indispensable.
Network Coding for Engineers readers will also find:
- A structure that facilitates gradual deepening of knowledge, ideal for students and new readers
- Follows a semester-long course curriculum structure, making it suitable for direct adaptation for academic purposes
- Detailed discussion of future applications in technology areas including post-quantum cryptography, 6G, and more
- Design principles for different network models, such as multi-path and mesh networks
Network Coding for Engineers is ideal for electrical engineering and computer science students, particularly those studying advanced networking and communications and related subjects.
"Synopsis" may belong to another edition of this title.
About the Author
Muriel Médard, PhD, is NEC Professor of Software Science and Engineering in the Electrical Engineering and Computer Science (EECS) Department and Head of the Network Coding and Reliable Communications Group in the Research Laboratory of Electronics at the Massachusetts Institute of Technology (MIT), USA. She is a member of the US National Academy of Engineering and a Fellow of the US National Academy of Inventors and the Institute of Electrical and Electronics Engineers, among other organizations, and is a past president of the IEEE Information Theory Society.
Vipindev Adat Vasudevan, PhD, is a Postdoctoral Associate in the Network Coding and Reliable Communications Group in the Research Laboratory of Electronics, Massachusetts Institute of Technology (MIT), USA. He has previously worked as an MSCA Fellow in the Wireless Telecommunications Laboratory of the University of Patras, Greece, and has researched extensively into network coding, network security, 5G, and related subjects.
Morten Videbæk Pedersen, PhD, is co-founder and Chief Technology Officer of Steinwurf APS, a company specializing in industrial-grade high-performance content distribution systems, where he focuses on low-complexity network coding algorithms and cooperative networking programs. He is a member of the Mobile Devices Research Group, Aalborg, Denmark, and a past recipient of the Forum Nokia Developer Champion Award.
Ken R. Duffy, PhD, is a Professor of Electrical and Computer Engineering, and a Professor of Mathematics, at Northeastern University (NU), USA. He leads the Engineering Probability Information and Communications Laboratory and is core faculty at NU’s Institute for the Wireless Internet of Things. He was previously the Director of the Hamilton Institute at the National University of Ireland, Maynooth, and a co-director of the Science Foundation Ireland Centre for Research Training in Foundations of Data Science.
"About the title" may belong to another edition of this title.
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