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Advanced Fiber Access Networks

  • Book

  • August 2022
  • Elsevier Science and Technology
  • ID: 5527305

Advanced Fiber Access Networks takes a holistic view of broadband access networks-from architecture to network technologies and network economies. The book reviews pain points and challenges that broadband service providers face (such as network construction, fiber cable efficiency, transmission challenges, network scalability, etc.) and how these challenges are tackled by new fiber access transmission technologies, protocols and architecture innovations. Chapters cover fiber-to-the-home (FTTH) applications as well as fiber backhauls in other access networks such as 5G wireless and hybrid-fiber-coax (HFC) networks.� In addition, it covers the network economy, challenges in fiber network construction and deployment, and more.

Finally, the book examines scaling issues and bottlenecks in an end-to-end broadband network, from Internet backbones to inside customer homes, something rarely covered in books.

Please Note: This is an On Demand product, delivery may take up to 11 working days after payment has been received.

Table of Contents

1. Introduction
2. Advanced PON standards: 10G, 25G, 50G, 100G and beyond
3. WDM in fiber access networks
4. Coherent PON networks
5. Optoelectronic technologies and implementation challenges for next generation PONs
6. DSP in fiber access networks
7. End-to-end fiber access system & network scaling
8. Converged fiber/wireless networks

Authors

Cedric F. Lam Principal Engineer, Google LLC, Mountain View, CA, USA. Cedric Lam was co-founder of Google Fiber which changed the landscape of broadband access networks in North America with the introduction of nationwide Gigabit FTTH networks. Cedric has experience both in product development and in engineering service provider networks. He started his career with AT&T and later joined Opvista, a startup company building high-capacity optical transport equipment, as chief system architect. After Opvista, he joined Google to work on datacenter networks before embarking the effort on Google Fiber, where he was Engineering Director, leading the Architecture and Device Engineering team. He is now Principal Engineer in Google's Technical Infrastructure team, leading the development of datacenter network architectures and the development of network generation optical interconnects for datacenter networks. Cedric is a member of the CORD Technical Steering Team, and Fellow of Optica. He also edited the first textbook in PON: Passive Optical Networks, Principles and Practice, Academic Press, 2007. Shuang Yin Staff Hardware Engineer, Google LLC, Mountain View, CA, USA. Shuang Yin is a staff hardware engineer at Google, working on optical technologies for machine learning applications. Prior to this, he was a senior hardware engineer at Google Fiber, where he was involved in developing next generation fiber access technologies and the metro transport network architecture for Fiber-to-the-Home networks. Shuang's research covers optical access network architectures, advanced modulation formats, and digital signal processing in high-speed optical communication systems. He received M.S. and Ph.D. degrees in Electrical Engineering from Stanford University. Tao Zhang Senior Hardware Engineer, Argo AI, Palo Alto, CA, USA. Tao Zhang is a Senior Hardware Engineer at Argo AI, where he is working on the hardware development for Argo AI's autonomous driving technologies. Prior to Argo AI, Tao was with Google. He was a hardware engineer at Google Fiber, designing next generation tunable optical transceivers, and a researcher at Google AI, working on the edge-TPU product development and doing research on machine learning hardware. Tao has experience on both transistor-level and board-level circuit/hardware designs. Before joining Google, he spent 10 years at several companies and institutions, including VIA technologies, LSI corporation and CERN, working on Integrated Circuit Design and Verification. His research interests are high-speed circuit design and machine learning hardwares.