Advanced Fiber Access Networks. Questo articolo non è disponibile.
Lingua: inglese
Editore: Academic Press, 2022
- Brossura
- Nuovo

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Codice articolo a7daaee23a74fa12fc0f3d523c985288
- Titolo
- Advanced Fiber Access Networks
- Autore
- Lam
- Editore
- Academic Press
- Anno di pubblicazione
- 2022
- Condizione
- new
- Rilegatura
- Brossura
- Lingua
- inglese
- ISBN 10
- 0323854990
- ISBN 13
- 9780323854993
- Peso dell'articolo
- 0,51 chilogrammi
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.
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Informazioni sull’autore
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 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.
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