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Creators/Authors contains: "Yu, Jiakai"

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  1. null (Ed.)
  2. Innovation in optical networks is essential to delivering advanced performance for future smart city and wireless networks. Incorporating optical systems research in real-world platforms presents a number of challenges, which are addressed through recent advances in the use of software defined networking and emulation. 
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  3. We analyze an optical control plane algorithm designed to operate in real-time to improve generalized-optical signal-to-noise ratio (gOSNR) quality-of-transmission-estimation (QoT-E), based on OSNR monitoring. We report QoT-E performance improvements of up to 1 dB. 
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  4. A hybrid machine learning (HML) model combining a-priori and a-posteriori knowledge is implemented and tested, which is shown to reduce the prediction error and training complexity, compared to an analytical or neural network learning model. 
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  5. Abstract: A hybrid machine learning (HML) model combining a-priori and a-posteriori knowledge is implemented and tested, which is shown to reduce the prediction error and training complexity, compared to an analytical or neural network learning model. 
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  6. Abstract: We investigate dynamic network resource allocation using software-defined networking optical controller with software-defined radios on the COSMOS testbed. 10 Gb/s capacity, deterministic low latency are maintained through user equipment wireless handover via optical switching. 
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  7. We investigate dynamic network resource allocation using software-defined networking optical controller with software-defined radios on the COSMOS testbed. 10 Gb/s capacity, deterministic low latency are maintained through user equipment wireless handover via optical switching. © 2020 The Author(s) OCIS codes: 060.4256, 060.0060. 
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