Conference Proceedings

Neural networks and FPGA hardware accelerators for millimeter-wave radio-over-fiber systems

J Lee, J He, K Wang

International Conference on Transparent Optical Networks | Published : 2020

Abstract

High speed data streaming has been highly demanded by mobile end users and millimetre-wave (mm-wave) radio-over-fiber (RoF) optical communications have been studied to satisfy the users' demands. To solve various impairments existing in mm-wave RoF systems, neural networks have been proposed and studied due to their capability in solving nonlinear effects and multiple impairments simultaneously. However, previous studies mainly focused on the fully-connected neural network (FC-NN), which has relatively complicated architecture and a large number of parameters to be learnt. To solve this issue, we have proposed the convolutional neural network (CNN) and binary convolutional neural network (BC..

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University of Melbourne Researchers

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