Journal article

FPGA-based neural network accelerators for millimeter-wave radio-over-fiber systems.

Jeonghun Lee, Jiayuan He, Ke Wang

Optics Express | Optical Society of America (OSA) | Published : 2020

Abstract

With rapidly developing high-speed wireless communications, the 60 GHz millimeter-wave (mm-wave) frequency range has attracted extensive interests, and radio-over-fiber (RoF) systems have been widely investigated as a promising solution to deliver mm-wave signals. Neural networks have been proposed and studied to improve the mm-wave RoF system performances at the receiver side by suppressing both linear and nonlinear impairments. However, previous studies of neural networks in mm-wave RoF systems all focus on the use of off-line processing with high-end GPUs or CPUs, which are not practical for low power-consumption, low-cost and limited computation platform applications. To solve this issue..

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University of Melbourne Researchers