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Siming Liu

Researcher at Georgia Institute of Technology

Publications -  18
Citations -  309

Siming Liu is an academic researcher from Georgia Institute of Technology. The author has contributed to research in topics: Transmission (telecommunications) & Fading. The author has an hindex of 9, co-authored 18 publications receiving 200 citations. Previous affiliations of Siming Liu include Nanjing University & Beijing University of Posts and Telecommunications.

Papers
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Journal ArticleDOI

A Multilevel Artificial Neural Network Nonlinear Equalizer for Millimeter-Wave Mobile Fronthaul Systems

TL;DR: The proposed and validated complex-valued multilevel artificial neural network nonlinear equalizer (ANN-NLE) for single-carrier 16QAM and 64QAM signals transmissions in the 60-GHz radio-over-fiber (RoF) transmission system has a great tolerance to phase rotations and is able to minimize the nonlinear compression in an RoF system.
Journal ArticleDOI

An Ultra-Reliable MMW/FSO A-RoF System Based on Coordinated Mapping and Combining Technique for 5G and Beyond Mobile Fronthaul

TL;DR: It is demonstrated experimentally that the proposed CMC improves power margins and enhances the robustness of the adaptive diversity combining technique (ADCT)-based FSO/MMW links by mitigating system impairments caused by frequency/time burst interference and power fading attributable to adverse weather conditions.
Proceedings ArticleDOI

Accurate Indoor Visible Light Positioning System utilizing Machine Learning Technique with Height Tolerance

TL;DR: An accurate, low-cost indoor visible light positioning system utilizing machine learning technique is proposed and experimentally demonstrated.
Journal ArticleDOI

$4\times100$ -Gb/s PAM-4 FSO Transmission Based on Polarization Modulation and Direct Detection

TL;DR: In this article, the first experimental demonstration of a 400-Gb/s FSO system using the polarization modulation (PolM) and direct detection (DD) scheme with the transmission distance of 1.2 m is presented.
Proceedings ArticleDOI

Real-Time Demonstration of Adaptive Functional Split in 5G Flexible Mobile Fronthaul Networks

TL;DR: A flexible and reconfigurable Fronthaul-I with analog RoF integration that aims to optimally serve different 5G applications to reduce the latency by more than %15 to support URLLC applications is experimentally demonstrated.