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Junlian Jia

dblp:216/2674 · DBLP profile ↗
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2ranked-venue papers
1as first author
2since 2021 · last 2023
0000-0001-8878-7423ORCID · corroborated

Domains — the database's venue-derived domains; a paper can count in several

Computer networks · 1 · 1 since 2021Applied, interdisciplinary, general and emerging computing · 1 · 1 first-author · 1 since 2021

Expertise — from the expertise taxonomy: the topics of the expert's papers under the CCF categories. A weight counts papers with recency: 1 for a paper about the topic, 0.3 when the topic is its context, halved every five years.

Computer networks
1 paper
Physical-layer communications · 92% Optical networks · 8%

Topics — the 5 heaviest of 5, each with the papers that count most for it

TopicWeightPapersLastEvidence papers
Physical-layer communications › modulation › constellation design
constellation shaping
0.712023
Constellation shaping optimization for nonlinearity mitigation in CAP UVLC system · Sci. China Inf. Sci. 2023
Physical-layer communications
modulation
0.712023
Constellation shaping optimization for nonlinearity mitigation in CAP UVLC system · Sci. China Inf. Sci. 2023
Physical-layer communications › receiver design › RF impairment compensation
nonlinear distortion compensation
0.712023
Constellation shaping optimization for nonlinearity mitigation in CAP UVLC system · Sci. China Inf. Sci. 2023
Optical networks
optical access network
0.212023
Constellation shaping optimization for nonlinearity mitigation in CAP UVLC system · Sci. China Inf. Sci. 2023
Physical-layer communications › optical wireless communication
visible light communication
0.212023
Constellation shaping optimization for nonlinearity mitigation in CAP UVLC system · Sci. China Inf. Sci. 2023

Methods — techniques the papers use, named apart from their topics

constellation shaping optimization · 0.7
YearPublicationVenuePosition
2023 Constellation shaping optimization for nonlinearity mitigation in CAP UVLC system
Junlian Jia, Junwen Zhang 0001, Nan Chi
Sci. China Inf. Sci.1
2022 Position-Dependent MIMO Demultiplexing Strategy for High-Speed Visible Light Communication in Internet of Vehicles
abstract
The context of the Internet of Vehicles (IoV) and the growing vehicular deployment of sensors and smart devices have demanded alternative wireless communication technologies. Despite the prevalent works on radio-frequency (RF)-based vehicular communication technologies, visible-light communication (VLC) is envisaged to be a promising candidate due to its unlicensed spectrum and high transmission rates. However, the long-distance and high-speed transmission performance of vehicular VLC needs more investigation considering the massive data transmission needs for automotive applications. In this article, a vehicular multiple-input–multiple-output (MIMO) VLC system based on two commercial headlights and a self-designed PIN array is experimentally demonstrated as a proof of concept for the IoV. Considering the relative movement of vehicles, different communication areas are divided based on the position-dependent receiver receiving states. The boundary condition of each area is derived. For the first time, the selection of the strategy that best suits the MIMO demultiplexing scheme is discussed by analyzing the rank and type of the channel matrix. A modified pilot-aided phase recovery method based on polynomial curve fitting (PCF) is proposed to compensate for the phase noise caused by the sampling frequency offset (SFO). The proposed method maintains good robustness even when the VLC system suffers from the strong nonlinearity and bandwidth limitation of the headlights. Based on the proposed MIMO VLC system, we achieve a record-breaking data rate of 3.08 Gb/s at a 2-m indoor transmission link. We further extend the transmission distance to 100 m, and successfully achieve overall data rates of 336 and 362 Mb/s during the daytime and nighttime, respectively. To the best of our knowledge, these are the highest transmission data rates ever reported for a 100-m vehicular VLC system. Our experimental demonstration clearly verifies the feasibility of VLC in the application of IoV.
Guoqiang Li 0010, Wenqing Niu, Yinaer Ha, Fangchen Hu, Jie Wang 0077, Junlian Jia, Zhixue He, Shaohua Yu, Nan Chi
IEEE Internet Things J.7