Chen  Gong

Prof. Dr. Chen Gong

Department of Electronic and Information Science, University of Science and Technology of China, Hefei 230026, China

Research Focus & Metrics

Academic Career Length

17Years (2010-Present)

(Calculated once Scilit publication data is synced: current year − year of first publication + 1)

Representative Publications

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21 December 2016 in IEEE Communications Letters
Verified
Journal Article
Closed access
XZXiaoke Zhang
Xiaoke Zhang
QGQian Gao
Qian Gao
Chen  GongChen Gong
Chen Gong
ZXZhengyuan Xu
Zhengyuan Xu
To design an efficient multiple access scheme for visible light communication (VLC) multi-cell networks, this letter leverages the non-orthogonal multiple access (NOMA), which has received significant attention in the 5th generation wireless communication. A user grouping based on user locations is proposed to reduce interference for VLC multi-cell networks. With the residual interference from the successive interference cancellation in NOMA taken into account, we optimize the power allocation within each cell to improve the achievable user rate under user quality of service constraint. The performance of the proposed approaches is evaluated by the numerical results.

25 April 2024 in Nature Electronics
Verified
Journal Article
Closed access
PDF file
Muhammad Hunain MemonMuhammad Hunain Memon
Muhammad Hunain Memon
HYHuabin Yu
Huabin Yu
YLYuanmin Luo
Yuanmin Luo
YKYang Kang
Yang Kang
WCWei Chen
Wei Chen
Haiding SunHaiding Sun
Haiding Sun

22 January 2021 in IEEE Transactions on Geoscience and Remote Sensing
Verified
Journal Article
Closed access
LWLi Wang
Li Wang
XBXueru Bai
Xueru Bai
Chen  GongChen Gong
Chen Gong
FZFeng Zhou
Feng Zhou
Synthetic aperture radar (SAR) automatic target recognition (ATR) plays an important role in SAR image interpretation. However, at least hundreds of training samples are usually required for each target type in the existing SAR ATR algorithms. In this article, a novel few-shot learning framework named hybrid inference network (HIN) is proposed to tackle the problem of SAR target recognition with only a few training samples. The recognition procedure of HIN consists of two main stages. In the first stage, an embedding network is utilized to map the SAR images into an embedding space. In the second stage, a hybrid inference strategy that combines the inductive inference and the transductive inference is adopted to classify the samples in the embedding space. In the inductive inference section, each sample is recognized independently according to a metric based on Euclidean distance. In the transductive inference section, all samples are recognized as a whole according to their manifold structures by label propagation. Finally, in the hybrid inference section, the classification result is obtained by combining the above two inference methods. To train the framework more effectively, a novel loss function named enhanced hybrid loss is proposed to constrain samples to gain better interclass separability in the embedding space. Experimental results on the moving and stationary target acquisition and recognition (MSTAR) benchmark data set illustrate that HIN performs well in few-shot SAR image classification.

6 April 2018 in IEEE Photonics Journal
Verified
Journal Article
Open access
GWGuanchu Wang
Guanchu Wang
KWKun Wang
Kun Wang
Chen  GongChen Gong
Chen Gong
DZDifan Zou
Difan Zou
ZJZhimeng Jiang
Zhimeng Jiang
ZXZhengyuan Xu
Zhengyuan Xu
In the nonline of sight (NLOS) ultraviolet (UV) scattering communication, the received signals exhibit the characteristics of discrete photoelectrons due to the extremely large path loss. We design and demonstrate an NLOS UV scattering communication system in this paper, where the receiver-side signal detection is designed based on a discrete-time Poisson channel model. In our system, a laser and multiple photomultiplier tubes are employed as the optical transmitter and detector, respectively. Furthermore, we design algorithms for pulse-counting, synchronization, channel estimation, and LLR computation for hardware realization in field-programmable gate array board. Simulation results are provided to evaluate the proposed system design and specify the system key parameters for real-time implementation. We perform field tests for real-time communication with the transmission range over 1 km, where the system throughput reaches 1 Mbps.

23 January 2023 in IEEE Electron Device Letters
Verified
Journal Article
Closed access
Muhammad Hunain MemonMuhammad Hunain Memon
Muhammad Hunain Memon
HYHuabin Yu
Huabin Yu
HJHongfeng Jia
Hongfeng Jia
SFShi Fang
Shi Fang
DWDanhao Wang
Danhao Wang
Haiding SunHaiding Sun
Haiding Sun
Optical wireless communication (OWC) systems are emerging as a crucial technique for the development of next-generation data transmission and acquisition, with a particular interest in the solar-blind deep-ultraviolet (DUV) as well as visible-light (VL) band, owing to their superior advantages in either free space or underwater application scenarios. A light-emitting device, which normally acts as a signal transmitter in OWC, capable of generating dual wavelengths, would certainly expand the capacity and functionality of OWC. Herein, we propose to vertically integrate DUV micro-LED-array with CdSe/ZnS blue color quantum dots to emit dual wavelengths, and strikingly, the device exhibits a bandwidth of 254 and 36 MHz and obtained the data rate of 586 and 55 Mbps using the on–off keying (OOK) modulation scheme, at the emission of 275 and 470 nm, respectively. Importantly, the associated bit error rate is under the forward error correction threshold, indicating the feasibility of implementing this low-cost and compact device for practical solar-blind and VL dual-band communication, i.e., in marine science and ocean exploration.

29 November 2018 in IEEE Transactions on Communications
Verified
Journal Article
Closed access
DZDifan Zou
Difan Zou
Chen  GongChen Gong
Chen Gong
KWKun Wang
Kun Wang
ZXZhengyuan Xu
Zhengyuan Xu