H-Index & Metrics Best Publications

H-Index & Metrics

Discipline name H-index Citations Publications World Ranking National Ranking
Electronics and Electrical Engineering D-index 31 Citations 4,956 187 World Ranking 3310 National Ranking 386

Overview

What is he best known for?

The fields of study he is best known for:

  • Artificial intelligence
  • Statistics
  • Machine learning

Guan Gui mostly deals with Artificial intelligence, Deep learning, Wireless, Communication channel and Algorithm. His studies in Artificial intelligence integrate themes in fields like Communications system, Modulation and Pattern recognition. The Deep learning study combines topics in areas such as Computer engineering, Artificial neural network, MIMO, Spectral efficiency and Key.

Guan Gui has researched Wireless in several fields, including Telecommunications network, Computer network and Base station. His Communication channel research focuses on Bandwidth and how it connects with Macrocell, Root mean square, Microcell and Transmitter. His Algorithm study integrates concerns from other disciplines, such as Channel state information and Mathematical optimization.

His most cited work include:

  • Deep Learning for Super-Resolution Channel Estimation and DOA Estimation Based Massive MIMO System (258 citations)
  • Deep Learning for an Effective Nonorthogonal Multiple Access Scheme (191 citations)
  • Data-Driven Deep Learning for Automatic Modulation Recognition in Cognitive Radios (189 citations)

What are the main themes of his work throughout his whole career to date?

His primary scientific interests are in Algorithm, Artificial intelligence, Communication channel, Compressed sensing and Deep learning. The various areas that Guan Gui examines in his Algorithm study include Mean squared error and Mathematical optimization. His Artificial intelligence research includes themes of Machine learning, Computer vision and Pattern recognition.

The concepts of his Communication channel study are interwoven with issues in Wireless and Electronic engineering. His study explores the link between Wireless and topics such as Base station that cross with problems in Telecommunications link. The study incorporates disciplines such as Feature extraction, Computer engineering, Modulation and Communications system in addition to Deep learning.

He most often published in these fields:

  • Algorithm (39.59%)
  • Artificial intelligence (28.17%)
  • Communication channel (26.90%)

What were the highlights of his more recent work (between 2020-2021)?

  • Artificial intelligence (28.17%)
  • Base station (4.06%)
  • Deep learning (15.99%)

In recent papers he was focusing on the following fields of study:

His primary areas of study are Artificial intelligence, Base station, Deep learning, Artificial neural network and Resource allocation. His Artificial intelligence research incorporates themes from Machine learning and Pattern recognition. His Base station study combines topics from a wide range of disciplines, such as Wireless, Transmitter power output, Communications system, Efficient energy use and Telecommunications link.

His Telecommunications link research is multidisciplinary, incorporating perspectives in MIMO, Electronic engineering and User equipment. His studies deal with areas such as Ground truth, Feature extraction, Convolutional neural network and Feature as well as Deep learning. He combines subjects such as Channel state information and Communication channel with his study of Artificial neural network.

Between 2020 and 2021, his most popular works were:

  • Hybrid Deep Learning for Botnet Attack Detection in the Internet-of-Things Networks (4 citations)
  • CV-3DCNN: Complex-Valued Deep Learning for CSI Prediction in FDD Massive MIMO Systems (4 citations)
  • Multiple Unmanned-Aerial-Vehicles Deployment and User Pairing for Nonorthogonal Multiple Access Schemes (4 citations)

In his most recent research, the most cited papers focused on:

  • Artificial intelligence
  • Statistics
  • Machine learning

Guan Gui mainly focuses on Artificial intelligence, Machine learning, Quality of service, Deep learning and Resource allocation. As part of his studies on Artificial intelligence, Guan Gui often connects relevant areas like Trajectory. His work deals with themes such as Distributed computing, Efficient energy use, Spectral efficiency and Service, which intersect with Quality of service.

His Spectral efficiency study frequently links to other fields, such as Wireless. His Deep learning research is multidisciplinary, incorporating elements of Feature extraction and Convolutional neural network. His studies in Resource allocation integrate themes in fields like Macrocell, Relay, Resource, Noma and Heterogeneous network.

This overview was generated by a machine learning system which analysed the scientist’s body of work. If you have any feedback, you can contact us here.

Best Publications

Deep Learning for Super-Resolution Channel Estimation and DOA Estimation Based Massive MIMO System

Hongji Huang;Jie Yang;Hao Huang;Yiwei Song.
IEEE Transactions on Vehicular Technology (2018)

421 Citations

Data-Driven Deep Learning for Automatic Modulation Recognition in Cognitive Radios

Yu Wang;Miao Liu;Jie Yang;Guan Gui.
IEEE Transactions on Vehicular Technology (2019)

332 Citations

Deep Learning for an Effective Nonorthogonal Multiple Access Scheme

Guan Gui;Hongji Huang;Yiwei Song;Hikmet Sari.
IEEE Transactions on Vehicular Technology (2018)

310 Citations

Deep-Learning-Based Millimeter-Wave Massive MIMO for Hybrid Precoding

Hongji Huang;Yiwei Song;Jie Yang;Guan Gui.
IEEE Transactions on Vehicular Technology (2019)

238 Citations

Caching UAV Assisted Secure Transmission in Hyper-Dense Networks Based on Interference Alignment

Nan Zhao;Fen Cheng;F. Richard Yu;Jie Tang.
IEEE Transactions on Communications (2018)

201 Citations

6G: Opening New Horizons for Integration of Comfort, Security, and Intelligence

Guan Gui;Miao Liu;Fengxiao Tang;Nei Kato.
IEEE Wireless Communications (2020)

188 Citations

Deep Cognitive Perspective: Resource Allocation for NOMA-Based Heterogeneous IoT With Imperfect SIC

Miao Liu;Tiecheng Song;Guan Gui.
IEEE Internet of Things Journal (2019)

181 Citations

Maximum correntropy criterion based sparse adaptive filtering algorithms for robust channel estimation under non-Gaussian environments

Wentao Ma;Hua Qu;Guan Gui;Li Xu.
Journal of The Franklin Institute-engineering and Applied Mathematics (2015)

149 Citations

Deep Learning-Inspired Message Passing Algorithm for Efficient Resource Allocation in Cognitive Radio Networks

Miao Liu;Tiecheng Song;Jing Hu;Jie Yang.
IEEE Transactions on Vehicular Technology (2019)

136 Citations

UAV-Relaying-Assisted Secure Transmission With Caching

Fen Cheng;Guan Gui;Nan Zhao;Yunfei Chen.
IEEE Transactions on Communications (2019)

117 Citations

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Best Scientists Citing Guan Gui

Yingsong Li

Yingsong Li

Harbin Engineering University

Publications: 53

Dusit Niyato

Dusit Niyato

Nanyang Technological University

Publications: 36

Nan Zhao

Nan Zhao

Dalian University of Technology

Publications: 34

Badong Chen

Badong Chen

Xi'an Jiaotong University

Publications: 32

Zhiguo Ding

Zhiguo Ding

University of Manchester

Publications: 30

Zhu Han

Zhu Han

University of Houston

Publications: 21

Haiquan Zhao

Haiquan Zhao

Southwest Jiaotong University

Publications: 20

Arumugam Nallanathan

Arumugam Nallanathan

Queen Mary University of London

Publications: 19

H. Vincent Poor

H. Vincent Poor

Princeton University

Publications: 18

Shi Jin

Shi Jin

Southeast University

Publications: 16

Yuanwei Liu

Yuanwei Liu

Queen Mary University of London

Publications: 16

Zhangdui Zhong

Zhangdui Zhong

Beijing Jiaotong University

Publications: 15

Linglong Dai

Linglong Dai

Tsinghua University

Publications: 15

Octavia A. Dobre

Octavia A. Dobre

Memorial University of Newfoundland

Publications: 15

Bhim Singh

Bhim Singh

Indian Institute of Technology Delhi

Publications: 14

Bo Ai

Bo Ai

Beijing Jiaotong University

Publications: 14

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