Le Liang

5.2k total citations · 3 hit papers
95 papers, 3.5k citations indexed

About

Le Liang is a scholar working on Electrical and Electronic Engineering, Computer Networks and Communications and Artificial Intelligence. According to data from OpenAlex, Le Liang has authored 95 papers receiving a total of 3.5k indexed citations (citations by other indexed papers that have themselves been cited), including 57 papers in Electrical and Electronic Engineering, 26 papers in Computer Networks and Communications and 18 papers in Artificial Intelligence. Recurrent topics in Le Liang's work include Advanced MIMO Systems Optimization (33 papers), Vehicular Ad Hoc Networks (VANETs) (16 papers) and Energy Harvesting in Wireless Networks (8 papers). Le Liang is often cited by papers focused on Advanced MIMO Systems Optimization (33 papers), Vehicular Ad Hoc Networks (VANETs) (16 papers) and Energy Harvesting in Wireless Networks (8 papers). Le Liang collaborates with scholars based in China, United States and United Kingdom. Le Liang's co-authors include Geoffrey Ye Li, Hao Ye, Wei Xu, Xiaodai Dong, Xuemin Shen, Haixia Peng, Chongtao Guo, JoonBeom Kim, Biing‐Hwang Juang and Guanding Yu and has published in prestigious journals such as Proceedings of the IEEE, Environmental Pollution and Proceedings of the Royal Society B Biological Sciences.

In The Last Decade

Le Liang

76 papers receiving 3.5k citations

Hit Papers

Low-Complexity Hybrid Precoding in Massive Multiuser MIMO... 2014 2026 2018 2022 2014 2019 2020 100 200 300 400 500

Peers — A (Enhanced Table)

Peers by citation overlap · career bar shows stage (early→late) cites · hero ref

Name h Career Trend Papers Cites
Le Liang China 22 2.8k 1.3k 625 512 286 95 3.5k
Junhui Zhao China 26 1.6k 0.6× 1.4k 1.1× 430 0.7× 388 0.8× 150 0.5× 117 2.4k
Haixia Peng China 20 1.2k 0.4× 1.2k 0.9× 389 0.6× 455 0.9× 188 0.7× 58 2.2k
Liping Qian China 37 3.1k 1.1× 2.6k 2.0× 588 0.9× 788 1.5× 127 0.4× 207 4.8k
Helin Yang China 30 2.3k 0.8× 908 0.7× 381 0.6× 659 1.3× 95 0.3× 110 3.0k
Shimin Gong China 25 2.2k 0.8× 1.7k 1.3× 473 0.8× 1.0k 2.0× 66 0.2× 137 3.6k
Chunguo Li China 35 3.0k 1.1× 1.8k 1.3× 397 0.6× 1.5k 2.8× 91 0.3× 277 4.2k
Xiangming Wen China 27 2.3k 0.8× 2.3k 1.7× 204 0.3× 470 0.9× 101 0.4× 367 3.6k
Fuqiang Liu China 24 1.6k 0.6× 1.2k 0.9× 227 0.4× 161 0.3× 220 0.8× 186 2.6k
Yang Cao China 29 1.7k 0.6× 1.5k 1.2× 173 0.3× 457 0.9× 108 0.4× 132 2.9k
Andreas Festag Germany 27 3.2k 1.2× 1.9k 1.5× 269 0.4× 154 0.3× 567 2.0× 106 3.7k

Countries citing papers authored by Le Liang

Since Specialization
Citations

This map shows the geographic impact of Le Liang's research. It shows the number of citations coming from papers published by authors working in each country. You can also color the map by specialization and compare the number of citations received by Le Liang with the expected number of citations based on a country's size and research output (numbers larger than one mean the country cites Le Liang more than expected).

Fields of papers citing papers by Le Liang

Since Specialization
Physical SciencesHealth SciencesLife SciencesSocial Sciences

This network shows the impact of papers produced by Le Liang. Nodes represent research fields, and links connect fields that are likely to share authors. Colored nodes show fields that tend to cite the papers produced by Le Liang. The network helps show where Le Liang may publish in the future.

Co-authorship network of co-authors of Le Liang

This figure shows the co-authorship network connecting the top 25 collaborators of Le Liang. A scholar is included among the top collaborators of Le Liang based on the total number of citations received by their joint publications. Widths of edges represent the number of papers authors have co-authored together. Node borders signify the number of papers an author published with Le Liang. Le Liang is excluded from the visualization to improve readability, since they are connected to all nodes in the network.

All Works

20 of 20 papers shown
1.
Zhang, Yanwen, et al.. (2025). A novel framework for vehicle charging pattern recognition and charging duration prediction based on EA-CAE and K-means clustering. Energy and AI. 22. 100599–100599. 1 indexed citations
2.
Ye, Hao, et al.. (2025). Power Allocation for Delay Optimization in Device-to-Device Networks: A Graph Reinforcement Learning Approach. IEEE Transactions on Vehicular Technology. 74(11). 17396–17412. 1 indexed citations
3.
Yi, Xinping, et al.. (2025). GRLinQ: A Hybrid Model/Data-Driven Spectrum Sharing Mechanism for Device-to-Device Communications. IEEE Transactions on Communications. 73(11). 11214–11229.
4.
Yang, Jie, et al.. (2025). Hybrid Beamforming Design for Bistatic Integrated Sensing and Communication Systems. IEEE Transactions on Communications. 73(11). 10360–10376. 1 indexed citations
5.
Zhang, Jing, et al.. (2025). Joint Deployment and Beamforming Design in Aerial RIS-Assisted MU-MISO Systems Using Deep Reinforcement Learning. IEEE Transactions on Vehicular Technology. 1–17.
6.
Liang, Le, Yuange Duan, Fan Song, et al.. (2025). Turning lances into shields: flower mantids stretch their raptorial forelegs to avert and deflect predator attack. Proceedings of the Royal Society B Biological Sciences. 292(2044). 20243081–20243081.
7.
Zhang, Hua, et al.. (2025). Task-Oriented Semantic Communication for Stereo-Vision 3D Object Detection. IEEE Transactions on Communications. 73(9). 7552–7567.
8.
Yang, Jie, et al.. (2024). ISAC Prototype System for Multi-Domain Cooperative Communication Networks. IEEE Wireless Communications Letters. 14(1). 108–112. 3 indexed citations
9.
Liang, Le, et al.. (2024). Near-Optimal MIMO Detection Using Gradient-Based MCMC in Discrete Spaces. IEEE Transactions on Signal Processing. 73. 584–600.
10.
Zhang, Hengxi, Le Liang, Ling Cheng, et al.. (2024). A Scalable Mean-Field MARL Framework for Multi-Objective V2X Resource Allocation. IEEE Transactions on Intelligent Vehicles. 10(2). 1071–1086. 3 indexed citations
11.
Wang, Zheng, Le Liang, Shanxiang Lyu, et al.. (2024). Efficient Statistical Linear Precoding for Downlink Massive MIMO Systems. IEEE Transactions on Wireless Communications. 23(10). 14805–14818.
12.
Yang, Jie, et al.. (2024). Multi-modal fusion for sensing-aided beam tracking in mmWave communications. Physical Communication. 67. 102514–102514.
13.
Liang, Le, et al.. (2024). Mini-Batch Gradient-Based MCMC for Decentralized Massive MIMO Detection. IEEE Transactions on Communications. 73(1). 677–692. 2 indexed citations
14.
Jin, Shi, et al.. (2023). Online Energy Consumption Optimization in WPCNs With Time-Varying Energy Storage Efficiency. IEEE Transactions on Communications. 71(3). 1771–1784. 3 indexed citations
15.
Liang, Le, et al.. (2023). Gradient-Based Markov Chain Monte Carlo for MIMO Detection. IEEE Transactions on Wireless Communications. 23(7). 7566–7581. 5 indexed citations
16.
Jin, Shi, et al.. (2023). Cooperative Distributed Resource Allocation in Heterogeneous Networks With D2D Communication. IEEE Transactions on Vehicular Technology. 72(12). 16426–16440. 8 indexed citations
17.
Guo, Chongtao, Songtao Liu, Bin Liao, Zhigang Wang, & Le Liang. (2023). AoI-Driven Power Allocation and Batch Sampling Control for V2V Status Update Communications. IEEE Transactions on Industrial Informatics. 20(1). 291–302. 2 indexed citations
18.
Gao, Ning, Le Liang, Donghong Cai, Xiao Li, & Shi Jin. (2022). Coverage Control for UAV Swarm Communication Networks: A Distributed Learning Approach. IEEE Internet of Things Journal. 9(20). 19854–19867. 36 indexed citations
19.
Ye, Hao, Le Liang, & Geoffrey Ye Li. (2022). Decentralized Federated Learning With Unreliable Communications. IEEE Journal of Selected Topics in Signal Processing. 16(3). 487–500. 108 indexed citations
20.
Liang, Le, et al.. (2019). A SEMG-angle model based on HMM for human robot interaction. Technology and Health Care. 27(1_suppl). 383–395. 2 indexed citations

Rankless uses publication and citation data sourced from OpenAlex, an open and comprehensive bibliographic database. While OpenAlex provides broad and valuable coverage of the global research landscape, it—like all bibliographic datasets—has inherent limitations. These include incomplete records, variations in author disambiguation, differences in journal indexing, and delays in data updates. As a result, some metrics and network relationships displayed in Rankless may not fully capture the entirety of a scholar's output or impact.

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