Yan Kyaw Tun

2.3k total citations · 1 hit paper
67 papers, 1.6k citations indexed

About

Yan Kyaw Tun is a scholar working on Aerospace Engineering, Electrical and Electronic Engineering and Computer Networks and Communications. According to data from OpenAlex, Yan Kyaw Tun has authored 67 papers receiving a total of 1.6k indexed citations (citations by other indexed papers that have themselves been cited), including 35 papers in Aerospace Engineering, 35 papers in Electrical and Electronic Engineering and 33 papers in Computer Networks and Communications. Recurrent topics in Yan Kyaw Tun's work include UAV Applications and Optimization (24 papers), Advanced Wireless Communication Technologies (22 papers) and IoT and Edge/Fog Computing (16 papers). Yan Kyaw Tun is often cited by papers focused on UAV Applications and Optimization (24 papers), Advanced Wireless Communication Technologies (22 papers) and IoT and Edge/Fog Computing (16 papers). Yan Kyaw Tun collaborates with scholars based in South Korea, United States and Denmark. Yan Kyaw Tun's co-authors include Choong Seon Hong, Zhu Han, Shashi Raj Pandey, Nguyen H. Tran, Yu Min Park, Madyan Alsenwi, Walid Saad, Aunas Manzoor, Mehdi Bennis and Sheikh Salman Hassan and has published in prestigious journals such as IEEE Access, IEEE Journal on Selected Areas in Communications and IEEE Transactions on Wireless Communications.

In The Last Decade

Yan Kyaw Tun

63 papers receiving 1.6k citations

Hit Papers

A Crowdsourcing Framework for On-Device Federated Learning 2020 2026 2022 2024 2020 50 100 150 200

Peers — A (Enhanced Table)

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

Name h Career Trend Papers Cites
Yan Kyaw Tun South Korea 24 819 637 609 512 207 67 1.6k
Shashi Raj Pandey South Korea 16 552 0.7× 453 0.7× 195 0.3× 486 0.9× 141 0.7× 38 1.1k
Xiumin Wang China 19 658 0.8× 645 1.0× 96 0.2× 443 0.9× 253 1.2× 81 1.6k
Yuben Qu China 19 568 0.7× 338 0.5× 424 0.7× 283 0.6× 95 0.5× 72 1.0k
Alia Asheralieva China 20 787 1.0× 459 0.7× 196 0.3× 276 0.5× 314 1.5× 65 1.2k
Jianfeng Guan China 20 1.4k 1.7× 652 1.0× 69 0.1× 343 0.7× 217 1.0× 148 1.9k
Zengbin Zhang United States 16 585 0.7× 783 1.2× 111 0.2× 163 0.3× 229 1.1× 33 1.3k
Jonathan Ledlie United States 18 1.2k 1.4× 547 0.9× 79 0.1× 209 0.4× 368 1.8× 30 1.7k
Tianle Mai China 19 715 0.9× 283 0.4× 215 0.4× 233 0.5× 290 1.4× 56 1.1k

Countries citing papers authored by Yan Kyaw Tun

Since Specialization
Citations

This map shows the geographic impact of Yan Kyaw Tun'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 Yan Kyaw Tun with the expected number of citations based on a country's size and research output (numbers larger than one mean the country cites Yan Kyaw Tun more than expected).

Fields of papers citing papers by Yan Kyaw Tun

Since Specialization
Physical SciencesHealth SciencesLife SciencesSocial Sciences

This network shows the impact of papers produced by Yan Kyaw Tun. 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 Yan Kyaw Tun. The network helps show where Yan Kyaw Tun may publish in the future.

Co-authorship network of co-authors of Yan Kyaw Tun

This figure shows the co-authorship network connecting the top 25 collaborators of Yan Kyaw Tun. A scholar is included among the top collaborators of Yan Kyaw Tun 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 Yan Kyaw Tun. Yan Kyaw Tun 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.
Hassan, Sheikh Salman, et al.. (2026). SemSpaceFL:A Collaborative Hierarchical Federated Learning Framework for Semantic Communication in 6G LEO Satellites. VBN Forskningsportal (Aalborg Universitet).
2.
Hassan, Sheikh Salman, et al.. (2025). Semantic Communication Enabled 6G-NTN Framework: A Novel Denoising and Gateway Hop Integration Mechanism. IEEE Transactions on Wireless Communications. 24(12). 10149–10165. 2 indexed citations
3.
Park, Yu Min, Sheikh Salman Hassan, Yan Kyaw Tun, et al.. (2025). Design Optimization of NOMA Aided Multi-STAR-RIS for Indoor Environments: A Convex Approximation Imitated Reinforcement Learning Approach. IEEE Transactions on Mobile Computing. 24(9). 7929–7946. 3 indexed citations
4.
Kim, Ki Tae, et al.. (2025). Active STAR-RIS Empowered Edge System for Enhanced Energy Efficiency and Task Management. IEEE Transactions on Mobile Computing. 25(4). 5494–5508. 1 indexed citations
5.
Hassan, Sheikh Salman, et al.. (2024). Semantic Enabled 6G LEO Satellite Communication for Earth Observation: A Resource-Constrained Network Optimization. VBN Forskningsportal (Aalborg Universitet). 4472–4478. 3 indexed citations
6.
Le, Tra Huong Thi, et al.. (2024). Min-Max Decoding Error Probability Optimization in RIS-Aided Hybrid TDMA-NOMA Networks. IEEE Access. 12. 129720–129732. 3 indexed citations
7.
Kim, Ki Tae, et al.. (2024). Data Service Maximization in Space-Air-Ground Integrated 6G Networks. IEEE Communications Letters. 28(11). 2598–2602.
9.
Hassan, Sheikh Salman, Yu Min Park, Yan Kyaw Tun, et al.. (2023). Satellite-Based ITS Data Offloading & Computation in 6G Networks: A Cooperative Multi-Agent Proximal Policy Optimization DRL With Attention Approach. IEEE Transactions on Mobile Computing. 23(5). 4956–4974. 43 indexed citations
10.
Kim, Ki Tae, Yan Kyaw Tun, Md. Shirajum Munir, Walid Saad, & Choong Seon Hong. (2023). Deep Reinforcement Learning for Channel Estimation in RIS-Aided Wireless Networks. IEEE Communications Letters. 27(8). 2053–2057. 11 indexed citations
11.
Alsenwi, Madyan, et al.. (2022). Energy-Efficient Resource Allocation in Multi-UAV-Assisted Two-Stage Edge Computing for Beyond 5G Networks. IEEE Transactions on Intelligent Transportation Systems. 23(9). 16421–16432. 77 indexed citations
12.
Park, Yu Min, Sheikh Salman Hassan, Yan Kyaw Tun, Zhu Han, & Choong Seon Hong. (2022). Joint Resources and Phase-Shift Optimization of MEC-Enabled UAV in IRS-Assisted 6G THz Networks. 1–7. 21 indexed citations
13.
Tun, Yan Kyaw, et al.. (2022). Energy-Efficiency Maximization of Multiple RISs-Enabled Communication Networks by Deep Reinforcement Learning. ICC 2022 - IEEE International Conference on Communications. 2181–2186. 9 indexed citations
14.
Pandey, Shashi Raj, Kitae Kim, Madyan Alsenwi, Yan Kyaw Tun, & Choong Seon Hong. (2021). A Crowd-enabled Task Execution Approach in UAV Networks Towards Fog Computing. 246–251. 3 indexed citations
15.
Alsenwi, Madyan, et al.. (2021). Multi-UAV-Assisted MEC System: Joint Association and Resource Management Framework. 213–218. 25 indexed citations
16.
Le, Tra Huong Thi, Nguyen H. Tran, Yan Kyaw Tun, Zhu Han, & Choong Seon Hong. (2020). Auction based Incentive Design for Efficient Federated Learning in Cellular Wireless Networks. VBN Forskningsportal (Aalborg Universitet). 1–6. 44 indexed citations
17.
Pandey, Shashi Raj, Nguyen H. Tran, Mehdi Bennis, et al.. (2019). Incentivize to Build: A Crowdsourcing Framework for Federated Learning. University of Oulu Repository (University of Oulu). 1–6. 27 indexed citations
18.
Tun, Yan Kyaw, et al.. (2019). Cost and Latency Tradeoff in Mobile Edge Computing: A Distributed Game Approach. 1–7. 8 indexed citations
19.
Alsenwi, Madyan, Ibrar Yaqoob, Shashi Raj Pandey, et al.. (2019). Towards Coexistence of Cellular and WiFi Networks in Unlicensed Spectrum: A Neural Networks Based Approach. IEEE Access. 7. 110023–110034. 19 indexed citations
20.
Tun, Yan Kyaw, et al.. (2017). DownlinK power allocation in virtualized wireless networks. 18. 346–349. 9 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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