Andrey Koucheryavy

3.3k total citations
116 papers, 1.5k citations indexed

About

Andrey Koucheryavy is a scholar working on Computer Networks and Communications, Electrical and Electronic Engineering and Aerospace Engineering. According to data from OpenAlex, Andrey Koucheryavy has authored 116 papers receiving a total of 1.5k indexed citations (citations by other indexed papers that have themselves been cited), including 83 papers in Computer Networks and Communications, 55 papers in Electrical and Electronic Engineering and 18 papers in Aerospace Engineering. Recurrent topics in Andrey Koucheryavy's work include IoT and Edge/Fog Computing (39 papers), Software-Defined Networks and 5G (22 papers) and Opportunistic and Delay-Tolerant Networks (19 papers). Andrey Koucheryavy is often cited by papers focused on IoT and Edge/Fog Computing (39 papers), Software-Defined Networks and 5G (22 papers) and Opportunistic and Delay-Tolerant Networks (19 papers). Andrey Koucheryavy collaborates with scholars based in Russia, Egypt and Saudi Arabia. Andrey Koucheryavy's co-authors include Ammar Muthanna, Abdelhamied A. Ateya, Ruslan Kirichek, Alexander Paramonov, Ibrahim A. Elgendy, Anastasia Vybornova, Abdelrahman Abuarqoub, Yevgeni Koucheryavy, Irina Gudkova and Abdukodir Khakimov and has published in prestigious journals such as Scientific Reports, IEEE Access and IEEE Journal on Selected Areas in Communications.

In The Last Decade

Andrey Koucheryavy

104 papers receiving 1.4k citations

Peers — A (Enhanced Table)

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

Name h Career Trend Papers Cites
Andrey Koucheryavy Russia 20 970 635 247 194 170 116 1.5k
Jiadai Wang China 17 961 1.0× 784 1.2× 305 1.2× 308 1.6× 211 1.2× 51 1.7k
Suraj Sharma India 22 1.3k 1.4× 825 1.3× 352 1.4× 343 1.8× 162 1.0× 80 1.9k
Ammar Muthanna Russia 26 1.2k 1.3× 771 1.2× 461 1.9× 327 1.7× 243 1.4× 165 2.1k
Maurizio A. Spirito Italy 22 1.1k 1.2× 849 1.3× 147 0.6× 286 1.5× 238 1.4× 72 1.7k
Lei Feng China 19 697 0.7× 742 1.2× 164 0.7× 224 1.2× 162 1.0× 176 1.3k
Sghaier Guizani Saudi Arabia 12 955 1.0× 474 0.7× 262 1.1× 249 1.3× 66 0.4× 45 1.4k
Yong Xiao China 24 1.4k 1.4× 1.2k 1.9× 378 1.5× 355 1.8× 153 0.9× 94 2.2k
Ziaul Haq Abbas Pakistan 26 1.1k 1.1× 1.2k 1.8× 309 1.3× 266 1.4× 179 1.1× 118 1.8k

Countries citing papers authored by Andrey Koucheryavy

Since Specialization
Citations

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

Fields of papers citing papers by Andrey Koucheryavy

Since Specialization
Physical SciencesHealth SciencesLife SciencesSocial Sciences

This network shows the impact of papers produced by Andrey Koucheryavy. 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 Andrey Koucheryavy. The network helps show where Andrey Koucheryavy may publish in the future.

Co-authorship network of co-authors of Andrey Koucheryavy

This figure shows the co-authorship network connecting the top 25 collaborators of Andrey Koucheryavy. A scholar is included among the top collaborators of Andrey Koucheryavy 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 Andrey Koucheryavy. Andrey Koucheryavy 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.
Ateya, Abdelhamied A., et al.. (2025). A novel feature-oriented quality of anything (QoX) framework for end-to-end robotic services in 6G networks. Scientific Reports. 15(1). 24945–24945.
2.
Muthanna, Ammar, Abdukodir Khakimov, Irina Kochetkova, et al.. (2025). SHARP-AODV: An Intelligent Adaptive Routing Protocol for Highly Mobile Autonomous Aerial Vehicle (AAV) Networks. Sensors. 25(24). 7522–7522.
3.
Al‐Ansi, Abdullah M., et al.. (2024). Blockchain technology integration in service migration to 6G communication networks: a comprehensive review. Indonesian Journal of Electrical Engineering and Computer Science. 34(3). 1654–1654. 5 indexed citations
4.
Muthanna, Ammar, et al.. (2024). Traffic Type Recognition in 6G Software-Defined Networking for Telepresence Services. 1–6. 2 indexed citations
5.
Koucheryavy, Andrey, et al.. (2023). Artificial Intelligence Driven 5G and Beyond Networks. 10(2). 1–13. 2 indexed citations
6.
Ateya, Abdelhamied A., Ammar Muthanna, Andrey Koucheryavy, Yassine Maleh, & Ahmed A. Abd El‐Latif. (2023). Energy efficient offloading scheme for MEC-based augmented reality system. Cluster Computing. 26(1). 789–806. 13 indexed citations
7.
Muthanna, Ammar, et al.. (2023). Deep Learning Peephole LSTM Neural Network-Based Channel State Estimators for OFDM 5G and Beyond Networks. Mathematics. 11(15). 3386–3386. 5 indexed citations
8.
Fokin, Grigoriy & Andrey Koucheryavy. (2022). Deployment of Ultra Dense Network Devices in Space. Part 1. Models and Methods of Geometric Factor. 10(3). 32–59. 1 indexed citations
9.
Fokin, Grigoriy & Andrey Koucheryavy. (2022). Deployment of Ultra Dense Network Devices in Space. Part 2. Search Using Geometric Factor. 10(4). 27–37. 1 indexed citations
10.
Muthanna, Ammar, et al.. (2022). Distributed Edge Computing for Resource Allocation in Smart Cities Based on the IoT. Information. 13(7). 328–328. 27 indexed citations
11.
Muthanna, Ammar, et al.. (2022). Deep Learning for Predicting Traffic in V2X Networks. Applied Sciences. 12(19). 10030–10030. 12 indexed citations
12.
Paramonov, Alexander, Mashael Khayyat, Ammar Muthanna, et al.. (2021). An Efficient Method for Choosing Digital Cluster Size in Ultralow Latency Networks. Wireless Communications and Mobile Computing. 2021(1). 9 indexed citations
13.
Kirichek, Ruslan, et al.. (2021). Machine Learning Algorithm for Delay Prediction in IoT and Tactile Internet. Future Internet. 13(12). 304–304. 17 indexed citations
14.
Alshahrani, Abdullah, et al.. (2021). Performance Estimation in V2X Networks Using Deep Learning-Based M-Estimator Loss Functions in the Presence of Outliers. Symmetry. 13(11). 2207–2207. 8 indexed citations
15.
Paramonov, Alexander, Jialiang Peng, Ammar Muthanna, et al.. (2021). Study and Analysis of Multiconnectivity for Ultrareliable and Low‐Latency Features in Networks and V2X Communications. Wireless Communications and Mobile Computing. 2021(1). 2 indexed citations
16.
Paramonov, Alexander, et al.. (2019). IoT traffic prediction using multi-step ahead prediction with neural network. 1–4. 30 indexed citations
17.
Koucheryavy, Andrey, et al.. (2019). Traffic Routing Method for the Internet of Things Based on the Minimum of Collisions Probability. Proceedings of Telecommunication Universities. 5(3). 37–44. 2 indexed citations
18.
Dinh, Tien Dung, et al.. (2019). Experimental Investigation of the Transmission of Multimedia Content for Augmented Reality Applications on the Basis of a Wireless Sensor Network. Proceedings of Telecommunication Universities. 5(2). 76–87. 1 indexed citations
19.
Koucheryavy, Andrey, et al.. (2014). The cluster head selection algorithm in the 3D USN. 462–466. 14 indexed citations
20.
Muthanna, Ammar, et al.. (2014). Comparison of protocols for Ubiquitous wireless sensor network. 3. 334–337. 10 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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