Farhad Rezazadeh

403 total citations
23 papers, 207 citations indexed

About

Farhad Rezazadeh is a scholar working on Electrical and Electronic Engineering, Computer Networks and Communications and Artificial Intelligence. According to data from OpenAlex, Farhad Rezazadeh has authored 23 papers receiving a total of 207 indexed citations (citations by other indexed papers that have themselves been cited), including 16 papers in Electrical and Electronic Engineering, 15 papers in Computer Networks and Communications and 5 papers in Artificial Intelligence. Recurrent topics in Farhad Rezazadeh's work include Software-Defined Networks and 5G (13 papers), Ferroelectric and Negative Capacitance Devices (4 papers) and Advanced MIMO Systems Optimization (4 papers). Farhad Rezazadeh is often cited by papers focused on Software-Defined Networks and 5G (13 papers), Ferroelectric and Negative Capacitance Devices (4 papers) and Advanced MIMO Systems Optimization (4 papers). Farhad Rezazadeh collaborates with scholars based in Spain, United States and Greece. Farhad Rezazadeh's co-authors include Hatim Chergui, Christos Verikoukis, Luis Alonso, Josep Mangues‐Bafalluy, Lanfranco Zanzi, Francesco Devoti, Xavier Costa‐Pérez, Nikolaos Bartzoudis, Engin Zeydan and Sergio Barrachina‐Muñoz and has published in prestigious journals such as IEEE Access, IEEE Communications Magazine and IEEE Transactions on Vehicular Technology.

In The Last Decade

Farhad Rezazadeh

22 papers receiving 203 citations

Peers — A (Enhanced Table)

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

Name h Career Trend Papers Cites
Farhad Rezazadeh Spain 9 113 103 45 25 22 23 207
Jordi Paillissé Spain 7 165 1.5× 50 0.5× 56 1.2× 56 2.2× 20 0.9× 17 242
Zhiming Liu China 8 126 1.1× 107 1.0× 67 1.5× 84 3.4× 12 0.5× 27 263
Guanqiao Qu China 7 72 0.6× 48 0.5× 44 1.0× 20 0.8× 16 0.7× 13 166
Lizhuang Tan China 6 228 2.0× 89 0.9× 33 0.7× 38 1.5× 12 0.5× 50 280
Tianjiao Chen China 9 241 2.1× 70 0.7× 29 0.6× 90 3.6× 11 0.5× 25 327
Amol Dhumane India 7 154 1.4× 57 0.6× 44 1.0× 79 3.2× 7 0.3× 19 244
Jung-Shian Li Taiwan 8 175 1.5× 73 0.7× 52 1.2× 71 2.8× 17 0.8× 68 252
Xiongyan Tang China 7 149 1.3× 143 1.4× 29 0.6× 58 2.3× 12 0.5× 36 275
Vijay Walunj United States 6 192 1.7× 91 0.9× 82 1.8× 26 1.0× 14 0.6× 8 257
Rodrigo Moreira Brazil 8 76 0.7× 63 0.6× 36 0.8× 11 0.4× 9 0.4× 32 167

Countries citing papers authored by Farhad Rezazadeh

Since Specialization
Citations

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

Fields of papers citing papers by Farhad Rezazadeh

Since Specialization
Physical SciencesHealth SciencesLife SciencesSocial Sciences

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

Co-authorship network of co-authors of Farhad Rezazadeh

This figure shows the co-authorship network connecting the top 25 collaborators of Farhad Rezazadeh. A scholar is included among the top collaborators of Farhad Rezazadeh 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 Farhad Rezazadeh. Farhad Rezazadeh 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.
2.
Rezazadeh, Farhad, et al.. (2025). Toward Generative 6G Simulation: An Experimental Multi-Agent LLM and ns-3 Integration. 1–6. 1 indexed citations
3.
Barrachina‐Muñoz, Sergio, Farhad Rezazadeh, Sławomir Kukliński, et al.. (2024). Empowering Beyond 5G Networks: An Experimental Assessment of Zero-Touch Management and Orchestration. IEEE Access. 12. 182752–182762. 2 indexed citations
4.
Zeydan, Engin, et al.. (2024). A Novel Approach for Scalable and Sustainable 6G Networks. IEEE Open Journal of the Communications Society. 5. 1673–1692. 7 indexed citations
5.
Rezazadeh, Farhad, et al.. (2024). GenOnet: Generative Open xG Network Simulation with Multi-Agent LLM and ns-3. Zenodo (CERN European Organization for Nuclear Research). 69–71. 1 indexed citations
6.
Rezazadeh, Farhad, Hatim Chergui, Mehdi Bennis, et al.. (2024). Toward Explainable Reasoning in 6G: A Proof of Concept Study on Radio Resource Allocation. IEEE Open Journal of the Communications Society. 5. 6239–6260. 8 indexed citations
7.
Rezazadeh, Farhad, et al.. (2024). Intelligible Protocol Learning for Resource Allocation in 6G O-RAN Slicing. IEEE Wireless Communications. 31(5). 192–199. 8 indexed citations
8.
Javed, Farhana, et al.. (2024). Decentralized Energy Marketplace via NFTs and AI-based Agents. Zenodo (CERN European Organization for Nuclear Research). 1–6. 3 indexed citations
9.
Rezazadeh, Farhad, et al.. (2023). Joint Explainability and Sensitivity-Aware Federated Deep Learning for Transparent 6G RAN Slicing. Zenodo (CERN European Organization for Nuclear Research). 1238–1243. 10 indexed citations
10.
Rezazadeh, Farhad, Hatim Chergui, & Josep Mangues‐Bafalluy. (2023). Explanation-Guided Deep Reinforcement Learning for Trustworthy 6G RAN Slicing. Zenodo (CERN European Organization for Nuclear Research). 1026–1031. 14 indexed citations
11.
Zeydan, Engin, et al.. (2023). A Marketplace Solution for Distributed Network Management and Orchestration of Slices. Zenodo (CERN European Organization for Nuclear Research). 1–6. 3 indexed citations
12.
Rezazadeh, Farhad, Sergio Barrachina‐Muñoz, Engin Zeydan, et al.. (2023). X-GRL: An Empirical Assessment of Explainable GNN-DRL in B5G/6G Networks. Zenodo (CERN European Organization for Nuclear Research). 172–174. 4 indexed citations
13.
Blanco, Luis, Sławomir Kukliński, Engin Zeydan, et al.. (2023). AI-Driven Framework for Scalable Management of Network Slices. IEEE Communications Magazine. 61(11). 216–222. 4 indexed citations
14.
Barrachina‐Muñoz, Sergio, et al.. (2023). Cloud Native Federated Learning for Streaming: An Experimental Demonstrator. Zenodo (CERN European Organization for Nuclear Research). 1–3. 4 indexed citations
15.
Rezazadeh, Farhad, et al.. (2022). SCHE2MA: Scalable, Energy-Aware, Multidomain Orchestration for Beyond-5G URLLC Services. IEEE Transactions on Intelligent Transportation Systems. 24(7). 7653–7663. 15 indexed citations
16.
Rezazadeh, Farhad & Nikolaos Bartzoudis. (2022). A Federated DRL Approach for Smart Micro-Grid Energy Control with Distributed Energy Resources. Zenodo (CERN European Organization for Nuclear Research). 108–114. 7 indexed citations
17.
Rezazadeh, Farhad, Hatim Chergui, Luis Blanco, Luis Alonso, & Christos Verikoukis. (2021). A Collaborative Statistical Actor-Critic Learning Approach for 6G Network Slicing Control. 2021 IEEE Global Communications Conference (GLOBECOM). 1–6. 7 indexed citations
18.
Rezazadeh, Farhad, et al.. (2021). Actor-Critic-Based Learning for Zero-touch Joint Resource and Energy Control in Network Slicing. 1–6. 18 indexed citations
19.
Rezazadeh, Farhad, Hatim Chergui, Luis Alonso, & Christos Verikoukis. (2020). Continuous Multi-objective Zero-touch Network Slicing via Twin Delayed DDPG and OpenAI Gym. QRU Quaderns de Recerca en Urbanisme. 1–6. 30 indexed citations
20.
Parvïn, Hamïd, et al.. (2017). Parkinson Detection: An Image Processing Approach. Journal of Medical Imaging and Health Informatics. 7(2). 464–472. 7 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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