Leonardo Bonati

41 papers receiving 1.5k citations

Hit Papers

Understanding O-RAN: Architecture, Interfaces, Algorithms...202220262023202420232022100200300400

Peers

Leonardo Bonati
Comparison fields: 5 of 56
  • Computer Networks and Communications 998
  • Electrical and Electronic Engineering 990
  • Artificial Intelligence 198
  • Biomedical Engineering 178
  • Aerospace Engineering 167
Replace Chengchao Liang with:
Chengchao Liang China
Tuyen X. Tran United States
Wibowo Hardjawana Australia
Ziaul Haq Abbas Pakistan
Yaohua Sun China
Valerio Frascolla Germany
Shao‐Yu Lien Taiwan
Vuk Marojevic United States
Fengxian Guo China
Tiago Koketsu Rodrigues Japan
Leonardo Bonati relative to Chengchao Liang China Chengchao Liang's profile →
Citations per field
00.5×3.4×
Chengchao Liang · 1×
Citations per year

Countries citing papers authored by Leonardo Bonati

Since Specialization
Citations

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

Fields of papers citing papers by Leonardo Bonati

Since Specialization
Physical SciencesHealth SciencesLife SciencesSocial Sciences

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

Co-authorship network of co-authors of Leonardo Bonati

This figure shows the co-authorship network connecting the top 25 collaborators of Leonardo Bonati. A scholar is included among the top collaborators of Leonardo Bonati 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 Leonardo Bonati. Leonardo Bonati 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
#WorkIndexed citations
1 0
2 4
3 18
4 1
5 6
6 16
7 7
8 26
9 5
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13 14
14 18
15
Understanding O-RAN: Architecture, Interfaces, Algorithms, Security, and Research Challengesbreakdown →
465
16 2
17
ColO-RAN: Developing Machine Learning-Based xApps for Open RAN Closed-Loop Control on Programmable Experimental Platformsbreakdown →
129
18 172
19
TIP channel sounder program results summary report
4
20 13

About Leonardo Bonati

Leonardo Bonati is a scholar working on Computer Networks and Communications, Electrical and Electronic Engineering and Aerospace Engineering, having authored 43 papers that have together received 1.6k indexed citations. Recurring topics across this work include Advanced MIMO Systems Optimization (19 papers), Software-Defined Networks and 5G (15 papers) and Energy Harvesting in Wireless Networks (6 papers). The work is most often cited by research in Computer Networks and Communications (998 citations), Electrical and Electronic Engineering (990 citations) and Media Technology (105 citations). Leonardo Bonati has collaborated with scholars based in United States, Italy and Mexico. Frequent co-authors include Tommaso Melodia, Salvatore D’Oro, Michele Polese, Stefano Basagni, Emrecan Demirors, Francesco Restuccia, Pedram Johari, Francesca Cuomo, Kaushik Chowdhury and Zhangyu Guan. Their work appears in journals such as IEEE Communications Surveys & Tutorials, IEEE Communications Magazine and IEEE/ACM Transactions on Networking.

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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