Mario Bkassiny

1.1k citations
24 papers · 810 indexed · 1 hit paper · h-index 12

Mario Bkassiny

22 papers receiving 779 citations

Hit Papers

A Survey on Machine-Learning Techniques in Cognitive Radios4252012202620162021100200300400

Peers

Mario Bkassiny
Comparison fields: 5 of 55
  • Computer Networks and Communications 566
  • Signal Processing 110
  • Electrical and Electronic Engineering 484
  • Aerospace Engineering 151
  • Artificial Intelligence 180
Replace Joseph Gaeddert with:
Joseph Gaeddert United States
Yong Huat Chew Singapore
Oshri Naparstek Israel
Ihsan Akbar United States
Beibei Wang United States
Kareem E. Baddour Canada
Shabnam Sodagari United States
Zhongding Lei Singapore
Ravikumar Balakrishnan United States
Jinkang Zhu China
Mario Bkassiny relative to Joseph Gaeddert United States Joseph Gaeddert's profile →
Citations per field
00.5×2.8×
Joseph Gaeddert · 1×
Citations per year

Countries citing papers authored by Mario Bkassiny

Since Specialization
Citations

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

Fields of papers citing papers by Mario Bkassiny

Since Specialization
Physical SciencesHealth SciencesLife SciencesSocial Sciences

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

Co-authorship network

The 14 scholars most cited alongside Mario Bkassiny, linked wherever they have co-authored with each other. Click a name or a connecting line to browse the papers they share.

Border = papers with Mario Bkassiny Line = papers co-authored together Mario Bkassiny links everyone, so they are left out of the graph.

All Works

20 of 20 papers shown
#Work
1 202210
2 201416
3 201411
4 20132
5 201314
6
A Survey on Machine-Learning Techniques in Cognitive Radiosbreakdown →
2012425
7 20127
8 201223
9 201237
10 20121
11 201160
12 201110
13 201128
14 201173
15 201111
16 20116
17 20103
18 201016
19 20095
20 20080

About Mario Bkassiny

Mario Bkassiny is a scholar working on Computer Networks and Communications, Management Information Systems and Electrical and Electronic Engineering, having authored 24 papers that have together received 810 indexed citations. Recurring topics across this work include Cognitive Radio Networks and Spectrum Sensing (15 papers), Distributed Sensor Networks and Detection Algorithms (7 papers), Ultra-Wideband Communications Technology (5 papers), Wireless Communication Security Techniques (4 papers), Advanced MIMO Systems Optimization (4 papers), Advanced Queuing Theory Analysis (4 papers), Radar Systems and Signal Processing (3 papers) and Advanced Wireless Communication Techniques (3 papers). The work is most often cited by research in Computer Networks and Communications (566 citations), Signal Processing (110 citations) and Electrical and Electronic Engineering (484 citations). Mario Bkassiny has collaborated with scholars based in United States and Lebanon. Frequent co-authors include Sudharman K. Jayaweera, Yang Li, Keith Avery, Christos G. Christodoulou, Chadi Abou‐Rjeily, Y. Tawk, Ali El‐Hajj, Mohammed Al‐Husseini, Chittabrata Ghosh and Lucinda L. Veeck. Their work appears in journals such as IEEE Communications Surveys & Tutorials, Fertility and Sterility and IEEE Transactions on Wireless Communications.

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.

Explore authors with similar magnitude of impact

Rankless by CCL
2026