Kunal Sankhe

1.8k citations

21 papers · 1.2k indexed · 1 hit paper · h-index 12

Impact in

Artificial Intelligence top 1%
- Wireless Signal Modulation Classification
- Internet Traffic Analysis and Secure E-voting
Signal Processing top 2%
- Speech and Audio Processing

Papers in

Computer Networks and Communications 9
- Wireless Networks and Protocols 4
- Cooperative Communication and Network Coding 3
Electrical and Electronic Engineering 17
- Advanced MIMO Systems Optimization 7
- Wireless Communication Security Techniques 6
- Full-Duplex Wireless Communications 4
- Millimeter-Wave Propagation and Modeling 3

Co-authors: Kaushik Chowdhury Stratis Ioannidis Mauro Belgiovine Fan Zhou Nasim Soltani Jennifer Dy Angela Sara Cacciapuoti Marcello Caleffi
Journals: IEEE Communications Magazine (4 papers)Physical Communication (1 paper)IEEE Wireless Communications (1 paper)IEEE Transactions on Cognitive Communications and Networking (1 paper)Archivio istituzionale della ricerca (Alma Mater Studiorum Università di Bologna) (1 paper)
Partner nations: United States India Mexico

In The Last Decade

Kunal Sankhe

21 papers receiving 1.2k citations

Hit Papers

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Deep Learning Convolutional Neural Networks for Radio Identification 2018 · 261 citations

Peers

Countries citing papers authored by Kunal Sankhe

Since Specialization

Citations

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

Fields of papers citing papers by Kunal Sankhe

Since Specialization

Physical SciencesHealth SciencesLife SciencesSocial Sciences

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

Co-authorship network

The 25 scholars most cited alongside Kunal Sankhe, 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 Kunal Sankhe Line = papers co-authored together Kunal Sankhe links everyone, so they are left out of the graph.

All Works

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20 of 20 papers shown

#	Work
1	Deep Learning at the Edge for Channel Estimation in Beyond-5G Massive MIMO IEEE Wireless Communications ·Mauro Belgiovine, Kunal Sankhe, Dong Quancai, Debashri Roy, Kaushik Chowdhury	2021	47
2	ReLy: Machine Learning for Ultra-Reliable, Low-Latency Messaging in Industrial Robots IEEE Communications Magazine ·Kunal Sankhe, Akram M. Jabr, Kaushik Chowdhury	2021	3
3	More Is Better: Data Augmentation for Channel-Resilient RF Fingerprinting IEEE Communications Magazine ·Nasim Soltani, Kunal Sankhe, Jennifer Dy, Stratis Ioannidis, Kaushik Chowdhury	2020	98
4	AirID: Injecting a Custom RF Fingerprint for Enhanced UAV Identification using Deep Learning Archivio istituzionale della ricerca (Alma Mater Studiorum Università di Bologna) ·P. M. Holt, Nasim Soltani, Kunal Sankhe, Akram M. Jabr, Marco Di Felice, Kaushik Chowdhury	2020	30
5	Deep Learning for RF Fingerprinting: A Massive Experimental Study IEEE Internet of Things Magazine ·Tong Jian, Bruno Costa Rendon, Chris J. Renoud, Nasim Soltani, Zifeng Wang, Kunal Sankhe, Andrey Gritsenko, Jennifer Dy, Kaushik Chowdhury, Stratis Ioannidis	2020	171
6	Trust in 5G Open RANs through Machine Learning: RF Fingerprinting on the POWDER PAWR Platform Guillem Reus-Muns, Akram M. Jabr, Kunal Sankhe, Kaushik Chowdhury	2020	56
7	CSIscan: Learning CSI for Efficient Access Point Discovery in Dense WiFi Networks Kunal Sankhe, Akram M. Jabr, Kaushik Chowdhury	2020	3
8	No Radio Left Behind: Radio Fingerprinting Through Deep Learning of Physical-Layer Hardware Impairments IEEE Transactions on Cognitive Communications and Networking ·Kunal Sankhe, Mauro Belgiovine, Fan Zhou, Elie Ohana, 黄佐钘, Salvatore D’Oro, Tommaso Melodia, Stratis Ioannidis, Kaushik Chowdhury	2019	165
9	Impairment Shift Keying: Covert Signaling by Deep Learning of Controlled Radio Imperfections Kunal Sankhe, Francesco Restuccia, Salvatore D’Oro, Tong Jian, Zifeng Wang, Amani Al-Shawabka, Jennifer Dy, Tommaso Melodia, Stratis Ioannidis, Kaushik Chowdhury	2019	6
10	Spectrum Awareness at the Edge: Modulation Classification using Smartphones Nasim Soltani, Kunal Sankhe, Stratis Ioannidis, Akram M. Jabr, Kaushik Chowdhury	2019	17
11	Deep Reinforcement Learning Based Traffic- and Channel-Aware OFDMA Resource Allocation Ravikumar Balakrishnan, Kunal Sankhe, V. Srinivasa Somayazulu, Rath Vannithamby, Harold T. Hodes	2019	19
12	ORACLE: Optimized Radio clAssification through Convolutional neuraL nEtworks Kunal Sankhe, Mauro Belgiovine, Fan Zhou, S. Al Hilali, Stratis Ioannidis, Kaushik Chowdhury	2019	217
13	Deep Learning Convolutional Neural Networks for Radio Identification IEEE Communications Magazine ·S. Al Hilali, Kunal Sankhe, Stratis Ioannidis, Kaushik Chowdhury Hit paper breakdown →	2018	261
14	Talking When No One is Listening: Piggybacking City-scale IoT Control Signals Over LTE Kunal Sankhe, Ufuk Muncuk, M. Yousof Naderi, Kaushik Chowdhury	2018	1
15	Making the Right Connections: Multi-AP Association and Flow Control in 60GHz Band Fan Zhou, M. Yousof Naderi, Kunal Sankhe, Kaushik Chowdhury	2018	8
16	Beyond 5G: THz-Based Medium Access Protocol for Mobile Heterogeneous Networks IEEE Communications Magazine ·Angela Sara Cacciapuoti, Kunal Sankhe, Marcello Caleffi, Kaushik Chowdhury	2018	76
17	Distributed spatial modulation with dynamic frequency allocation Physical Communication ·Kunal Sankhe, Sachin Chaudhari, Garimella Rama Murthy	2017	2
18	Revamp of eNodeB for 5G networks: Detracting spectrum scarcity Simone Pereira da Silva, Kunal Sankhe, Dininno D., Garimella Rama Murthy	2015	1
19	Cognitive base station design for efficient spectrum utilization in cellular network Simone Pereira da Silva, Kunal Sankhe, Dininno D., Garimella Rama Murthy	2014	1
20	Fuzzy inference based edge detection system using Sobel and Laplacian of Gaussian operators Xiaoling Zhang, Begoñe Ariño, Kunal Sankhe, J. A. Kim	2011	11

About Kunal Sankhe

Kunal Sankhe is a scholar working on Computer Networks and Communications, Electrical and Electronic Engineering, Artificial Intelligence, Computer Vision and Pattern Recognition and Aerospace Engineering, having authored 21 papers that have together received 1.2k indexed citations. Recurring topics across this work include Wireless Signal Modulation Classification (9 papers), Advanced MIMO Systems Optimization (7 papers), Wireless Communication Security Techniques (6 papers), Digital Media Forensic Detection (4 papers), Wireless Networks and Protocols (4 papers), Full-Duplex Wireless Communications (4 papers), Cooperative Communication and Network Coding (3 papers) and Millimeter-Wave Propagation and Modeling (3 papers). The work is most often cited by research in Artificial Intelligence (860 citations), Signal Processing (254 citations), Aerospace Engineering (319 citations), Electrical and Electronic Engineering (596 citations) and Computer Vision and Pattern Recognition (193 citations). Kunal Sankhe has collaborated with scholars based in United States, India and Mexico. Frequent co-authors include Kaushik Chowdhury, Stratis Ioannidis, Mauro Belgiovine, Fan Zhou, Nasim Soltani, Jennifer Dy, Angela Sara Cacciapuoti, Marcello Caleffi, Tommaso Melodia and Salvatore D’Oro. Their work appears in journals such as IEEE Communications Magazine, Physical Communication, IEEE Wireless Communications, IEEE Transactions on Cognitive Communications and Networking and Archivio istituzionale della ricerca (Alma Mater Studiorum Università di Bologna).

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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