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Journal Articles
- 2024
[j15]Anu Jagannath, Zackary Kane, Jithin Jagannath:
Bluetooth and WiFi Dataset for Real World RF Fingerprinting of Commercial Devices. IEEE Commun. Mag. 62(5): 50-56 (2024)- 2023
- [j14]Keyvan Ramezanpour, Jithin Jagannath
, Anu Jagannath:
Security and privacy vulnerabilities of 5G/6G and WiFi 6: Survey and research directions from a coexistence perspective. Comput. Networks 221: 109515 (2023) - [j13]Collin Farquhar, Swatantra Kafle, Kian Hamedani, Anu Jagannath, Jithin Jagannath:
Marconi-Rosenblatt Framework for Intelligent Networks (MR-iNet Gym): For Rapid Design and Implementation of Distributed Multi-agent Reinforcement Learning Solutions for Wireless Networks. Comput. Networks 222: 109489 (2023) - [j12]Swatantra Kafle, Jithin Jagannath, Zackary Kane, Noor Biswas, Prem Sagar Pattanshetty Vasanth Kumar, Anu Jagannath:
Generalization of Deep Reinforcement Learning for Jammer-Resilient Frequency and Power Allocation. IEEE Commun. Lett. 27(7): 1789-1793 (2023) - [j11]Anu Jagannath, Jithin Jagannath:
Embedding-Assisted Attentional Deep Learning for Real-World RF Fingerprinting of Bluetooth. IEEE Trans. Cogn. Commun. Netw. 9(4): 940-949 (2023) - 2022
- [j10]Jithin Jagannath, Anu Jagannath, Justin Henney, Tyler Gwin, Zackary Kane, Noor Biswas, Andrew L. Drozd:
Design of fieldable cross-layer optimized network using embedded software defined radios: Survey and novel architecture with field trials. Comput. Networks 209: 108917 (2022) - [j9]Keyvan Ramezanpour, Jithin Jagannath:
Intelligent zero trust architecture for 5G/6G networks: Principles, challenges, and the role of machine learning in the context of O-RAN. Comput. Networks 217: 109358 (2022) - [j8]Anu Jagannath, Jithin Jagannath, Prem Sagar Pattanshetty Vasanth Kumar:
A comprehensive survey on radio frequency (RF) fingerprinting: Traditional approaches, deep learning, and open challenges. Comput. Networks 219: 109455 (2022) - [j7]Anu Jagannath, Jithin Jagannath:
Multi-task learning approach for modulation and wireless signal classification for 5G and beyond: Edge deployment via model compression. Phys. Commun. 54: 101793 (2022) - 2021
- [j6]Anu Jagannath, Jithin Jagannath:
Dataset for modulation classification and signal type classification for multi-task and single task learning. Comput. Networks 199: 108441 (2021) - [j5]Anu Jagannath, Jithin Jagannath, Tommaso Melodia:
Redefining Wireless Communication for 6G: Signal Processing Meets Deep Learning With Deep Unfolding. IEEE Trans. Artif. Intell. 2(6): 528-536 (2021) - 2019
- [j4]Nan Cen, Jithin Jagannath, Simone Moretti, Zhangyu Guan, Tommaso Melodia:
LANET: Visible-light ad hoc networks. Ad Hoc Networks 84: 107-123 (2019) - [j3]Jithin Jagannath, Sean Furman, Anu Jagannath, Luther Ling, Andrew Burger, Andrew L. Drozd:
HELPER: Heterogeneous Efficient Low Power Radio for enabling ad hoc emergency public safety networks. Ad Hoc Networks 89: 218-235 (2019) - [j2]Jithin Jagannath, Nicholas Polosky, Anu Jagannath, Francesco Restuccia, Tommaso Melodia:
Machine learning for wireless communications in the Internet of Things: A comprehensive survey. Ad Hoc Networks 93 (2019) - [j1]Jithin Jagannath, Sean Furman, Tommaso Melodia, Andrew L. Drozd:
Design and Experimental Evaluation of a Cross-Layer Deadline-Based Joint Routing and Spectrum Allocation Algorithm. IEEE Trans. Mob. Comput. 18(8): 1774-1788 (2019)
Conference and Workshop Papers
- 2024
- [c24]Jithin Jagannath:
Framework for Federated Learning and Edge Deployment of Real-Time Reinforcement Learning Decision Engine on Software Defined Radio. AAAI Spring Symposia 2024: 304 - 2022
- [c23]Nicholas Polosky, Tyler Gwin, Sean Furman, Parth Barhanpurkar, Jithin Jagannath:
Machine Learning Subsystem for Autonomous Collision Avoidance on a small UAS with Embedded GPU. CCNC 2022: 1-7 - [c22]Anu Jagannath, Zackary Kane, Jithin Jagannath:
RF Fingerprinting Needs Attention: Multi-task Approach for Real-World WiFi and Bluetooth. GLOBECOM 2022: 4607-4612 - [c21]Nicholas Polosky, Bruno C. da Silva, Madalina Fiterau, Jithin Jagannath:
Constrained Offline Policy Optimization. ICML 2022: 17801-17810 - [c20]Jithin Jagannath, Kian Hamedani, Collin Farquhar, Keyvan Ramezanpour, Anu Jagannath:
MR-iNet Gym: Framework for Edge Deployment of Deep Reinforcement Learning on Embedded Software Defined Radio. WiseML@WiSec 2022: 51-56 - [c19]Jithin Jagannath, Keyvan Ramezanpour, Anu Jagannath:
Digital Twin Virtualization with Machine Learning for IoT and Beyond 5G Networks: Research Directions for Security and Optimal Control. WiseML@WiSec 2022: 81-86 - 2021
- [c18]Anu Jagannath, Jithin Jagannath:
Multi-task Learning Approach for Automatic Modulation and Wireless Signal Classification. ICC 2021: 1-7 - [c17]Jithin Jagannath, Anu Jagannath, Justin Henney, Noor Biswas, Tyler Gwin, Zackary Kane, Andrew L. Drozd:
Fieldable Cross-Layer Optimized Embedded Software Defined Radio is Finally Here! MILCOM 2021: 927-932 - [c16]Kian Hamedani, Lingjia Liu, Jithin Jagannath, Yang Cindy Yi:
Adversarial Classification of the Attacks on Smart Grids Using Game Theory and Deep Learning. WiseML@WiSec 2021: 13-18 - 2020
- [c15]Anu Jagannath, Jithin Jagannath, Andrew L. Drozd:
High Rate-Reliability Beamformer Design for 2×2 Mimo-OFDM System Under Hostile Jamming. ICCCN 2020: 1-9 - [c14]Anu Jagannath, Jithin Jagannath:
Jam-Guard: Low-Cost, Hand-held Device for First Responders to Detect and Localize Jammers. ICSPCS 2020: 1-7 - 2019
- [c13]Jithin Jagannath, Sean Furman, Anu Jagannath, Andrew L. Drozd:
Energy Efficient Ad Hoc Networking Devices for Off-the-Grid Public Safety Networks. CCNC 2019: 1-4 - [c12]Anu Jagannath, Jithin Jagannath, Brendan Sheaffer, Andrew L. Drozd:
Developing a Low Cost, Portable Jammer Detection and Localization Device for First Responders. CCNC 2019: 1-4 - [c11]Anu Jagannath, Jithin Jagannath, Andrew L. Drozd:
Towards Higher Spectral Efficiency: Rate-2 Full-Diversity Complex Space-Time Block Codes. GLOBECOM 2019: 1-6 - [c10]Jithin Jagannath, Tommaso Melodia:
VL-ROUTE: A Cross-Layer Routing Protocol for Visible Light Ad Hoc Network. WOWMOM 2019: 1-9 - 2018
- [c9]Jithin Jagannath, Nicholas Polosky, Daniel O'Connor, Lakshmi Narasimhan Theagarajan, Brendan Sheaffer, Svetlana Foulke, Pramod K. Varshney:
Artificial Neural Network Based Automatic Modulation Classification over a Software Defined Radio Testbed. ICC 2018: 1-6 - [c8]Jithin Jagannath, Tommaso Melodia:
An Opportunistic Medium Access Control Protocol for Visible Light Ad Hoc Networks. ICNC 2018: 609-614 - 2017
- [c7]Jithin Jagannath, Daniel O'Connor, Nicholas Polosky, Brendan Sheaffer, Svetlana Foulke, Lakshmi Narasimhan Theagarajan, Pramod K. Varshney:
Design and evaluation of hierarchical hybrid automatic modulation classifier using software defined radios. CCWC 2017: 1-7 - 2016
- [c6]Jithin Jagannath, Tommaso Melodia, Andrew L. Drozd:
DRS: Distributed Deadline-Based Joint Routing and Spectrum Allocation for Tactical Ad-Hoc Networks. GLOBECOM 2016: 1-6 - [c5]Jithin Jagannath, Hanne M. Saarinen, Timothy Woods, Joshua O'Brien, Sean Furman, Andrew L. Drozd, Tommaso Melodia:
COmBAT: Cross-layer Based testbed with Analysis Tool implemented using software defined radios. MILCOM 2016: 1261-1266 - 2015
- [c4]Jithin Jagannath, Hanne M. Saarinen, Andrew L. Drozd:
Framework for automatic signal classification techniques (FACT) for software defined radios. CISDA 2015: 1-7 - [c3]Thakshila Wimalajeewa, Jithin Jagannath, Pramod K. Varshney, Andrew L. Drozd, Wei Su:
Distributed asynchronous modulation classification based on hybrid maximum likelihood approach. MILCOM 2015: 1519-1523 - 2014
- [c2]Svetlana Foulke, Jithin Jagannath, Andrew L. Drozd, Thakshila Wimalajeewa, Pramod K. Varshney, Wei Su:
Multisensor Modulation Classification (MMC): Implementation Considerations - USRP Case Study. MILCOM 2014: 1663-1668 - 2013
- [c1]Jithin Jagannath, Anu Saji, Hovannes Kulhandjian, Yifan Sun, Emrecan Demirors, Tommaso Melodia:
A hybrid MAC protocol with channel-dependent optimized scheduling for clustered underwater acoustic sensor networks. WUWNet 2013: 3:1-3:8
Parts in Books or Collections
- 2021
- [p1]Jithin Jagannath, Anu Jagannath, Sean Furman, Tyler Gwin:
Deep Learning and Reinforcement Learning for Autonomous Unmanned Aerial Systems: Roadmap for Theory to Deployment. Deep Learning for Unmanned Systems 2021: 25-82
Data and Artifacts
- 2022
- [d2]Anu Jagannath, Jithin Jagannath:
RF-Fingerprint-BT-IoT: Real-world Frequency Hopping Bluetooth dataset from IoT devices for RF fingerprinting. IEEE DataPort, 2022
- [d1]Anu Jagannath, Zackary Kane, Jithin Jagannath:
Real-world Commercial WiFi and Bluetooth Dataset for RF Fingerprinting. IEEE DataPort, 2022
Informal and Other Publications
- 2024
- [i25]Sabarish Krishna Moorthy, Jithin Jagannath:
Survey of Graph Neural Network for Internet of Things and NextG Networks. CoRR abs/2405.17309 (2024) - 2023
- [i24]Swatantra Kafle, Jithin Jagannath, Zackary Kane, Noor Biswas, Prem Sagar Pattanshetty Vasanth Kumar, Anu Jagannath:
Generalization of Deep Reinforcement Learning for Jammer-Resilient Frequency and Power Allocation. CoRR abs/2302.02250 (2023) - [i23]Anu Jagannath, Zackary Kane, Jithin Jagannath:
Bluetooth and WiFi Dataset for Real World RF Fingerprinting of Commercial Devices. CoRR abs/2303.13538 (2023) - 2022
- [i22]Anu Jagannath, Jithin Jagannath, Prem Sagar Pattanshetty Vasanth Kumar:
A Comprehensive Survey on Radio Frequency (RF) Fingerprinting: Traditional Approaches, Deep Learning, and Open Challenges. CoRR abs/2201.00680 (2022) - [i21]Jithin Jagannath, Anu Jagannath, Justin Henney, Tyler Gwin, Zackary Kane, Noor Biswas, Andrew L. Drozd:
Design of Fieldable Cross-Layer Optimized Network using Embedded Software Defined Radios: Survey and Novel Architecture with Field Trials. CoRR abs/2201.09454 (2022) - [i20]Anu Jagannath, Jithin Jagannath:
Multi-task Learning Approach for Modulation and Wireless Signal Classification for 5G and Beyond: Edge Deployment via Model Compression. CoRR abs/2203.00517 (2022) - [i19]Jithin Jagannath, Keyvan Ramezanpour, Anu Jagannath:
Digital Twin Virtualization with Machine Learning for IoT and Beyond 5G Networks: Research Directions for Security and Optimal Control. CoRR abs/2204.01950 (2022) - [i18]Anu Jagannath, Jithin Jagannath, Yanzhi Wang, Tommaso Melodia:
Deep neural network goes lighter: A case study of deep compression techniques on automatic RF modulation recognition for Beyond 5G networks. CoRR abs/2204.04390 (2022) - [i17]Jithin Jagannath, Kian Hamedani, Collin Farquhar, Keyvan Ramezanpour, Anu Jagannath:
MR-iNet Gym: Framework for Edge Deployment of Deep Reinforcement Learning on Embedded Software Defined Radio. CoRR abs/2204.04507 (2022) - [i16]Collin Farquhar, Prem Sagar Pattanshetty Vasanth Kumar, Anu Jagannath, Jithin Jagannath:
Distributed Transmission Control for Wireless Networks using Multi-Agent Reinforcement Learning. CoRR abs/2205.06800 (2022) - [i15]Keyvan Ramezanpour, Jithin Jagannath, Anu Jagannath:
Security and Privacy vulnerabilities of 5G/6G and WiFi 6: Survey and Research Directions from a Coexistence Perspective. CoRR abs/2206.14997 (2022) - [i14]Anu Jagannath, Zackary Kane, Jithin Jagannath:
RF Fingerprinting Needs Attention: Multi-task Approach for Real-World WiFi and Bluetooth. CoRR abs/2209.03142 (2022) - [i13]Anu Jagannath, Jithin Jagannath:
Embedding-Assisted Attentional Deep Learning for Real-World RF Fingerprinting of Bluetooth. CoRR abs/2210.02897 (2022) - 2021
- [i12]Anu Jagannath, Jithin Jagannath:
Multi-task Learning Approach for Automatic Modulation and Wireless Signal Classification. CoRR abs/2101.10254 (2021) - [i11]Keyvan Ramezanpour, Jithin Jagannath:
Intelligent Zero Trust Architecture for 5G/6G Tactical Networks: Principles, Challenges, and the Role of Machine Learning. CoRR abs/2105.01478 (2021) - [i10]Kian Hamedani, Lingjia Liu, Jithin Jagannath, Yang Yi:
Adversarial Classification of the Attacks on Smart Grids Using Game Theory and Deep Learning. CoRR abs/2106.03209 (2021) - [i9]Jithin Jagannath, Anu Jagannath, Justin Henney, Noor Biswas, Tyler Gwin, Zackary Kane, Andrew L. Drozd:
Fieldable Cross-Layer Optimized Embedded Software Defined Radio is Finally Here! CoRR abs/2110.01080 (2021) - [i8]Nicholas Polosky, Tyler Gwin, Sean Furman, Parth Barhanpurkar, Jithin Jagannath:
Machine Learning Subsystem for Autonomous Collision Avoidance on a small UAS with Embedded GPU. CoRR abs/2112.01688 (2021) - 2020
- [i7]Anu Jagannath, Jithin Jagannath, Tommaso Melodia:
Redefining Wireless Communication for 6G: Signal Processing Meets Deep Learning. CoRR abs/2004.10715 (2020) - [i6]Anu Jagannath, Jithin Jagannath, Andrew L. Drozd:
High rate-reliability beamformer design for 2x2 MIMO-OFDM system under hostile jamming. CoRR abs/2004.14306 (2020) - [i5]Jithin Jagannath, Anu Jagannath, Sean Furman, Tyler Gwin:
Deep Learning and Reinforcement Learning for Autonomous Unmanned Aerial Systems: Roadmap for Theory to Deployment. CoRR abs/2009.03349 (2020) - 2019
- [i4]Jithin Jagannath, Nicholas Polosky, Anu Jagannath, Francesco Restuccia, Tommaso Melodia:
Machine Learning for Wireless Communications in the Internet of Things: A Comprehensive Survey. CoRR abs/1901.07947 (2019) - [i3]Jithin Jagannath, Sean Furman, Anu Jagannath, Luther Ling, Andrew Burger, Andrew L. Drozd:
HELPER: Heterogeneous Efficient Low Power Radio for Enabling Ad Hoc Emergency Public Safety Networks. CoRR abs/1903.08974 (2019) - [i2]Jithin Jagannath, Tommaso Melodia:
VL-ROUTE: A Cross-Layer Routing Protocol for Visible Light Ad Hoc Network. CoRR abs/1904.05177 (2019) - [i1]Anu Jagannath, Jithin Jagannath, Andrew L. Drozd:
Towards Higher Spectral Efficiency: Rate-2 Full-Diversity Complex Space-Time Block Codes. CoRR abs/1907.09545 (2019)
Coauthor Index
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