301 citations · 351 across the 21 of their papers we have counts for
22 papers
Bluetooth and WiFi Dataset for Real World RF Fingerprinting of Commercial Devices
Anu Jagannath, Zackary Kane, Jithin Jagannath
RF fingerprinting is emerging as a physical layer security scheme to identify illegitimate and/or unauthorized emitters sharing the RF spectrum. However, due to the lack of publicl…
Generalization of Deep Reinforcement Learning for Jammer-Resilient Frequency and Power Allocation
Swatantra Kafle, Jithin Jagannath, Zackary Kane +3
We tackle the problem of joint frequency and power allocation while emphasizing the generalization capability of a deep reinforcement learning model. Most of the existing methods s…
Embedding-Assisted Attentional Deep Learning for Real-World RF Fingerprinting of Bluetooth
Anu Jagannath, Jithin Jagannath
A scalable and computationally efficient framework is designed to fingerprint real-world Bluetooth devices. We propose an embedding-assisted attentional framework (Mbed-ATN) suitab…
RF Fingerprinting Needs Attention: Multi-task Approach for Real-World WiFi and Bluetooth
Anu Jagannath, Zackary Kane, Jithin Jagannath
A novel cross-domain attentional multi-task architecture - xDom - for robust real-world wireless radio frequency (RF) fingerprinting is presented in this work. To the best of our k…
Security and Privacy vulnerabilities of 5G/6G and WiFi 6: Survey and Research Directions from a Coexistence Perspective
Keyvan Ramezanpour, Jithin Jagannath, Anu Jagannath
Spectrum scarcity has been a major concern for achieving the desired quality of experience (QoE) in next-generation (5G/6G and beyond) networks supporting a massive volume of mobil…
Distributed Transmission Control for Wireless Networks using Multi-Agent Reinforcement Learning
Collin Farquhar, Prem Sagar Pattanshetty Vasanth Kumar, Anu Jagannath +1
We examine the problem of transmission control, i.e., when to transmit, in distributed wireless communications networks through the lens of multi-agent reinforcement learning. Most…
Digital Twin Virtualization with Machine Learning for IoT and Beyond 5G Networks: Research Directions for Security and Optimal Control
Jithin Jagannath, Keyvan Ramezanpour, Anu Jagannath
Digital twin (DT) technologies have emerged as a solution for real-time data-driven modeling of cyber physical systems (CPS) using the vast amount of data available by Internet of…
MR-iNet Gym: Framework for Edge Deployment of Deep Reinforcement Learning on Embedded Software Defined Radio
Jithin Jagannath, Kian Hamedani, Collin Farquhar +2
Dynamic resource allocation plays a critical role in the next generation of intelligent wireless communication systems. Machine learning has been leveraged as a powerful tool to ma…
Deep neural network goes lighter: A case study of deep compression techniques on automatic RF modulation recognition for Beyond 5G networks
Anu Jagannath, Jithin Jagannath, Yanzhi Wang +1
Automatic RF modulation recognition is a primary signal intelligence (SIGINT) technique that serves as a physical layer authentication enabler and automated signal processing schem…
Multi-task Learning Approach for Modulation and Wireless Signal Classification for 5G and Beyond: Edge Deployment via Model Compression
Anu Jagannath, Jithin Jagannath
Future communication networks must address the scarce spectrum to accommodate extensive growth of heterogeneous wireless devices. Wireless signal recognition is becoming increasing…
Design of Fieldable Cross-Layer Optimized Network using Embedded Software Defined Radios: Survey and Novel Architecture with Field Trials
Jithin Jagannath, Anu Jagannath, Justin Henney +4
The proliferation of wireless devices and their ever increasing influence on our day-to-day life is very evident and seems irreplaceable. This exponential growth in demand, both in…
A Comprehensive Survey on Radio Frequency (RF) Fingerprinting: Traditional Approaches, Deep Learning, and Open Challenges
Anu Jagannath, Jithin Jagannath, Prem Sagar Pattanshetty Vasanth Kumar
Fifth generation (5G) network and beyond envision massive Internet of Things (IoT) rollout to support disruptive applications such as extended reality (XR), augmented/virtual reali…
Fieldable Cross-Layer Optimized Embedded Software Defined Radio is Finally Here!
Jithin Jagannath, Anu Jagannath, Justin Henney +4
The concept of cross-layer optimization has been around for several years now. The primary goal of the cross-layer approach was to liberate the strict boundary between the layers o…
Multi-task Learning Approach for Automatic Modulation and Wireless Signal Classification
Anu Jagannath, Jithin Jagannath
Wireless signal recognition is becoming increasingly more significant for spectrum monitoring, spectrum management, and secure communications. Consequently, it will become a key en…
Jam-Guard: Low-Cost, Hand-held Device for First Responders to Detect and Localize Jammers
Anu Jagannath, Jithin Jagannath
Intentional and unintentional interferences collectively referred to as Radio Frequency Interference (RFI) result in severe security threat to the public safety, first responder em…
Deep Learning and Reinforcement Learning for Autonomous Unmanned Aerial Systems: Roadmap for Theory to Deployment
Jithin Jagannath, Anu Jagannath, Sean Furman +1
Unmanned Aerial Systems (UAS) are being increasingly deployed for commercial, civilian, and military applications. The current UAS state-of-the-art still depends on a remote human…
High Rate-Reliability Beamformer Design for 2x2 MIMO-OFDM System Under Hostile Jamming
Anu Jagannath, Jithin Jagannath, Andrew Drozd
Multiple-input multiple-output (MIMO) systems find immense potential and applicability in the long term evolution (LTE), 5G, Internet of Things (IoT), vehicular ad hoc networks (VA…
Breaking the Bound: Rate-2, Full Diversity, Orthogonal MIMO-STBC Transceiver Design
Anu Jagannath, Jithin Jagannath, Andrew Drozd
Space Time Block Codes (STBCs) from orthogonal designs have attracted significant interest in recent years. However, with the growing demand for higher capacity schemes, the multia…
Redefining Wireless Communication for 6G: Signal Processing Meets Deep Learning with Deep Unfolding
Anu Jagannath, Jithin Jagannath, Tommaso Melodia
The year 2019 witnessed the rollout of the 5G standard, which promises to offer significant data rate improvement over 4G. While 5G is still in its infancy, there has been an incre…
Towards Higher Spectral Efficiency: Rate-2 Full-Diversity Complex Space-Time Block Codes
Anu Jagannath, Jithin Jagannath, Andrew Drozd
The upcoming 5G networks demand high-speed and high spectral-efficiency communications to keep up with the proliferating traffic demands. To this end, Massive multiple-input multip…
HELPER: Heterogeneous Efficient Low Power Radio for Enabling Ad Hoc Emergency Public Safety Networks
Jithin Jagannath, Sean Furman, Anu Jagannath +3
Natural and man-made disasters have been causing destruction and distress to humanity all over the world. In these scenarios, communication infrastructures are the most affected en…
Machine Learning for Wireless Communications in the Internet of Things: A Comprehensive Survey
Jithin Jagannath, Nicholas Polosky, Anu Jagannath +2
The Internet of Things (IoT) is expected to require more effective and efficient wireless communications than ever before. For this reason, techniques such as spectrum sharing, dyn…