6 citations · 25 across the 16 of their papers we have counts for
16 papers
Survey of Graph Neural Network for Internet of Things and NextG Networks
Sabarish Krishna Moorthy, Jithin Jagannath
The exponential increase in Internet of Things (IoT) devices coupled with 6G pushing towards higher data rates and connected devices has sparked a surge in data. Consequently, harn…
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…
Machine Learning Subsystem for Autonomous Collision Avoidance on a small UAS with Embedded GPU
Nicholas Polosky, Tyler Gwin, Sean Furman +2
Interest in unmanned aerial system (UAS) powered solutions for 6G communication networks has grown immensely with the widespread availability of machine learning based autonomy mod…
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…
Intelligent Zero Trust Architecture for 5G/6G Networks: Principles, Challenges, and the Role of Machine Learning in the context of O-RAN
Keyvan Ramezanpour, Jithin Jagannath
In this position paper, we discuss the critical need for integrating zero trust (ZT) principles into next-generation communication networks (5G/6G). We highlight the challenges and…