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20192023
most citedMachine Learning for Wireless Communications in the Internet of Things: A Comprehensive Survey

301 citations · 351 across the 21 of their papers we have counts for

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Showing 2022Show all

10 papers · 1 filter

cs.NI2022

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…

cs.LG2022

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…

cs.NI2022★ 1 cited

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…

cs.LG2022★ 1 cited

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…

cs.NI2022★ 4 cited

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…

cs.LG2022★ 3 cited

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…

cs.LG2022★ 1 cited

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…

eess.SP2022★ 4 cited

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…

cs.NI2022

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…

cs.LG2022★ 1 cited

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…