141 citations · 438 across the 53 of their papers we have counts for
10 papers · 1 filter
Robust Improvement of the Age of Information by Adaptive Packet Coding
Maice Costa, Yalin Sagduyu, Tugba Erpek +1
We consider a wireless communication network with an adaptive scheme to select the number of packets to be admitted and encoded for each transmission, and characterize the informat…
Channel Effects on Surrogate Models of Adversarial Attacks against Wireless Signal Classifiers
Brian Kim, Yalin E. Sagduyu, Tugba Erpek +2
We consider a wireless communication system that consists of a background emitter, a transmitter, and an adversary. The transmitter is equipped with a deep neural network (DNN) cla…
Reinforcement Learning for Dynamic Resource Optimization in 5G Radio Access Network Slicing
Yi Shi, Yalin E. Sagduyu, Tugba Erpek
The paper presents a reinforcement learning solution to dynamic resource allocation for 5G radio access network slicing. Available communication resources (frequency-time blocks an…
Adversarial Attacks with Multiple Antennas Against Deep Learning-Based Modulation Classifiers
Brian Kim, Yalin E. Sagduyu, Tugba Erpek +2
We consider a wireless communication system, where a transmitter sends signals to a receiver with different modulation types while the receiver classifies the modulation types of t…
Fast Initial Access with Deep Learning for Beam Prediction in 5G mmWave Networks
Tarun S. Cousik, Vijay K. Shah, Jeffrey H. Reed +2
This paper presents DeepIA, a deep learning solution for faster and more accurate initial access (IA) in 5G millimeter wave (mmWave) networks when compared to conventional IA. By u…
How to Make 5G Communications "Invisible": Adversarial Machine Learning for Wireless Privacy
Brian Kim, Yalin E. Sagduyu, Kemal Davaslioglu +2
We consider the problem of hiding wireless communications from an eavesdropper that employs a deep learning (DL) classifier to detect whether any transmission of interest is presen…
Deep Learning for Wireless Communications
Tugba Erpek, Timothy J. O'Shea, Yalin E. Sagduyu +2
Existing communication systems exhibit inherent limitations in translating theory to practice when handling the complexity of optimization for emerging wireless applications with h…
Channel-Aware Adversarial Attacks Against Deep Learning-Based Wireless Signal Classifiers
Brian Kim, Yalin E. Sagduyu, Kemal Davaslioglu +2
This paper presents channel-aware adversarial attacks against deep learning-based wireless signal classifiers. There is a transmitter that transmits signals with different modulati…
Over-the-Air Adversarial Attacks on Deep Learning Based Modulation Classifier over Wireless Channels
Brian Kim, Yalin E. Sagduyu, Kemal Davaslioglu +2
We consider a wireless communication system that consists of a transmitter, a receiver, and an adversary. The transmitter transmits signals with different modulation types, while t…
When Wireless Security Meets Machine Learning: Motivation, Challenges, and Research Directions
Yalin E. Sagduyu, Yi Shi, Tugba Erpek +4
Wireless systems are vulnerable to various attacks such as jamming and eavesdropping due to the shared and broadcast nature of wireless medium. To support both attack and defense s…