38 citations · 123 across the 34 of their papers we have counts for
42 papers
Deep Reinforcement Learning for Power Control in Next-Generation WiFi Network Systems
Ziad El Jamous, Kemal Davaslioglu, Yalin E. Sagduyu
This paper presents a deep reinforcement learning (DRL) solution for power control in wireless communications, describes its embedded implementation with WiFi transceivers for a Wi…
Federated Learning for Distributed Spectrum Sensing in NextG Communication Networks
Yi Shi, Yalin E. Sagduyu, Tugba Erpek
NextG networks are intended to provide the flexibility of sharing the spectrum with incumbent users and support various spectrum monitoring tasks such as anomaly detection, fault d…
Jamming Attacks on Federated Learning in Wireless Networks
Yi Shi, Yalin E. Sagduyu
Federated learning (FL) offers a decentralized learning environment so that a group of clients can collaborate to train a global model at the server, while keeping their training d…
Adversarial Attacks against Deep Learning Based Power Control in Wireless Communications
Brian Kim, Yi Shi, Yalin E. Sagduyu +2
We consider adversarial machine learning based attacks on power allocation where the base station (BS) allocates its transmit power to multiple orthogonal subcarriers by using a de…
Membership Inference Attack and Defense for Wireless Signal Classifiers with Deep Learning
Yi Shi, Yalin E. Sagduyu
An over-the-air membership inference attack (MIA) is presented to leak private information from a wireless signal classifier. Machine learning (ML) provides powerful means to class…
Jamming-Resilient Path Planning for Multiple UAVs via Deep Reinforcement Learning
Xueyuan Wang, M. Cenk Gursoy, Tugba Erpek +1
Unmanned aerial vehicles (UAVs) are expected to be an integral part of wireless networks. In this paper, we aim to find collision-free paths for multiple cellular-connected UAVs, w…