output
20162022
most citedMachine Learning in NextG Networks via Generative Adversarial Networks

58 citations

Showing 2019Show all

6 papers · 1 filter

cs.NI2019

Coherent Communications in Self-Organizing Networks with Distributed Beamforming

Yi Shi, Yalin E. Sagduyu

Coherent communications aim to support higher data rates and extended connectivity at lower power consumption compared with traditional point-to-point transmissions. The typical se…

cs.NI2019★ 2 cited

Adversarial Deep Learning for Over-the-Air Spectrum Poisoning Attacks

Yalin E. Sagduyu, Yi Shi, Tugba Erpek

An adversarial deep learning approach is presented to launch over-the-air spectrum poisoning attacks. A transmitter applies deep learning on its spectrum sensing results to predict…

cs.NI2019★ 1 cited

DeepWiFi: Cognitive WiFi with Deep Learning

Kemal Davaslioglu, Sohraab Soltani, Tugba Erpek +1

We present the DeepWiFi protocol, which hardens the baseline WiFi (IEEE 802.11ac) with deep learning and sustains high throughput by mitigating out-of-network interference. DeepWiF…

cs.NI2019

Trojan Attacks on Wireless Signal Classification with Adversarial Machine Learning

Kemal Davaslioglu, Yalin E. Sagduyu

We present a Trojan (backdoor or trapdoor) attack that targets deep learning applications in wireless communications. A deep learning classifier is considered to classify wireless…

eess.SP2019★ 10 cited

Generative Adversarial Network for Wireless Signal Spoofing

Yi Shi, Kemal Davaslioglu, Yalin E. Sagduyu

The paper presents a novel approach of spoofing wireless signals by using a general adversarial network (GAN) to generate and transmit synthetic signals that cannot be reliably dis…

cs.IT2019

Interference Regime Enforcing Rate Maximization for Non-Orthogonal Multiple Access (NOMA)

Tugba Erpek, Sennur Ulukus, Yalin E. Sagduyu

An interference regime enforcing rate maximization scheme is proposed to maximize the achievable ergodic sum-rate of the parallel Gaussian interference channels by enforcing very s…