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20132025
most citedMachine Learning in NextG Networks via Generative Adversarial Networks

58 citations · 158 across the 29 of their papers we have counts for

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Showing 2019 · cs.NIShow all

5 papers · 2 filters

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…

cs.NI2019

QoS and Jamming-Aware Wireless Networking Using Deep Reinforcement Learning

Nof Abuzainab, Tugba Erpek, Kemal Davaslioglu +8

The problem of quality of service (QoS) and jamming-aware communications is considered in an adversarial wireless network subject to external eavesdropping and jamming attacks. To…

cs.NI2019

Real-Time and Embedded Deep Learning on FPGA for RF Signal Classification

Sohraab Soltani, Yalin E. Sagduyu, Raqibul Hasan +3

We designed and implemented a deep learning based RF signal classifier on the Field Programmable Gate Array (FPGA) of an embedded software-defined radio platform, DeepRadio, that c…

cs.NI2019★ 4 cited

Deep Learning for RF Signal Classification in Unknown and Dynamic Spectrum Environments

Yi Shi, Kemal Davaslioglu, Yalin E. Sagduyu +3

Dynamic spectrum access (DSA) benefits from detection and classification of interference sources including in-network users, out-network users, and jammers that may all coexist in…