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20142026
most citedDeep Learning Based MIMO Communications

141 citations · 438 across the 53 of their papers we have counts for

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Showing 2019Show all

7 papers · 1 filter

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

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

IoT Network Security from the Perspective of Adversarial Deep Learning

Yalin E. Sagduyu, Yi Shi, Tugba Erpek

Machine learning finds rich applications in Internet of Things (IoT) networks such as information retrieval, traffic management, spectrum sensing, and signal authentication. While…

cs.NI2019★ 2 cited

Spectrum Data Poisoning with Adversarial Deep Learning

Yi Shi, Tugba Erpek, Yalin E. Sagduyu +1

Machine learning has been widely applied in wireless communications. However, the security aspects of machine learning in wireless applications have not been well understood yet. W…

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…