68 citations · 278 across the 34 of their papers we have counts for
20 papers · 1 filter
How to Discover Knowledge for FutureG: Contextual RAG and LLM Prompting for O-RAN
Nathan Conger, Nathan Scollar, Kemal Davaslioglu +2
We present a retrieval-augmented question answering framework for 5G/6G networks, where the Open Radio Access Network (O-RAN) has become central to disaggregated, virtualized, and…
Coordinated Anti-Jamming Resilience in Swarm Networks via Multi-Agent Reinforcement Learning
Bahman Abolhassani, Tugba Erpek, Kemal Davaslioglu +2
Reactive jammers pose a severe security threat to robotic-swarm networks by selectively disrupting inter-agent communications and undermining formation integrity and mission succes…
MULTI-SCOUT: Multistatic Integrated Sensing and Communications in 5G and Beyond for Moving Target Detection, Positioning, and Tracking
Yalin E. Sagduyu, Kemal Davaslioglu, Tugba Erpek +3
This paper presents a complete signal-processing chain for multistatic integrated sensing and communications (ISAC) using 5G Positioning Reference Signal (PRS). We consider a distr…
Relay Selection and User Equipment Admission in Resource-Efficient NextG Sidelink Communications
Yalin E. Sagduyu, Tugba Erpek, Sastry Kompella +1
5G/6G sidelink communications addresses the challenge of connecting outer UEs, which are unable to directly access a base station (gNodeB), through inner UEs that act as relays to…
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…
Self-Supervised RF Signal Representation Learning for NextG Signal Classification with Deep Learning
Kemal Davaslioglu, Serdar Boztas, Mehmet Can Ertem +2
Deep learning (DL) finds rich applications in the wireless domain to improve spectrum awareness. Typically, DL models are either randomly initialized following a statistical distri…
Generative Adversarial Network in the Air: Deep Adversarial Learning for Wireless Signal Spoofing
Yi Shi, Kemal Davaslioglu, Yalin E. Sagduyu
The spoofing attack is critical to bypass physical-layer signal authentication. This paper presents a deep learning-based spoofing attack to generate synthetic wireless signals tha…
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…
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…
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…
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…
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…
Generative Adversarial Learning for Spectrum Sensing
Kemal Davaslioglu, Yalin E. Sagduyu
A novel approach of training data augmentation and domain adaptation is presented to support machine learning applications for cognitive radio. Machine learning provides effective…
New Algorithms for Maximizing Cellular Wireless Network Energy Efficiency
Kemal Davaslioglu, Cemil Can Coskun, Ender Ayanoglu
In this paper, we aim to maximize the energy efficiency of cellular wireless networks. Specifically, we address the power allocation problem in multi-cell multi-carrier systems. Co…
Energy Efficiency Optimization of Channel Access Probabilities in IEEE 802.15.6 UWB WBANs
Yang Liu, Kemal Davaslioglu, Richard D. Gitlin
Energy efficiency is essential for Wireless Body Area Network (WBAN) applications because of the battery-operated nodes. Other requirements such as throughput, delay, quality of se…
CLOEE - Cross-Layer Optimization for Energy Efficiency of IEEE 802.15.6 IR-UWB WBANs
Kemal Davaslioglu, Yang Liu, Richard D. Gitlin
Advances in sensor networks enable pervasive health monitoring and patient-specific treatments that take into account the patients medical history, current state, genetic backgroun…
Quantifying Potential Energy Efficiency Gain in Green Cellular Wireless Networks
Kemal Davaslioglu, Ender Ayanoglu
Conventional cellular wireless networks were designed with the purpose of providing high throughput for the user and high capacity for the service provider, without any provisions…
Interference-Based Cell Selection in Heterogenous Networks
Kemal Davaslioglu, Ender Ayanoglu
Heterogeneous cellular networks provide significant improvements in terms of increased data rates and cell coverage, and offer reduced user rate starvation. However, there are impo…
Common Rate Maximization in Two-Layer Cellular Radio Systems
Kemal Davaslioglu, Ender Ayanoglu
We address the common rate maximization problem in two-layer cellular networks where high-power and low-power base stations are colocated in the same geographical area. Interferenc…
Power Control in Multi-Layer Cellular Networks
Kemal Davaslioglu, Ender Ayanoglu
We investigate the possible performance gains of power control in multi-layer cellular systems where microcells and picocells are distributed within macrocells. Although multilayer…