1 citations · 1 across the 8 of their papers we have counts for
12 papers
Deep Learning Based Active Spatial Channel Gain Prediction Using a Swarm of Unmanned Aerial Vehicles
Enes Krijestorac, Danijela Cabric
Prediction of wireless channel gain (CG) across space is a necessary tool for many important wireless network design problems. In this paper, we develop prediction methods that use…
REM-U-net: Deep Learning Based Agile REM Prediction with Energy-Efficient Cell-Free Use Case
Hazem Sallouha, Shamik Sarkar, Enes Krijestorac +1
Radio environment maps (REMs) hold a central role in optimizing wireless network deployment, enhancing network performance, and ensuring effective spectrum management. Conventional…
GAN-RXA: A Practical Scalable Solution to Receiver-Agnostic Transmitter Fingerprinting
Tianyi Zhao, Shamik Sarkar, Enes Krijestorac +1
Radio frequency fingerprinting has been proposed for device identification. However, experimental studies also demonstrated its sensitivity to deployment changes. Recent works have…
Multiband Massive IoT: A Learning Approach to Infrastructure Deployment
Enes Krijestorac, Ghaith Hattab, Petar Popovski +1
We consider a novel ultra-narrowband (UNB) low-power wide-area network (LPWAN) architecture design for uplink transmission of a massive number of Internet of Things (IoT) devices o…
Destination-Feedback Free Distributed Transmit Beamforming using Guided Directionality
Samer Hanna, Enes Krijestorac, Danijela Cabric
Distributed transmit beamforming enables cooperative radios to act as one virtual antenna array, extending their communications' range beyond the capabilities of a single radio. Mo…
UAV Swarm Position Optimization for High Capacity MIMO Backhaul
Samer Hanna, Enes Krijestorac, Danijela Cabric
A swarm of cooperating UAVs communicating with a distant multiantenna ground station can leverage MIMO spatial multiplexing to scale the capacity. Due to the line-of-sight propagat…
Spatial Signal Strength Prediction using 3D Maps and Deep Learning
Enes Krijestorac, Samer Hanna, Danijela Cabric
Machine learning (ML) and artificial neural networks (ANNs) have been successfully applied to simulating complex physics by learning physics models thanks to large data. Inspired b…
Penetrating RF Fingerprinting-based Authentication with a Generative Adversarial Attack
Samurdhi Karunaratne, Enes Krijestorac, Danijela Cabric
Physical layer authentication relies on detecting unique imperfections in signals transmitted by radio devices to isolate their fingerprint. Recently, deep learning-based authentic…
Hybrid Vehicular and Cloud Distributed Computing: A Case for Cooperative Perception
Enes Krijestorac, Agon Memedi, Takamasa Higuchi +3
In this work, we propose the use of hybrid offloading of computing tasks simultaneously to edge servers (vertical offloading) via LTE communication and to nearby cars (horizontal o…
Band Assignment in Ultra-Narrowband (UNB) Systems for Massive IoT Access
Enes Krijestorac, Ghaith Hattab, Petar Popovski +1
In this work, we consider a novel type of Internet of Things (IoT) ultra-narrowband (UNB) network architecture that involves multiple multiplexing bands or channels for uplink tran…
UAV Access Point Placement for Connectivity to a User with Unknown Location Using Deep RL
Enes Krijestorac, Samer Hanna, Danijela Cabric
In recent years, unmanned aerial vehicles (UAVs) have been considered for telecommunications purposes as relays, caches, or IoT data collectors. In addition to being easy to deploy…
UAV Swarms as Amplify-and-Forward MIMO Relays
Samer Hanna, Enes Krijestorac, Han Yan +1
Unmanned aerial vehicles provide new opportunities for performance improvements in future wireless communications systems. For example, they can act as relays that extend the range…