258 citations · 1.2k across the 44 of their papers we have counts for
9 papers · 1 filter
Hybrid Federated and Centralized Learning
Ahmet M. Elbir, Sinem Coleri, Kumar Vijay Mishra
Many of the machine learning (ML) tasks are focused on centralized learning (CL), which requires the transmission of local datasets from the clients to a parameter server (PS) lead…
Cognitive Learning-Aided Multi-Antenna Communications
Ahmet M. Elbir, Kumar Vijay Mishra
Cognitive communications have emerged as a promising solution to enhance, adapt, and invent new tools and capabilities that transcend conventional wireless networks. Deep learning…
A Survey of Deep Learning Architectures for Intelligent Reflecting Surfaces
Ahmet M. Elbir, Kumar Vijay Mishra
Intelligent reflecting surfaces (IRSs) have recently received significant attention for 6G wireless communications as they enable the control of the wireless propagation environmen…
Federated Learning for Channel Estimation in Conventional and RIS-Assisted Massive MIMO
Ahmet M. Elbir, Sinem Coleri
Machine learning (ML) has attracted a great research interest for physical layer design problems, such as channel estimation, thanks to its low complexity and robustness. Channel e…
Sparse Array Selection Across Arbitrary Sensor Geometries with Deep Transfer Learning
Ahmet M. Elbir, Kumar Vijay Mishra
Sparse sensor array selection arises in many engineering applications, where it is imperative to obtain maximum spatial resolution from a limited number of array elements. Recent r…
A Deep Learning Framework for Hybrid Beamforming Without Instantaneous CSI Feedback
Ahmet M. Elbir
Hybrid beamformer design plays very crucial role in the next generation millimeter-wave (mm-Wave) massive MIMO (multiple-input multiple-output) systems. Previous works assume the p…
Federated Learning in Vehicular Networks
Ahmet M. Elbir, Burak Soner, Sinem Coleri +2
Machine learning (ML) has recently been adopted in vehicular networks for applications such as autonomous driving, road safety prediction and vehicular object detection, due to its…
Federated Learning for Hybrid Beamforming in mm-Wave Massive MIMO
Ahmet M. Elbir, Sinem Coleri
Machine learning for hybrid beamforming has been extensively studied by using centralized machine learning (CML) techniques, which require the training of a global model with a lar…
Deep Channel Learning For Large Intelligent Surfaces Aided mm-Wave Massive MIMO Systems
Ahmet M. Elbir, A Papazafeiropoulos, P. Kourtessis +1
This letter presents the first work introducing a deep learning (DL) framework for channel estimation in large intelligent surface (LIS) assisted massive MIMO (multiple-input multi…