Search Results for author: Sinem Coleri

Found 16 papers, 1 papers with code

Federated Channel Learning for Intelligent Reflecting Surfaces With Fewer Pilot Signals

no code implementations6 May 2022 Ahmet M. Elbir, Sinem Coleri, Kumar Vijay Mishra

Channel estimation is a critical task in intelligent reflecting surface (IRS)-assisted wireless systems due to the uncertainties imposed by environment dynamics and rapid changes in the IRS configuration.

Federated Learning

Measurement Based Non-Line-Of-Sight Vehicular Visible Light Communication Channel Characterization

no code implementations22 Nov 2021 Bugra Turan, Omer Narmanlioglu, Osman Nuri Koc, Emrah Kar, Sinem Coleri, Murat Uysal

We propose a distance-based NLoS V-VLC channel path loss model considering reflection surface characteristics and NLoS V-VLC channel impulse response (CIR) incorporating the temporal broadening effect due to vehicle reflections through weighted double gamma function.

Vehicular Visible Light Communications Noise Analysis and Autoencoder Based Denoising

no code implementations20 Nov 2021 Bugra Turan, O. Nuri Koc, Emrah Kar, Sinem Coleri

In this paper, to investigate both time-correlated and white noise components of the V-VLC channel, we propose a noise analysis based on Allan variance (AVAR), which provides a time-series analysis method to identify noise from the data.

Denoising Time Series +1

A Hybrid Architecture for Federated and Centralized Learning

no code implementations7 May 2021 Ahmet M. Elbir, Sinem Coleri, Anastasios K. Papazafeiropoulos, Pandelis Kourtessis, Symeon Chatzinotas

To address this common scenario, we propose a more efficient approach called hybrid federated and centralized learning (HFCL), wherein only the clients with sufficient resources employ FL, while the remaining ones send their datasets to the PS, which computes the model on behalf of them.

BIG-bench Machine Learning Federated Learning

Non-Stationary Wireless Channel Modeling Approach Based on Extreme Value Theory for Ultra-Reliable Communications

no code implementations23 Apr 2021 Niloofar Mehrnia, Sinem Coleri

In this paper, we propose a methodology based on EVT to model the extreme events of a non-stationary wireless channel for the ultra-reliable regime of operation.

Federated Dropout Learning for Hybrid Beamforming With Spatial Path Index Modulation In Multi-User mmWave-MIMO Systems

no code implementations15 Feb 2021 Ahmet M. Elbir, Sinem Coleri, Kumar Vijay Mishra

Then, we leverage federated learning (FL) with dropout learning (DL) to train a learning model on the local dataset of users, who estimate the beamformers by feeding the model with their channel data.

Federated Learning

Minimum Length Scheduling for Multi-cell Full Duplex Wireless Powered Communication Networks

no code implementations20 Jan 2021 Muhammad Shahid Iqbal, Yalcin Sadi, Sinem Coleri

In this paper, we investigate a novel minimum length scheduling problem to determine the optimal power control, and scheduling for constant and continuous rate models, while considering concurrent transmission of users, energy causality, maximum transmit power and traffic demand constraints.

Hybrid Federated and Centralized Learning

no code implementations13 Nov 2020 Ahmet M. Elbir, Sinem Coleri, Kumar Vijay Mishra

We address this through a novel hybrid federated and centralized learning (HFCL) framework to effectively train a learning model by exploiting the computational capability of the clients.

Federated Learning

Vehicular Visible Light Positioning for Collision Avoidance and Platooning: A Survey

1 code implementation19 Oct 2020 Burak Soner, Merve Karakas, Utku Noyan, Furkan Sahbaz, Sinem Coleri

Our results show that VLP methods can indeed satisfy the accuracy and rate requirements for localization in collision avoidance and platooning applications.

Autonomous Driving

Vehicular Networks for Combating a Worldwide Pandemic: Preventing the Spread of COVID-19

no code implementations15 Oct 2020 Ahmet M. Elbir, Gokhan Gurbilek, Burak Soner, Anastasios K. Papazafeiropoulos, Pandelis Kourtessis, Sinem Coleri

As a worldwide pandemic, the coronavirus disease-19 (COVID-19) has caused serious restrictions in people's social life, along with the loss of lives, the collapse of economies and the disruption of humanitarian aids.

Humanitarian

Federated Learning for Channel Estimation in Conventional and RIS-Assisted Massive MIMO

no code implementations25 Aug 2020 Ahmet M. Elbir, Sinem Coleri

Channel estimation via ML requires model training on a dataset, which usually includes the received pilot signals as input and channel data as output.

Federated Learning

Federated Learning in Vehicular Networks

no code implementations2 Jun 2020 Ahmet M. Elbir, Burak Soner, Sinem Coleri, Deniz Gunduz, Mehdi Bennis

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 model-free characteristic, allowing adaptive fast response.

Autonomous Driving Federated Learning +3

Federated Learning for Hybrid Beamforming in mm-Wave Massive MIMO

no code implementations20 May 2020 Ahmet M. Elbir, Sinem Coleri

In this work, we introduce a federated learning (FL) based framework for hybrid beamforming, where the model training is performed at the BS by collecting only the gradients from the users.

BIG-bench Machine Learning Federated Learning

Wireless Channel Modeling Based on Extreme Value Theory for Ultra-Reliable Communications

no code implementations3 Feb 2020 Niloofar Mehrnia, Sinem Coleri

A key building block in the design of ultra-reliable communication systems is a wireless channel model that captures the statistics of rare events occurring due to the significant fading.

Minimum Length Scheduling for Full Duplex Time-Critical Wireless Powered Communication Networks

no code implementations3 Feb 2020 Muhammad Shahid Iqbal, Yalcin Sadi, Sinem Coleri

In this paper, we propose a novel minimum length scheduling problem to determine the optimal power control, time allocation and transmission schedule subject to data, energy causality and maximum transmit power constraints in a full-duplex wireless powered communication network.

Machine Learning Based Channel Modeling for Vehicular Visible Light Communication

no code implementations3 Feb 2020 Bugra Turan, Sinem Coleri

Current OWC channel models based on deterministic and stochastic methods, fail to address mobility induced ambient light, optical turbulence and road reflection effects on channel characterization.

BIG-bench Machine Learning Ensemble Learning

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