Search Results for author: Mustafa Ozger

Found 7 papers, 0 papers with code

Nash Soft Actor-Critic LEO Satellite Handover Management Algorithm for Flying Vehicles

no code implementations31 Jan 2024 Jinxuan Chen, Mustafa Ozger, Cicek Cavdar

Compared with the terrestrial networks (TN), which can only support limited coverage areas, low-earth orbit (LEO) satellites can provide seamless global coverage and high survivability in case of emergencies.

Blocking Management +2

Reliability and Delay Analysis of 3-Dimensional Networks with Multi-Connectivity: Satellite, HAPs, and Cellular Communications

no code implementations18 Aug 2023 Fateme Salehi, Mustafa Ozger, Cicek Cavdar

Based on the simulation results, we find out that even with very efficient interference mitigation, MC is the key enabler for safe remote piloting operations.

Coverage Performance of UAV-powered Sensors for Energy-neutral Networks with Recharging Stations

no code implementations21 Jun 2023 Oktay Cetinkaya, Mustafa Ozger, David De Roure

Yet, as these sensors rely solely on UAV-transferred power, the absence of UAVs causes sensor outages and hence loss of coverage when they visit recharging stations for battery replenishment.

Ultra-Reliable Low-Latency Communication for Aerial Vehicles via Multi-Connectivity

no code implementations12 May 2022 Fateme Salehi, Mustafa Ozger, Naaser Neda, Cicek Cavdar

In our numerical study, we find that providing requirements by single connectivity to AVs is very challenging due to the line-of-sight (LoS) interference and reduced gains of downtilt ground base station (BS) antenna.

Noise Learning Based Denoising Autoencoder

no code implementations20 Jan 2021 Woong-Hee Lee, Mustafa Ozger, Ursula Challita, Ki Won Sung

This letter introduces a new denoiser that modifies the structure of denoising autoencoder (DAE), namely noise learning based DAE (nlDAE).

Denoising

Machine Learning assisted Handover and Resource Management for Cellular Connected Drones

no code implementations22 Jan 2020 Amin Azari, Fayezeh Ghavimi, Mustafa Ozger, Riku Jantti, Cicek Cavdar

Here, we first present the major challenges in co-existence of terrestrial and drone communications by considering real geographical network data for Stockholm.

BIG-bench Machine Learning Management

Risk-Aware Resource Allocation for URLLC: Challenges and Strategies with Machine Learning

no code implementations22 Dec 2018 Amin Azari, Mustafa Ozger, Cicek Cavdar

The results further provide insights on the benefits of leveraging intelligent RRM, e. g. a 75% increase in data rate with respect to the conservative design approach for the scheduled traffic is achieved, while the 99. 99% reliability of both scheduled and nonscheduled traffic types is satisfied.

BIG-bench Machine Learning Management

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