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20162020
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cs.IT2020

REQIBA: Regression and Deep Q-Learning for Intelligent UAV Cellular User to Base Station Association

Boris Galkin, Erika Fonseca, Ramy Amer +2

Unmanned Aerial Vehicles (UAVs) are emerging as important users of next-generation cellular networks. By operating in the sky, UAV users experience very different radio conditions…

cs.IT2020

Performance Analysis and Optimization of Cache-Assisted CoMP for Clustered D2D Networks

Ramy Amer, Hesham ElSawy, Jacek Kibiłda +2

Caching at mobile devices and leveraging cooperative device-to-device (D2D) communications are two promising approaches to support massive content delivery over wireless networks w…

cs.IT2020

Optimized Caching and Spectrum Partitioning for D2D enabled Cellular Systems with Clustered Devices

Ramy Amer, Hesham Elsawy, M. Majid Butt +3

Caching at mobile devices and leveraging device- to-device (D2D) communication are two promising approaches to support massive content delivery over wireless networks. The analysis…

cs.IT2020

Optimizing Joint Probabilistic Caching and Channel Access for Clustered D2D Networks

Ramy Amer, M. Majid Butt, Nicola Marchetti

Caching at mobile devices and leveraging device-to-device (D2D) communication are two promising approaches to support massive content delivery over wireless networks. Analysis of s…

cs.IT2020

Intelligent Base Station Association for UAV Cellular Users: A Supervised Learning Approach

Boris Galkin, Ramy Amer, Erika Fonseca +1

Fifth Generation (5G) cellular networks are expected to provide cellular connectivity for vehicular users, including Unmanned Aerial Vehicles (UAVs). When flying in the air, these…

cs.IT2020

Performance Analysis of Mobile Cellular-Connected Drones under Practical Antenna Configurations

Ramy Amer, Walid Saad, Boris Galkin +1

Providing seamless connectivity to unmanned aerial vehicle user equipments (UAV-UEs) is very challenging due to the encountered line-of-sight interference and reduced gains of down…