4 papers
Quantifying the Reality Gap for RL-Based UAV Placement at mmWave and Sub-THz
Abdullateef Almohamad, Mostafa Ibrahim, Sabit Ekin +1
Reinforcement learning (RL) policies for unmanned aerial vehicle (UAV) placement in mmWave and sub-terahertz networks are typically trained on simplified analytical channels. We qu…
Terahertz Multiple Access: A Deep Reinforcement Learning Controlled Multihop IRS Topology
Muhammad Shehab, Abdullateef Almohamad, Mohamed Elsayed +5
We investigate THz communication uplink multiple access using cascaded intelligent reflecting surfaces (IRSs) assuming correlated channels. Two independent objectives to be achieve…
On Optimizing the Secrecy Performance of RIS-Assisted Cooperative Networks
Abdullateef Almohamad, Ayman Al-Kababji, Anas Tahir +2
Employing reconfigurable intelligent surfaces (RIS) is emerging as a game-changer candidate, thanks to their unique capabilities in improving the power efficiency and supporting th…
Smart and Secure Wireless Communications via Reflecting Intelligent Surfaces: A Short Survey
Abdullateef Almohamad, Anas M. Tahir, Ayman Al-Kababji +4
With the emergence of the internet of things (IoT) technology, wireless connectivity should be more ubiquitous than ever. In fact, the availability of wireless connection everywher…