collaborators

5 papers

eess.SP2024

UAV-Assisted Enhanced Coverage and Capacity in Dynamic MU-mMIMO IoT Systems: A Deep Reinforcement Learning Approach

MohammadMahdi Ghadaksaz, Mobeen Mahmood, Tho Le-Ngoc

This study focuses on a multi-user massive multiple-input multiple-output (MU-mMIMO) system by incorporating an unmanned aerial vehicle (UAV) as a decode-and-forward (DF) relay bet…

cs.IT2024

Multiple UAV-Assisted Cooperative DF Relaying in Multi-User Massive MIMO IoT Systems

Mobeen Mahmood, Yicheng Yuan, Tho Le-Ngoc

This work considers a multi-user massive multiple-input multiple-output (MU-mMIMO) Internet-of-Things (IoT) system, where multiple unmanned aerial vehicles (UAVs) operating as deco…

cs.IT2024

Adaptive Modulus RF Beamforming for Enhanced Self-Interference Suppression in Full-Duplex Massive MIMO Systems

Mobeen Mahmood, Yuanxing Zhang, Robert Morawski +1

This study employs a uniform rectangular array (URA) sub-connected hybrid beamforming (SC-HBF) architecture to provide a novel self-interference (SI) suppression scheme in a full-d…

cs.IT2023

Deep Learning Meets Swarm Intelligence for UAV-Assisted IoT Coverage in Massive MIMO

Mobeen Mahmood, MohammadMahdi Ghadaksaz, Asil Koc +1

This study considers a UAV-assisted multi-user massive multiple-input multiple-output (MU-mMIMO) systems, where a decode-and-forward (DF) relay in the form of an unmanned aerial ve…

cs.IT2023

Sub-Array Selection in Full-Duplex Massive MIMO for Enhanced Self-Interference Suppression

Mobeen Mahmood, Asil Koc, Duc Tuong Nguyen +2

This study considers a novel full-duplex (FD) massive multiple-input multiple-output (mMIMO) system using hybrid beamforming (HBF) architecture, which allows for simultaneous uplin…