7 papers
Rate-Aware Quantum-Inspired Trajectory Learning for Interference-Limited Multi-UAV Networks
Khaoula Khaled, Muhammad Afaq, Ali Arshad Nasir +1
Unmanned aerial vehicle (UAV) can provide on-demand, high-capacity connectivity in disaster and normal situation. However, it faces a challenge of curse of dimensionality in trajec…
Redefining Digital Twins as Predictive Decision Engines for AI-Native Wireless Networks
Afan Ali, Ali Arshad Nasir, Naveed Iqbal +1
Future artificial intelligence (AI)-native 6G networks require wireless systems that move beyond reactive optimization toward autonomous, predictive, and continuously adaptive inte…
Adaptive UAV Communications for URLLC: From Preplanned Designs to Real-Time Intelligence
Asim Ihsan, Muhammad Asif, Ali Arshad Nasir +2
Unmanned aerial vehicles (UAVs) are emerging as a key enabler of next-generation wireless networks, particularly for applications that require ultra-reliable and low-latency commun…
Performance Bounds for Near-Field Velocity Estimation With Modular Linear Array
Khalid A. Alshumayri, Mudassir Masood, Ali. A. Nasir
Velocity estimation is a cornerstone of the recently introduced near-field predictive beamforming. This paper derives the Cramer-Rao bounds (CRBs) for joint radial and transverse v…
Online Model Predictive Control for Trajectory and Beamforming Optimization in UAV-Enabled URLLC
Asim Ihsan, Muhammad Asif, Ali Arshad Nasir +2
This paper investigates joint trajectory and active beamforming design for unmanned aerial vehicle (UAV)-enabled ultra-reliable low-latency communication (URLLC) systems under fini…
Intelligent Spectrum Sharing in Integrated TN-NTNs: A Hierarchical Deep Reinforcement Learning Approach
Muhammad Umer, Muhammad Ahmed Mohsin, Ali Arshad Nasir +2
Integrating non-terrestrial networks (NTNs) with terrestrial networks (TNs) is key to enhancing coverage, capacity, and reliability in future wireless communications. However, the…