collaborators

6 papers

eess.SP2026

Fluid Antenna-Enabled Hybrid NOMA and AirFL Networks Under Imperfect CSI and SIC

Saeid Pakravan, Mohsen Ahmadzadeh, Ming Zeng +2

The integration of communication and computation is essential for next-generation wireless systems, especially in scenarios demanding massive connectivity and ultra-low latency. Ov…

cs.IT2026

Channel Estimation for Rydberg Atomic Quantum Receivers: Unrolled Phase Retrieval from Holographic Snapshots

Jian Xiao, Ji Wang, Ming Zeng +3

A model-driven deep learning framework is proposed for channel estimation in Rydberg atomic quantum receivers (RAQRs) based on the measurement of holographic snapshots. Specificall…

eess.SP2026

Robust Resource Allocation in RIS-Assisted Wireless Networks Integrating NOMA and Over-the-Air Federated Learning

Saeid Pakravan, Mohsen Ahmadzadeh, Ming Zeng +4

This paper addresses the critical issue of spectrum scarcity and the need to support diverse services, including communication and learning tasks, by presenting a reconfigurable in…

eess.SP2026

AI-Empowered Resource Allocation for Wirelessly Powered Pinching-Antenna Systems

Saeid Pakravan, Mohsen Ahmadzadeh, Ming Zeng +2

This paper considers a multi-user system, where the users first harvest energy from the base station and then use the harvested energy to transmit information via non-orthogonal mu…

cs.IT2026

Robust Single- and Multi-Pinching Antenna Systems Under User Location Uncertainty

Hao Feng, Ebrahim Bedeer, Ming Zeng +3

Pinching antenna (PA) systems have recently emerged as a promising architecture for reconfigurable wireless communications by enabling flexible antenna placement along a dielectric…

eess.SP2025

A Novel Spatiotemporal Correlation Anomaly Detection Method Based on Time-Frequency-Domain Feature Fusion and a Dynamic Graph Neural Network in Wireless Sensor Network

Miao Ye, Zhibang Jiang, Xingsi Xue +3

Attention-based transformers have played an important role in wireless sensor network (WSN) timing anomaly detection due to their ability to capture long-term dependencies. However…