collaborators

30 papers

eess.SP2026

Deep-Unfolded Accelerated Projected Gradient for Energy-Efficient Cell-Free Massive MIMO

Phuong Nam Tran, Nhan Thanh Nguyen, Hien Quoc Ngo +1

This paper investigates energy efficiency (EE) maximization for the downlink of cell-free massive multiple-input multiple-output systems under quality-of-service and per-access poi…

eess.SP2026

Performance Analysis and Joint Beamforming for Hybrid RIS-Aided Massive MIMO ISAC

Smriti Uniyal, Tianyu Fang, Marco Di Renzo +2

In integrated sensing and communication (ISAC) systems, stringent sensing performance constraints can severely limit the power available for communication. Hybrid reconfigurable in…

eess.SP2026

Energy Efficiency Maximization for Hybrid RIS-Aided Communications via Deep Unfolding

Pouya Mobaraki, Abolfazl Zakeri, Marco Di Renzo +2

We address energy-efficiency (EE) maximization in a multiuser (MU) multiple-input single-output (MISO) downlink system assisted by a hybrid reconfigurable intelligent surface(RIS),…

eess.SP2026

Lightweight Vision-Aided Beam Tracking for Cross-Environment mmWave Communications

Mengyuan Ma, Ahmed Alkhateeb, Nhan Thanh Nguyen +2

Sensing-aided beam tracking is a promising approach to reduce the overhead for millimeter-wave beam management. However, real-world application remains challenging due to rapid cha…

eess.SP2026

Resource-Efficient WiFi CSI Sensing via Exploiting the Age of Samples

Abolfazl Zakeri, Nhan Thanh Nguyen, Markku Juntti

WiFi channel state information (CSI) sensing must coexist with data communications, which constrains the acquisition rate of fresh CSI measurements. To model this, we formulate CSI…

eess.SP2026

Data-Free Knowledge Distillation for LiDAR-Aided Beam Tracking in MmWave Systems

Abolfazl Zakeri, Nhan Thanh Nguyen, Ahmed Alkhateeb +1

We propose a data-free knowledge distillation (DF- KD) framework for LiDAR-aided mmWave beam tracking, where the objective is to predict the optimal current and future beams from a…