activity
20242026
collaborators

10 papers

cs.IT2026

Tri-Hybrid Beamforming Design for integrated Sensing and Communications

Tianyu Fang, Mengyuan Ma, Markku Juntti +1

Tri-hybrid beamforming architectures have been proposed to enable energy-efficient communications systems in extra-largescale antenna arrays using low-cost programmable metasurface…

eess.SP2025

AoI-Aware Machine Learning for Constrained Multimodal Sensing-Aided Communications

Abolfazl Zakeri, Nhan Thanh Nguyen, Ahmed Alkhateeb +1

Using environmental sensory data can enhance communications beam training and reduce its overhead compared to conventional methods. However, the availability of fresh sensory data…

eess.SP2025

Deep Reinforcement Learning for Dynamic Sensing and Communications

Abolfazl Zakeri, Nhan Thanh Nguyen, Ahmed Alkhateeb +1

Environmental sensing can significantly enhance mmWave communications by assisting beam training, yet its benefits must be balanced against the associated sensing costs. To this en…

cs.IT2025

Energy Efficiency for Massive MIMO Integrated Sensing and Communication Systems

Huy T. Nguyen, Van-Dinh Nguyen, Nhan Thanh Nguyen +5

This paper explores the energy efficiency (EE) of integrated sensing and communication (ISAC) systems employing massive multiple-input multiple-output (mMIMO) techniques to leverag…

eess.SP2025

Attention-Enhanced Learning for Sensing-Assisted Long-Term Beam Tracking in mmWave Communications

Mengyuan Ma, Nhan Thanh Nguyen, Nir Shlezinger +2

Beam training and prediction in millimeter-wave communications are highly challenging due to fast time-varying channels and sensitivity to blockages and mobility. In this context,…

eess.SP2025

Constrained Multimodal Sensing-Aided Communications: A Dynamic Beamforming Design

Abolfazl Zakeri, Nhan Thanh Nguyen, Ahmed Alkhateeb +1

Using multimodal sensory data can enhance communications systems by reducing the overhead and latency in beam training. However, processing such data incurs high computational comp…