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20242026
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eess.SP2026

Knowledge Distillation for Lightweight Multimodal Sensing-Aided mmWave Beam Tracking

Mengyuan Ma, Isuri Welgamage, Ahmed Alkhateeb +3

Beam training and prediction in real-world millimeter-wave (mmWave) communications systems are challenging due to rapidly time-varying channels and strong interference from surroun…

eess.SP2026

Knowledge Distillation for Collaborative Learning in Distributed Communications and Sensing

Nhan Thanh Nguyen, Mengyuan Ma, Nir Shlezinger +4

The rise of sixth generation (6G) wireless networks promises to deliver ultra-reliable, low-latency, and energy-efficient communications, sensing, and computing. However, tradition…

eess.SP2026

Impact of Pointing Error on Coverage Performance of 3D Indoor Terahertz Communication Systems

Zhifeng Tang, Nan Yang, Xiangyun Zhou +3

In this paper, we develop a tractable analytical framework for a three-dimensional (3D) indoor terahertz (THz) communication system to theoretically assess the impact of the pointi…

eess.SP2026

Deep Reinforcement Learning for Hybrid RIS Assisted MIMO Communications

Phuong Nam Tran, Nhan Thanh Nguyen, Markku Juntti

Hybrid reconfigurable intelligent surfaces (HRIS) enhance wireless systems by combining passive reflection with active signal amplification. However, jointly optimizing the transmi…

eess.SP2026

Deep Reinforcement Learning-Based Dynamic Resource Allocation in Cell-Free Massive MIMO

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

In this paper, we consider power allocation and antenna activation of cell-free massive multiple-input multiple-output (CFmMIMO) systems. We first derive closed-form expressions fo…

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…