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20232026
most citedBeam Squint Analysis and Mitigation via Hybrid Beamforming Design in THz Communications

96 citations · 96 across the 35 of their papers we have counts for

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32 papers · 1 filter

eess.SP2026

Freshness-Aware Constrained Sensing-Aided Beam Prediction with Knowledge Distillation

Abolfazl Zakeri, Nhan Thanh Nguyen, Ahmed Alkhateeb +1

Beam prediction leveraging environmental data reduces over-the-air beam training overhead. Existing frameworks, however, assume continuous access to fresh sensory data, an assumpti…

eess.SP2026

Beamforming Design Via GNN in mmWave Cell-Free Massive MIMO Using Sub-6 GHz CSI

Sina Tavakolian, Abolfazl Zakeri, Ahmed Alkhateeb +2

Beamforming methods in millimeter-wave (mmWave) cell-free massive multiple-input multiple-output (CFmMIMO) systems require accurate channel state information (CSI), whose acquisiti…

eess.SP2026

Beamforming and Filter Design for Bistatic ISAC under Known and Unknown Transmit Symbols

Mohammad Hatami, Nhan Thanh Nguyen, Markku Juntti

This paper investigates the joint design of beamforming and radar receive filters in a multiuser bistatic integrated sensing and communications (ISAC) system, aiming to maximize th…

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 Wi-Fi CSI-Based Sensing via Exploiting the Age of Samples

Abolfazl Zakeri, Nhan Thanh Nguyen, Markku Juntti

Wi-Fi channel state information (CSI)-based sensing must coexist with data communications, limiting the availability of temporally-dense CSI measurements. We formulate CSI-based hu…

eess.SP2026

Parametric Channel Estimation with Hardware Impaired Hybrid Beamformers: Sensing, Communications, and Power Efficiency Tradeoffs

Enrique T. R. Pinto, Silvio Mandelli, Marcus Henninger +1

Due to high power consumption and hardware costs of fully digital arrays, hybrid beamformers are often considered as a more economic alternative. Furthermore, using high resolution…

eess.SP2026

Time-Varying Parametric Channel Estimation With CP Decomposition Tensor Processing

Enrique T. R. Pinto, André L. F. de Almeida, Markku Juntti

Integrated sensing and communications (ISAC) is a key use case for sixth-generation (6G) wireless systems, where parametric channel estimation (PCE) plays a central role in enablin…

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

Knowledge Distillation for mmWave Beam Prediction Using Sub-6 GHz Channels

Sina Tavakolian, Nhan Thanh Nguyen, Ahmed Alkhateeb +1

Beamforming in millimeter-wave (mmWave) high-mobility environments typically incurs substantial training overhead. While prior studies suggest that sub-6 GHz channels can be exploi…

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…

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…

eess.SP2025

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…

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

Knowledge Distillation for Sensing-Assisted Long-Term Beam Tracking in mmWave Communications

Mengyuan Ma, Nhan Thanh Nguyen, Nir Shlezinger +3

Infrastructure-mounted sensors can capture rich environmental information to enhance communications and facilitate beamforming in millimeter-wave systems. This work presents an eff…

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…

eess.SP2025

Exploiting Symmetric Non-Convexity for Multi-Objective Symbol-Level DFRC Signal Design

Ly V. Nguyen, Rang Liu, Nhan Thanh Nguyen +3

Symbol-level precoding (SLP) is a promising solution for addressing the inherent interference problem in dual-functional radar-communication (DFRC) signal designs. This paper consi…

eess.SP2025

Dynamic Joint Communications and Sensing Precoding Design: A Lyapunov Approach

Abolfazl Zakeri, Nhan Thanh Nguyen, Ahmed Alkhateeb +1

This letter proposes a dynamic joint communications and sensing (JCAS) framework to adaptively design dedicated sensing and communications precoders. We first formulate a stochasti…