96 citations · 96 across the 22 of their papers we have counts for
22 papers · 1 filter
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…
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…
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…
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…
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),…
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…
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…
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…
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…
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…
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…
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…
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…
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…
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…
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,…
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…
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…
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…
Comprehensive Review of Deep Unfolding Techniques for Next-Generation Wireless Communication Systems
Sukanya Deka, Kuntal Deka, Nhan Thanh Nguyen +3
The application of machine learning in wireless communications has been extensively explored, with deep unfolding emerging as a powerful model-based technique. Deep unfolding enhan…
Performance Analysis and Power Allocation for Massive MIMO ISAC Systems
Nhan Thanh Nguyen, Van-Dinh Nguyen, Hieu V. Nguyen +3
Integrated sensing and communications (ISAC) is envisioned as a key feature in future wireless communications networks. Its integration with massive multiple-input-multiple-output…
Joint Beamforming Design and Bit Allocation in Massive MIMO with Resolution-Adaptive ADCs
Mengyuan Ma, Nhan Thanh Nguyen, Italo Atzeni +1
Low-resolution analog-to-digital converters (ADCs) have emerged as a promising technology for reducing power consumption and complexity in massive multiple-input multiple-output (M…