10 papers
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…
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),…
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…
On the Value of Base Station Motion Knowledge for Goal-Oriented Remote Monitoring with Energy-Harvesting Sensors
Sehani Siriwardana, Jean Michel de Souza Sant'Ana, Richard Demo Souza +2
This paper investigates goal-oriented remote monitoring of an unobservable Markov source using energy-harvesting sensors that communicate with a mobile receiver, such as a Low Eart…
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…
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…