12 papers · 1 filter
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…
Low Complexity Artificial Noise Aided Beam Focusing Design in Near-Field Terahertz Communications
Zhifeng Tang, Nan Yang, Xiangyun Zhou +3
In this paper, we develop a novel low-complexity artificial noise (AN) aided beam focusing scheme in a near-field terahertz wiretap communication system. In this system, the base s…
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…
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…
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…