80 citations · 126 across the 13 of their papers we have counts for
12 papers · 1 filter
A Variational Bayesian Perspective on Massive MIMO Detection
Duy H. N. Nguyen, Italo Atzeni, Antti Tölli +1
Optimal data detection in massive multiple-input multiple-output (MIMO) systems requires prohibitive computational complexity. A variety of detection algorithms have been proposed…
Leveraging Deep Neural Networks for Massive MIMO Data Detection
Ly V. Nguyen, Nhan T. Nguyen, Nghi H. Tran +3
Massive multiple-input multiple-output (MIMO) is a key technology for emerging next-generation wireless systems. Utilizing large antenna arrays at base-stations, massive MIMO enabl…
Deep Learning for Estimation and Pilot Signal Design in Few-Bit Massive MIMO Systems
Ly V. Nguyen, Duy H. N. Nguyen, A. Lee Swindlehurst
Estimation in few-bit MIMO systems is challenging, since the received signals are nonlinearly distorted by the low-resolution ADCs. In this paper, we propose a deep learning framew…
Machine Learning-based Reconfigurable Intelligent Surface-aided MIMO Systems
Nhan Thanh Nguyen, Ly V. Nguyen, Thien Huynh-The +3
Reconfigurable intelligent surface (RIS) technology has recently emerged as a spectral- and cost-efficient approach for wireless communications systems. However, existing hand-engi…
DNN-based Detectors for Massive MIMO Systems with Low-Resolution ADCs
Ly V. Nguyen, Duy H. N. Nguyen, A. Lee Swindlehurst
Low-resolution analog-to-digital converters (ADCs) have been considered as a practical and promising solution for reducing cost and power consumption in massive Multiple-Input-Mult…
Multi-Agent Reinforcement Learning for Channel Assignment and Power Allocation in Platoon-Based C-V2X Systems
Hung V. Vu, Mohammad Farzanullah, Zheyu Liu +3
We consider the problem of joint channel assignment and power allocation in underlaid cellular vehicular-to-everything (C-V2X) systems where multiple vehicle-to-network (V2N) uplin…
Linear and Deep Neural Network-based Receivers for Massive MIMO Systems with One-Bit ADCs
Ly V. Nguyen, A. Lee Swindlehurst, Duy H. N. Nguyen
The use of one-bit analog-to-digital converters (ADCs) is a practical solution for reducing cost and power consumption in massive Multiple-Input-Multiple-Output (MIMO) systems. How…
SVM-based Channel Estimation and Data Detection for One-Bit Massive MIMO Systems
Ly V. Nguyen, A. Lee Swindlehurst, Duy H. N. Nguyen
The use of low-resolution Analog-to-Digital Converters (ADCs) is a practical solution for reducing cost and power consumption for massive Multiple-Input-Multiple-Output (MIMO) syst…
Neural Network-Optimized Channel Estimator and Training Signal Design for MIMO Systems with Few-Bit ADCs
Duy H. N. Nguyen
This paper is concerned with channel estimation in MIMO systems with few-bit ADCs. In these systems, a linear minimum mean-squared error (MMSE) channel estimator obtained in closed…
System Energy-Efficient Hybrid Beamforming for mmWave Multi-user Systems
Vu Nguyen Ha, Duy H. N. Nguyen, Jean-Francois Frigon
This paper develops energy-efficient hybrid beamforming designs for mmWave multi-user systems where analog precoding is realized by switches and phase shifters such that radio freq…
Linear Receivers for Massive MIMO Systems with One-Bit ADCs
Ly V. Nguyen, Duy H. N. Nguyen
In this letter, we propose three linear receivers including Bussgang-based Maximal Ratio Combining (BMRC), Bussgang-based Zero-Forcing (BZF), and Bussgang-based Minimum Mean Square…
Supervised and Semi-Supervised Learning for MIMO Blind Detection with Low-Resolution ADCs
Ly V. Nguyen, Duy T. Ngo, Nghi H. Tran +2
The use of low-resolution analog-to-digital converters (ADCs) is considered to be an effective technique to reduce the power consumption and hardware complexity of wireless transce…