3 citations · 4 across the 5 of their papers we have counts for
8 papers
Variational Bayes for Joint Channel Estimation and Data Detection in Few-Bit Massive MIMO Systems
Ly V. Nguyen, A. Lee Swindlehurst, Duy H. N. Nguyen
Massive multiple-input multiple-output (MIMO) communications using low-resolution analog-to-digital converters (ADCs) is a promising technology for providing high spectral and ener…
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…
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…