Robust semantic communications with masked VQ-VAE enabled codebook
Although semantic communications have exhibited satisfactory performance on a large
number of tasks, the impact of semantic noise and the robustness of the systems have not …
number of tasks, the impact of semantic noise and the robustness of the systems have not …
Deep unfolding hybrid beamforming designs for THz massive MIMO systems
Hybrid beamforming (HBF) is a key enabler for wideband terahertz (THz) massive multiple-
input multiple-output (mMIMO) communications systems. A core challenge with designing …
input multiple-output (mMIMO) communications systems. A core challenge with designing …
Model-driven deep learning for hybrid precoding in millimeter wave MU-MIMO system
The use of a hybrid analog-digital architecture that connects one RF chain to multiple
antennas through phase shifters is an energy-efficient solution for multiuser multiple-input …
antennas through phase shifters is an energy-efficient solution for multiuser multiple-input …
Mixed-timescale deep-unfolding for joint channel estimation and hybrid beamforming
In massive multiple-input multiple-output (MIMO) systems, hybrid analog-digital
beamforming is an essential technique for exploiting the potential array gain without using a …
beamforming is an essential technique for exploiting the potential array gain without using a …
Learn to rapidly and robustly optimize hybrid precoding
O Lavi, N Shlezinger - IEEE Transactions on Communications, 2023 - ieeexplore.ieee.org
Hybrid precoding plays a key role in realizing massive multiple-input multiple-output (MIMO)
transmitters with controllable cost. MIMO precoders are required to frequently adapt based …
transmitters with controllable cost. MIMO precoders are required to frequently adapt based …
Attention-Aided Autoencoder-Based Channel Prediction for Intelligent Reflecting Surface-Assisted Millimeter-Wave Communications
HY Chen, MH Wu, TW Yang… - IEEE Transactions on …, 2023 - ieeexplore.ieee.org
Sixth-generation (6G) wireless communication networks will provide larger coverage and
capacity with lower energy consumption and hardware costs than 5G. Intelligent reflecting …
capacity with lower energy consumption and hardware costs than 5G. Intelligent reflecting …
DDPG-driven deep-unfolding with adaptive depth for channel estimation with sparse Bayesian learning
Deep-unfolding neural networks (NNs) have received great attention since they achieve
satisfactory performance with relatively low complexity. Typically, these deep-unfolding NNs …
satisfactory performance with relatively low complexity. Typically, these deep-unfolding NNs …
Hybrid transceiver design for tera-hertz MIMO systems relying on Bayesian learning aided sparse channel estimation
S Srivastava, A Tripathi, N Varshney… - IEEE Transactions …, 2022 - ieeexplore.ieee.org
Hybrid transceiver design in multiple-input multiple-output (MIMO) Tera-Hertz (THz) systems
relying on sparse channel state information (CSI) estimation techniques is conceived. To …
relying on sparse channel state information (CSI) estimation techniques is conceived. To …
Incentivization and aggregation schemes for federated learning applications
Currently, the data collected by the Internet of Things (IoT) still relies on the cloud-centric
data aggregation and processing approach for preparing machine learning models. This …
data aggregation and processing approach for preparing machine learning models. This …
End-to-end autoencoder communications with optimized interference suppression
An end-to-end communications system based on Orthogonal Frequency Division
Multiplexing (OFDM) is modeled as an autoencoder (AE) for which the transmitter (coding …
Multiplexing (OFDM) is modeled as an autoencoder (AE) for which the transmitter (coding …