Search Results for author:
Found 13 papers, 1 papers with code
Joint Channel Estimation and Cooperative Localization for Near-Field Ultra-Massive MIMO
To address the joint channel estimation and cooperative localization problem for near-field UM-MIMO systems, we propose a variational Newtonized near-field channel estimation (VNNCE) algorithm and a Gaussian fusion cooperative localization (GFCL) algorithm.
Learning a Low-Rank Feature Representation: Achieving Better Trade-Off between Stability and Plasticity in Continual Learning
This approach optimizes network parameters in the null space of the past tasks' feature representation matrix to guarantee the stability.
Hyb-NeRF: A Multiresolution Hybrid Encoding for Neural Radiance Fields
To address these issues, we present Hyb-NeRF, a novel neural radiance field with a multi-resolution hybrid encoding that achieves efficient neural modeling and fast rendering, which also allows for high-quality novel view synthesis.
Realizing In-Memory Baseband Processing for Ultra-Fast and Energy-Efficient 6G
To support emerging applications ranging from holographic communications to extended reality, next-generation mobile wireless communication systems require ultra-fast and energy-efficient baseband processors.
Multi-Channel Attentive Feature Fusion for Radio Frequency Fingerprinting
The features extracted from different channels are fused adaptively using a shared attention module, where the weights of neural features from multiple channels are learned during training the McAFF model.
Learning to Scale Temperature in Masked Self-Attention for Image Inpainting
Recent advances in deep generative adversarial networks (GAN) and self-attention mechanism have led to significant improvements in the challenging task of inpainting large missing regions in an image.
Trainable Proximal Gradient Descent Based Channel Estimation for mmWave Massive MIMO Systems
The TPGD-Net unfolds the iterative proximal gradient descent (PGD) algorithm into a layer-wise network, with the gradient descent step size set as a trainable parameter.
Collaborative 3D Object Detection for Automatic Vehicle Systems via Learnable Communications
Accurate detection of objects in 3D point clouds is a key problem in autonomous driving systems.
Realizing Ultra-Fast and Energy-Efficient Baseband Processing Using Analogue Resistive Switching Memory
To support emerging applications ranging from holographic communications to extended reality, next-generation mobile wireless communication systems require ultra-fast and energy-efficient (UFEE) baseband processors.
Intelligent Reflecting Surface Aided Mobile Edge Computing With Binary Offloading: Energy Minimization for IoT Devices
Mobile edge computing (MEC) is envisioned as a promising technique to support computation-intensive and timecritical applications in future Internet of Things (IoT) era.
Learning of Time-Frequency Attention Mechanism for Automatic Modulation Recognition
Recent learning-based image classification and speech recognition approaches make extensive use of attention mechanisms to achieve state-of-the-art recognition power, which demonstrates the effectiveness of attention mechanisms.
A Multi-intersection Vehicular Cooperative Control based on End-Edge-Cloud Computing
In particular, we propose a Multi-intersection Vehicular Cooperative Control (MiVeCC) to enable cooperation among vehicles in a large area with multiple unsignalized intersections.
Monthly electricity consumption forecasting by the fruit fly optimization algorithm enhanced Holt-Winters smoothing method
The main idea is that, we use fruit fly optimization algorithm to select smoothing parameters for Holt-Winters exponential smoothing method.
