Constructing 6G Near-field Networks: Opportunities and Challenges
RIS enables the construction of ubiquitous near-field wireless propagation environments for future 6G networks, presenting new challenges and opportunities.
Energy-Efficient Hybrid Beamforming for Integrated Sensing, Communications, and Powering
Investigating energy-efficient hybrid beamforming design for integrated sensing, communications, and powering systems.
Enabling Physical Localization of Uncooperative Cellular Devices: Investigating UMA
UMA effectively addresses challenges in physical localization of uncooperative cellular devices by manipulating uplink scheduling and boosting transmission power.
GNN Approach for Cell-Free Massive MIMO: Graph Neural Network Solution for Power Control
Graph Neural Networks offer a superior solution to power control in Cell-Free Massive MIMO systems, outperforming traditional methods.
Graph Neural Network Approach for Cell-Free Massive MIMO Power Control
Using a Graph Neural Network (GNN) approach can efficiently solve downlink max-min power control problems in Cell-Free Massive MIMO systems with superior performance and scalability.
6D Movable Antenna System for Wireless Networks Optimization
Proposing a 6D movable antenna system to enhance wireless network capacity by adapting to user distribution.
Energy Consumption Analysis in Wireless Systems with RES, UAVs, and IRSs
Mobile base stations equipped with UAVs, IRSs, and RESs face energy challenges and benefits.
Quantized Constant-Envelope Waveform Design for Massive MIMO DFRC Systems
Both dual-functional radar-communication (DFRC) and massive MIMO are crucial for 6G wireless networks, with a focus on quantized constant-envelope (QCE) waveform design.
RISAR: RIS-assisted Human Activity Recognition with Commercial Wi-Fi Devices
RISAR significantly enhances human activity recognition accuracy using Wi-Fi signals.
NeWRF: A Deep Learning Framework for Wireless Radiation Field Reconstruction and Channel Prediction
NeWRF is a novel deep learning framework that accurately predicts wireless channels using sparse measurements, revolutionizing wireless network optimization.
