5G NR空口技术介绍，灵活多变的子载波间隔与帧结构

Principal Component Analysis Based Broadband Hybrid Precoding for Millimeter-Wave Massive MIMO Systems

Compressive Sensing Based Massive Access for IoT Relying on Media Modulation Aided Machine Type Communications

Massive Access in Cell-Free Massive MIMO-Based Internet of Things：Cloud Computing and Edge Computing Paradigms

Data-Driven Deep Learning to Design Pilot and Channel Estimator for Massive MIMO

Compressive Sensing-Based Adaptive Active User Detection and Channel Estimation：Massive Access Meets Massive MIMO

Compressive Sensing Based Channel Estimation for Millimeter-Wave Full-Dimensional MIMO With Lens-Array

GMD-Based Hybrid Beamforming for Large Reconfigurable Intelligent Surface Assisted Millimeter-Wave Massive MIMO

Closed-Loop Sparse Channel Estimation for Wideband Millimeter-Wave Full-Dimensional MIMO Systems

Over-Sampling Codebook-Based Hybrid Minimum Sum-Mean-Square-Error Precoding for Millimeter-Wave 3D-MIMO

Compressive Sensing Techniques for Next-Generation Wireless Communications

2D Unitary ESPRIT Based Super-Resolution Channel Estimation for Millimeter-Wave Massive MIMO With Hybrid Precoding

Near-Optimal Signal Detector Based on Structured Compressive Sensing for Massive SM-MIMO

Compressive Sensing Based Multi-User Detector for the Large-Scale SM-MIMO Uplink

Structured Compressive Sensing-Based Spatio-Temporal Joint Channel Estimation for FDD Massive MIMO

Spatially Common Sparsity Based Adaptive Channel Estimation and Feedback for FDD Massive MIMO

MmWave Massive-MIMO-based Wireless Backhaul for the 5G ultra-dense Network

Asymptotic Orthogonality Analysis of Time-Domain Sparse Massive MIMO Channels

Robust Preamble Design for Synchronization, Signaling Transmission, and Channel Estimation

Priori-Information Aided Iterative Hard Threshold：A Low-Complexity High-Accuracy Compressive Sensing Based Channel Estimation for TDS-OFDM