| Design and Evaluation of Reconfigurable Intelligent Surfaces in Real-World Environment | 0 | 0.34 | 2022 |
| Neural Networks Based Beam Codebooks: Learning mmWave Massive MIMO Beams That Adapt to Deployment and Hardware | 0 | 0.34 | 2022 |
| Blockage Prediction Using Wireless Signatures: Deep Learning Enables Real-World Demonstration | 0 | 0.34 | 2022 |
| Vision-Position Multi-Modal Beam Prediction Using Real Millimeter Wave Datasets | 0 | 0.34 | 2022 |
| Reinforcement Learning of Beam Codebooks in Millimeter Wave and Terahertz MIMO Systems | 2 | 0.40 | 2022 |
| Sensory Data Assisted Downlink Channel Prediction for Massive MIMO | 0 | 0.34 | 2021 |
| Deep Learning-Based Antenna Selection and CSI Extrapolation in Massive MIMO Systems | 2 | 0.38 | 2021 |
| Deep Learning for THz Drones with Flying Intelligent Surfaces: Beam and Handoff Prediction | 0 | 0.34 | 2021 |
| Vision-Aided Dynamic Blockage Prediction for 6G Wireless Communication Networks | 1 | 0.35 | 2021 |
| Deep Learning Predictive Band Switching in Wireless Networks | 2 | 0.37 | 2021 |
| Vision-Aided 6G Wireless Communications: Blockage Prediction and Proactive Handoff | 2 | 0.37 | 2021 |
| Deep Learning Based Channel Covariance Matrix Estimation With User Location and Scene Images | 1 | 0.35 | 2021 |
| Deep Multimodal Learning: Merging Sensory Data for Massive MIMO Channel Prediction | 5 | 0.39 | 2021 |
| ViWi: A Deep Learning Dataset Framework for Vision-Aided Wireless Communications | 1 | 0.37 | 2020 |
| Deep Learning for mmWave Beam and Blockage Prediction Using Sub-6 GHz Channels | 19 | 0.79 | 2020 |
| Learning Beam Codebooks with Neural Networks: Towards Environment-Aware mmWave MIMO | 0 | 0.34 | 2020 |
| Deep Learning for Massive MIMO With 1-Bit ADCs: When More Antennas Need Fewer Pilots | 3 | 0.38 | 2020 |
| Deep Learning Based MIMO Channel Prediction: An Initial Proof of Concept Prototype | 1 | 0.35 | 2020 |
| Deep Transfer Learning-Based Downlink Channel Prediction for FDD Massive MIMO Systems | 10 | 0.54 | 2020 |
| Vision Aided URLL Communications: Proactive Service Identification and Coexistence | 0 | 0.34 | 2020 |
| Advanced Receiver Architectures for Millimeter-Wave Communications with Low-Resolution ADCs | 2 | 0.36 | 2020 |
| Deep Reinforcement Learning for 5G Networks: Joint Beamforming, Power Control, and Interference Coordination | 16 | 0.60 | 2020 |
| 3D Scene-Based Beam Selection for mmWave Communications | 4 | 0.39 | 2020 |
| Millimeter Wave Base Stations with Cameras - Vision-Aided Beam and Blockage Prediction. | 1 | 0.37 | 2020 |
| Situation-Aware Channel Covariance Prediction for Deep Learning Aided Massive MIMO Systems. | 0 | 0.34 | 2020 |
| Reinforcement Learning for Beam Pattern Design in Millimeter Wave and Massive MIMO Systems | 3 | 0.39 | 2020 |
| Deep Learning for Large Intelligent Surfaces in Millimeter Wave and Massive MIMO Systems | 4 | 0.45 | 2019 |
| DeepMIMO: A Generic Deep Learning Dataset for Millimeter Wave and Massive MIMO Applications. | 7 | 0.57 | 2019 |
| Deep Learning For Tdd And Fdd Massive Mimo: Mapping Channels In Space And Frequency | 14 | 0.76 | 2019 |
| Wireless Communications and Applications Above 100 GHz: Opportunities and Challenges for 6G and Beyond. | 14 | 0.61 | 2019 |
| Enabling Large Intelligent Surfaces With Compressive Sensing And Deep Learning | 22 | 0.92 | 2019 |
| Deep Learning For Direct Hybrid Precoding In Millimeter Wave Massive Mimo Systems | 4 | 0.47 | 2019 |
| Beamforming in Millimeter Wave Systems: Prototyping and Measurement Results. | 1 | 0.34 | 2018 |
| Machine Learning for Reliable mmWave Systems: Blockage Prediction and Proactive Handoff. | 5 | 0.49 | 2018 |
| Deep Learning Coordinated Beamforming for Highly-Mobile Millimeter Wave Systems. | 18 | 0.75 | 2018 |
| Leveraging Mmwave Imaging And Communications For Simultaneous Localization And Mapping | 0 | 0.34 | 2018 |
| Generative Adversarial Estimation of Channel Covariance in Vehicular Millimeter Wave Systems. | 2 | 0.39 | 2018 |
| Initial Beam Association in Millimeter Wave Cellular Systems: Analysis and Design Insights. | 22 | 0.80 | 2017 |
| Hybrid Architectures with Few-Bit ADC Receivers: Achievable Rates and Energy-Rate Tradeoffs. | 42 | 1.15 | 2017 |
| Channel Estimation for Hybrid Architecture-Based Wideband Millimeter Wave Systems. | 59 | 1.38 | 2017 |
| Multi-Layer Precoding: A Potential Solution for Full-Dimensional Massive MIMO Systems. | 2 | 0.37 | 2017 |
| Dynamic Subarrays for Hybrid Precoding in Wideband mmWave MIMO Systems. | 33 | 0.82 | 2017 |
| Modeling and Analyzing Millimeter Wave Cellular Systems. | 49 | 1.47 | 2017 |
| Restricted Secondary Licensing for mmWave Cellular: How Much Gain Can Be Obtained? | 0 | 0.34 | 2016 |
| Massive MIMO Combining with Switches. | 10 | 0.63 | 2016 |
| Achievable Rates of Hybrid Architectures with Few-Bit ADC Receivers | 0 | 0.34 | 2016 |
| Gains of Restricted Secondary Licensing in Millimeter Wave Cellular Systems. | 13 | 0.57 | 2016 |
| Dynamic Subarray Architecture For Wideband Hybrid Precoding In Millimeter Wave Massive Mimo Systems | 0 | 0.34 | 2016 |
| Gram Schmidt Based Greedy Hybrid Precoding for Frequency Selective Millimeter Wave MIMO Systems. | 4 | 0.41 | 2016 |
| Millimeter Wave Energy Harvesting | 2 | 0.38 | 2015 |
