Ahmed Alkhateeb

IEEE Wirel. Commun. Lett., December, 2024

Joint and Robust Beamforming Framework for Integrated Sensing and Communication Systems.

[BibT_eX]

[DOI]

IEEE Trans. Wirel. Commun., November, 2024

Real-World Evaluation of Full-Duplex Millimeter Wave Communication Systems.

[BibT_eX]

[DOI]

IEEE Trans. Wirel. Commun., September, 2024

Vision-Guided MIMO Radar Beamforming for Enhanced Vital Signs Detection in Crowds.

[BibT_eX]

[DOI]

IEEE Trans. Aerosp. Electron. Syst., August, 2024

Site-Specific Beam Alignment in 6G via Deep Learning.

[BibT_eX]

[DOI]

IEEE Commun. Mag., August, 2024

Multiple Access Techniques for Intelligent and Multifunctional 6G: Tutorial, Survey, and Outlook.

[BibT_eX]

[DOI]

Proc. IEEE, July, 2024

DeepVerse 6G.

[BibT_eX]

[DOI]

Dataset, July, 2024

Online Beam Learning With Interference Nulling for Millimeter Wave MIMO Systems.

[BibT_eX]

[DOI]

IEEE Trans. Wirel. Commun., May, 2024

PARAMOUNT: Toward Generalizable Deep Learning for mmWave Beam Selection Using Sub-6 GHz Channel Measurements.

[BibT_eX]

[DOI]

Katarina Vuckovic

Mahdi Boloursaz Mashhadi

Farzam Hejazi

Nazanin Rahnavard

IEEE Trans. Wirel. Commun., May, 2024

Environment Semantic Communication: Enabling Distributed Sensing Aided Networks.

[BibT_eX]

[DOI]

Shoaib Imran

IEEE Open J. Commun. Soc., 2024

User Identification: A Key Enabler for Multi-User Vision-Aided Communications.

[BibT_eX]

[DOI]

IEEE Open J. Commun. Soc., 2024

Integrated Sensing and Communications in Downlink FDD MIMO without CSI Feedback.

[BibT_eX]

[DOI]

CoRR, 2024

Digital Twin Assisted Beamforming Design for Integrated Sensing and Communication Systems.

[BibT_eX]

[DOI]

CoRR, 2024

A Dataset Similarity Evaluation Framework for Wireless Communications and Sensing.

[BibT_eX]

[DOI]

CoRR, 2024

Sensing-Aided 6G Drone Communications: Real-World Datasets and Demonstration.

[BibT_eX]

[DOI]

CoRR, 2024

Large Wireless Model (LWM): A Foundation Model for Wireless Channels.

[BibT_eX]

[DOI]

Sadjad Alikhani

CoRR, 2024

Enabling ISAC in Real World: Beam-Based User Identification with Machine Learning.

[BibT_eX]

[DOI]

CoRR, 2024

Learnable Wireless Digital Twins: Reconstructing Electromagnetic Field with Neural Representations.

[BibT_eX]

[DOI]

CoRR, 2024

DeepSense-V2V: A Vehicle-to-Vehicle Multi-Modal Sensing, Localization, and Communications Dataset.

[BibT_eX]

[DOI]

CoRR, 2024

Digital Twin Aided Compressive Sensing: Enabling Site-Specific MIMO Hybrid Precoding.

[BibT_eX]

[DOI]

CoRR, 2024

Digital Twins for Supporting AI Research with Autonomous Vehicle Networks.

[BibT_eX]

[DOI]

CoRR, 2024

Decentralized Interference-Aware Codebook Learning in Millimeter Wave MIMO Systems.

[BibT_eX]

[DOI]

CoRR, 2024

Multiple Access Techniques for Intelligent and Multi-Functional 6G: Tutorial, Survey, and Outlook.

[BibT_eX]

[DOI]

CoRR, 2024

Digital Twin Aided RIS Communication: Robust Beamforming and Interference Management.

[BibT_eX]

[DOI]

Sadjad Alikhani

Proceedings of the 100th IEEE Vehicular Technology Conference, 2024

Learning Beamforming in Cell-free Massive MIMO ISAC Systems.

[BibT_eX]

[DOI]

Proceedings of the 25th IEEE International Workshop on Signal Processing Advances in Wireless Communications, 2024

Digital Twin for Spectrum Sharing and Coexistence: Coordinating the Uncoordinated.

[BibT_eX]

[DOI]

Sadjad Alikhani

Proceedings of the 25th IEEE International Workshop on Signal Processing Advances in Wireless Communications, 2024

Localization in Digital Twin MIMO Networks: A Case for Massive Fingerprinting.

[BibT_eX]

[DOI]

João Morais

Proceedings of the IEEE International Conference on Communications Workshops, 2024

ISAC with Backscattering RFID Tags: Joint Beamforming Design.

[BibT_eX]

[DOI]

Proceedings of the IEEE International Conference on Communications, 2024

Digital Twin Aided Massive MIMO: CSI Compression and Feedback.

[BibT_eX]

[DOI]

Proceedings of the IEEE International Conference on Communications, 2024

2023

Sensing Aided Reconfigurable Intelligent Surfaces for 3GPP 5G Transparent Operation.

[BibT_eX]

[DOI]

Ahmed Hindy

IEEE Trans. Commun., November, 2023

Real-Time Digital Twins: Vision and Research Directions for 6G and Beyond.

[BibT_eX]

[DOI]

IEEE Commun. Mag., November, 2023

DeepSense 6G: A Large-Scale Real-World Multi-Modal Sensing and Communication Dataset.

[BibT_eX]

[DOI]

IEEE Commun. Mag., September, 2023

DeepSense 6G: A Large-Scale Real-World Multi-Modal Sensing and Communication Dataset.

[BibT_eX]

[DOI]

Dataset, August, 2023

Computer Vision Aided Codebook Design for MIMO Communications Systems.

[BibT_eX]

[DOI]

IEEE Trans. Wirel. Commun., May, 2023

Integrated Sensing and Communication for 6G: Ten Key Machine Learning Roles.

[BibT_eX]

[DOI]

IEEE Commun. Mag., May, 2023

Computer Vision Aided mmWave Beam Alignment in V2X Communications.

[BibT_eX]

[DOI]

IEEE Trans. Wirel. Commun., April, 2023

Deep Learning of Near Field Beam Focusing in Terahertz Wideband Massive MIMO Systems.

[BibT_eX]

[DOI]

IEEE Wirel. Commun. Lett., March, 2023

LiDAR Aided Future Beam Prediction in Real-World Millimeter Wave V2I Communications.

[BibT_eX]

[DOI]

IEEE Wirel. Commun. Lett., 2023

Proactively Predicting Dynamic 6G Link Blockages Using LiDAR and In-Band Signatures.

[BibT_eX]

[DOI]

Shunyao Wu

Chaitali Chakrabarti

IEEE Open J. Commun. Soc., 2023

Vehicle Cameras Guide mmWave Beams: Approach and Real-World V2V Demonstration.

[BibT_eX]

[DOI]

CoRR, 2023

Camera Based mmWave Beam Prediction: Towards Multi-Candidate Real-World Scenarios.

[BibT_eX]

[DOI]

CoRR, 2023

Cell-Free ISAC MIMO Systems: Joint Sensing and Communication Beamforming.

[BibT_eX]

[DOI]

CoRR, 2023

Arcaboard: An Overview of the SElectromagnetic HoverBoard.

[BibT_eX]

[DOI]

Nagham A. Al-Madi

Mohammad Azmi Al-Madi

Proceedings of the International Conference on Information Technology, 2023

Implementation of Real-Time Adversarial Attacks on DNN-based Modulation Classifier.

[BibT_eX]

[DOI]

Proceedings of the International Conference on Computing, Networking and Communications, 2023

A Digital Twin Assisted Framework for Interference Nulling in Millimeter Wave MIMO Systems.

[BibT_eX]

[DOI]

Proceedings of the IEEE International Conference on Communications, 2023

Reconfigurable Intelligent Surface Aided Wireless Sensing for Scene Depth Estimation.

[BibT_eX]

[DOI]

Proceedings of the IEEE International Conference on Communications, 2023

Position-Aided Beam Prediction in the Real World: How Useful GPS Locations Actually are?

[BibT_eX]

[DOI]

Proceedings of the IEEE International Conference on Communications, 2023

Camera Aided Reconfigurable Intelligent Surfaces: Computer Vision Based Fast Beam Selection.

[BibT_eX]

[DOI]

Ahmed Hindy

Proceedings of the IEEE International Conference on Communications, 2023

Sensing Aided OTFS Massive MIMO Systems: Compressive Channel Estimation.

[BibT_eX]

[DOI]

Proceedings of the IEEE International Conference on Communications, 2023

Digital Twin Based Beam Prediction: Can We Train in the Digital World and Deploy in Reality?

[BibT_eX]

[DOI]

Proceedings of the IEEE International Conference on Communications, 2023

Environment Semantic Aided Communication: A Real World Demonstration for Beam Prediction.

[BibT_eX]

[DOI]

Shoaib Imran

Proceedings of the IEEE International Conference on Communications, 2023

Millimeter Wave Drones with Cameras: Computer Vision Aided Wireless Beam Prediction.

[BibT_eX]

[DOI]

Andrew Hredzak

Proceedings of the IEEE International Conference on Communications, 2023

Sparse Delay-Doppler Channel Estimation for OTFS Modulation Using 2D-Music.

[BibT_eX]

[DOI]

Proceedings of the IEEE International Conference on Acoustics, 2023

Millimeter Wave V2V Beam Tracking using Radar: Algorithms and Real-World Demonstration.

[BibT_eX]

[DOI]

Proceedings of the 31st European Signal Processing Conference, 2023

Steer+: Robust Beam Refinement for Full-Duplex Millimeter Wave Communication Systems (Invited Paper).

[BibT_eX]

[DOI]

Proceedings of the 57th Asilomar Conference on Signals, Systems, and Computers, ACSSC 2023, Pacific Grove, CA, USA, October 29, 2023

Vehicle Cameras Guide mm Wave Beams: Approach and Real-World V2V Demonstration.

[BibT_eX]

[DOI]

Proceedings of the 57th Asilomar Conference on Signals, Systems, and Computers, ACSSC 2023, Pacific Grove, CA, USA, October 29, 2023

Integrated Imaging and Communication with Reconfigurable Intelligent Surfaces.

[BibT_eX]

[DOI]

Proceedings of the 57th Asilomar Conference on Signals, Systems, and Computers, ACSSC 2023, Pacific Grove, CA, USA, October 29, 2023

Cell-Free Joint Sensing and Communication MIMO: A Max-Min Fair Beamforming Approach.

[BibT_eX]

[DOI]

Proceedings of the 57th Asilomar Conference on Signals, Systems, and Computers, ACSSC 2023, Pacific Grove, CA, USA, October 29, 2023

2022

Enabling Cell-Free Massive MIMO Systems With Wireless Millimeter Wave Fronthaul.

[BibT_eX]

[DOI]

IEEE Trans. Wirel. Commun., 2022

Reinforcement Learning of Beam Codebooks in Millimeter Wave and Terahertz MIMO Systems.

[BibT_eX]

[DOI]

IEEE Trans. Commun., 2022

Neural Networks Based Beam Codebooks: Learning mmWave Massive MIMO Beams That Adapt to Deployment and Hardware.

[BibT_eX]

[DOI]

Panagiotis Theofanopoulos

IEEE Trans. Commun., 2022

Hybrid Blockchain Platforms for the Internet of Things (IoT): A Systematic Literature Review.

[BibT_eX]

[DOI]

Sensors, 2022

Blockage Prediction Using Wireless Signatures: Deep Learning Enables Real-World Demonstration.

[BibT_eX]

[DOI]

IEEE Open J. Commun. Soc., 2022

Design and Evaluation of Reconfigurable Intelligent Surfaces in Real-World Environment.

[BibT_eX]

[DOI]

Georgios C. Trichopoulos

IEEE Open J. Commun. Soc., 2022

Sensing Aided OTFS Channel Estimation for Massive MIMO Systems.

[BibT_eX]

[DOI]

CoRR, 2022

Multi-Modal Beam Prediction Challenge 2022: Towards Generalization.

[BibT_eX]

[DOI]

CoRR, 2022

Position Aided Beam Prediction in the Real World: How Useful GPS Locations Actually Are?

[BibT_eX]

[DOI]

CoRR, 2022

Predicting Future CSI Feedback For Highly-Mobile Massive MIMO Systems.

[BibT_eX]

[DOI]

CoRR, 2022

LiDAR-Aided Mobile Blockage Prediction in Real-World Millimeter Wave Systems.

[BibT_eX]

[DOI]

Shunyao Wu

Chaitali Chakrabarti

Proceedings of the IEEE Wireless Communications and Networking Conference, 2022

Radar Aided 6G Beam Prediction: Deep Learning Algorithms and Real-World Demonstration.

[BibT_eX]

[DOI]

Proceedings of the IEEE Wireless Communications and Networking Conference, 2022

Vision-Position Multi-Modal Beam Prediction Using Real Millimeter Wave Datasets.

[BibT_eX]

[DOI]

Proceedings of the IEEE Wireless Communications and Networking Conference, 2022

Deep Learning for Moving Blockage Prediction using Real mmWave Measurements.

[BibT_eX]

[DOI]

Proceedings of the IEEE International Conference on Communications, 2022

Radar Aided Proactive Blockage Prediction in Real-World Millimeter Wave Systems.

[BibT_eX]

[DOI]

Proceedings of the IEEE International Conference on Communications, 2022

Location- and Orientation-aware Millimeter Wave Beam Selection for Multi -Panel Antenna Devices.

[BibT_eX]

[DOI]

Sajad Rezaie

João Morais

Elisabeth de Carvalho

Carles Navarro Manchón

Proceedings of the IEEE Global Communications Conference, 2022

Computer Vision Aided Beam Tracking in A Real-World Millimeter Wave Deployment.

[BibT_eX]

[DOI]

Proceedings of the IEEE Globecom 2022 Workshops, 2022

Towards Real-World 6G Drone Communication: Position and Camera Aided Beam Prediction.

[BibT_eX]

[DOI]

Proceedings of the IEEE Global Communications Conference, 2022

Computer Vision Aided Blockage Prediction in Real-World Millimeter Wave Deployments.

[BibT_eX]

[DOI]

Proceedings of the IEEE Globecom 2022 Workshops, 2022

Online Beam Learning for Interference Nulling in Hardware-Constrained mm Wave MIMO Systems.

[BibT_eX]

[DOI]

Proceedings of the 56th Asilomar Conference on Signals, Systems, and Computers, ACSSC 2022, Pacific Grove, CA, USA, October 31, 2022

2021

Deep Learning Predictive Band Switching in Wireless Networks.

[BibT_eX]

[DOI]

IEEE Trans. Wirel. Commun., 2021

Deep Learning-Based Antenna Selection and CSI Extrapolation in Massive MIMO Systems.

[BibT_eX]

[DOI]

IEEE Trans. Wirel. Commun., 2021

Vision-Aided 6G Wireless Communications: Blockage Prediction and Proactive Handoff.

[BibT_eX]

[DOI]

IEEE Trans. Veh. Technol., 2021

Deep Learning Based Channel Covariance Matrix Estimation With User Location and Scene Images.

[BibT_eX]

[DOI]

IEEE Trans. Commun., 2021

Deep Multimodal Learning: Merging Sensory Data for Massive MIMO Channel Prediction.

[BibT_eX]

[DOI]

IEEE J. Sel. Areas Commun., 2021

Learning Reflection Beamforming Codebooks for Arbitrary RIS and Non-Stationary Channels.

[BibT_eX]

[DOI]

CoRR, 2021

Computer Vision Aided URLL Communications: Proactive Service Identification and Coexistence.

[BibT_eX]

[DOI]

CoRR, 2021

Deep Learning for Moving Blockage Prediction using Real Millimeter Wave Measurements.

[BibT_eX]

[DOI]

CoRR, 2021

Millimeter Wave MIMO-Based Depth Maps for Wireless Virtual and Augmented Reality.

[BibT_eX]

[DOI]

IEEE Access, 2021

Enabling Large Intelligent Surfaces With Compressive Sensing and Deep Learning.

[BibT_eX]

[DOI]

IEEE Access, 2021

Deep Learning Based Channel Covariance Matrix Estimation with Scene Images.

[BibT_eX]

[DOI]

Proceedings of the 10th IEEE/CIC International Conference on Communications in China, 2021

Sensory Data Assisted Downlink Channel Prediction for Massive MIMO.

[BibT_eX]

[DOI]

Proceedings of the ICC 2021, 2021

Vision-Aided Dynamic Blockage Prediction for 6G Wireless Communication Networks.

[BibT_eX]

[DOI]

Proceedings of the IEEE International Conference on Communications Workshops, 2021

Deep Learning for THz Drones with Flying Intelligent Surfaces: Beam and Handoff Prediction.

[BibT_eX]

[DOI]

Proceedings of the IEEE International Conference on Communications Workshops, 2021

Autoencoder-based Communications with Reconfigurable Intelligent Surfaces.

[BibT_eX]

[DOI]

Proceedings of the IEEE International Symposium on Dynamic Spectrum Access Networks, 2021

2020

Deep Learning for Massive MIMO With 1-Bit ADCs: When More Antennas Need Fewer Pilots.

[BibT_eX]

[DOI]

IEEE Wirel. Commun. Lett., 2020

3D Scene-Based Beam Selection for mmWave Communications.

[BibT_eX]

[DOI]

IEEE Wirel. Commun. Lett., 2020

Deep Transfer Learning-Based Downlink Channel Prediction for FDD Massive MIMO Systems.

[BibT_eX]

[DOI]

IEEE Trans. Commun., 2020

Deep Reinforcement Learning for 5G Networks: Joint Beamforming, Power Control, and Interference Coordination.

[BibT_eX]

[DOI]

Faris B. Mismar

Brian L. Evans

IEEE Trans. Commun., 2020

Deep Learning for mmWave Beam and Blockage Prediction Using Sub-6 GHz Channels.

[BibT_eX]

[DOI]

IEEE Trans. Commun., 2020

Relay Aided Intelligent Reconfigurable Surfaces: Achieving the Potential Without So Many Antennas.

[BibT_eX]

[DOI]

Xiaoyan Ying

CoRR, 2020

ViWi Vision-Aided mmWave Beam Tracking: Dataset, Task, and Baseline Solutions.

[BibT_eX]

[DOI]

CoRR, 2020

Advanced Receiver Architectures for Millimeter-Wave Communications with Low-Resolution ADCs.

[BibT_eX]

[DOI]

IEEE Commun. Mag., 2020

ViWi: A Deep Learning Dataset Framework for Vision-Aided Wireless Communications.

[BibT_eX]

[DOI]

Proceedings of the 91st IEEE Vehicular Technology Conference, 2020

Millimeter Wave Base Stations with Cameras: Vision-Aided Beam and Blockage Prediction.

[BibT_eX]

[DOI]

Andrew Hredzak

Proceedings of the 91st IEEE Vehicular Technology Conference, 2020

Learning Beam Codebooks with Neural Networks: Towards Environment-Aware mmWave MIMO.

[BibT_eX]

[DOI]

Proceedings of the 21st IEEE International Workshop on Signal Processing Advances in Wireless Communications, 2020

Deep Reinforcement Learning for Intelligent Reflecting Surfaces: Towards Standalone Operation.

[BibT_eX]

[DOI]

Proceedings of the 21st IEEE International Workshop on Signal Processing Advances in Wireless Communications, 2020

Reinforcement Learning for Beam Pattern Design in Millimeter Wave and Massive MIMO Systems.

[BibT_eX]

[DOI]

Proceedings of the 54th Asilomar Conference on Signals, Systems, and Computers, 2020

Situation-Aware Channel Covariance Prediction for Deep Learning Aided Massive MIMO Systems.

[BibT_eX]

[DOI]

Proceedings of the 54th Asilomar Conference on Signals, Systems, and Computers, 2020

Deep Learning Based MIMO Channel Prediction: An Initial Proof of Concept Prototype.

[BibT_eX]

[DOI]

Proceedings of the 54th Asilomar Conference on Signals, Systems, and Computers, 2020

Vision Aided URLL Communications: Proactive Service Identification and Coexistence.

[BibT_eX]

[DOI]

Proceedings of the 54th Asilomar Conference on Signals, Systems, and Computers, 2020

2019

Deep Learning for mmWave Beam and Blockage Prediction Using Sub-6GHz Channels.

[BibT_eX]

[DOI]

CoRR, 2019

DeepMIMO: A Generic Deep Learning Dataset for Millimeter Wave and Massive MIMO Applications.

[BibT_eX]

[DOI]

CoRR, 2019

Wireless Communications and Applications Above 100 GHz: Opportunities and Challenges for 6G and Beyond.

[BibT_eX]

[DOI]

Theodore S. Rappaport

Georgios C. Trichopoulos

IEEE Access, 2019

Leveraging mmWave Imaging and Communications for Simultaneous Localization and Mapping.

[BibT_eX]

[DOI]

Mohammed Aladsani

Georgios C. Trichopoulos

Proceedings of the IEEE International Conference on Acoustics, 2019

Deep Learning for Large Intelligent Surfaces in Millimeter Wave and Massive MIMO Systems.

[BibT_eX]

[DOI]

Proceedings of the 2019 IEEE Global Communications Conference, 2019

Deep Learning for TDD and FDD Massive MIMO: Mapping Channels in Space and Frequency.

[BibT_eX]

[DOI]

Proceedings of the 53rd Asilomar Conference on Signals, Systems, and Computers, 2019

Deep Learning for Direct Hybrid Precoding in Millimeter Wave Massive MIMO Systems.

[BibT_eX]

[DOI]

Xiaofeng Li

Proceedings of the 53rd Asilomar Conference on Signals, Systems, and Computers, 2019

2018

Machine Learning for Reliable mmWave Systems: Blockage Prediction and Proactive Handoff.

[BibT_eX]

[DOI]

Iz Beltagy

CoRR, 2018

Deep Learning Coordinated Beamforming for Highly-Mobile Millimeter Wave Systems.

[BibT_eX]

[DOI]

IEEE Access, 2018

Beamforming in Millimeter Wave Systems: Prototyping and Measurement Results.

[BibT_eX]

[DOI]

Proceedings of the 88th IEEE Vehicular Technology Conference, 2018

Machine Learning for Reliable MMWAVE Systems: Blockage Prediction and Proactive Handoff.

[BibT_eX]

[DOI]

Iz Beltagy

Sam Alex

Proceedings of the 2018 IEEE Global Conference on Signal and Information Processing, 2018

Generative Adversarial Estimation of Channel Covariance in Vehicular Millimeter Wave Systems.

[BibT_eX]

[DOI]

Xiaofeng Li

Cihan Tepedelenlioglu

Proceedings of the 52nd Asilomar Conference on Signals, Systems, and Computers, 2018

2017

Dynamic Subarrays for Hybrid Precoding in Wideband mmWave MIMO Systems.

[BibT_eX]

[DOI]

Sungwoo Park

IEEE Trans. Wirel. Commun., 2017

Hybrid Architectures With Few-Bit ADC Receivers: Achievable Rates and Energy-Rate Tradeoffs.

[BibT_eX]

[DOI]

IEEE Trans. Wirel. Commun., 2017

Initial Beam Association in Millimeter Wave Cellular Systems: Analysis and Design Insights.

[BibT_eX]

[DOI]

IEEE Trans. Wirel. Commun., 2017

Multi-Layer Precoding: A Potential Solution for Full-Dimensional Massive MIMO Systems.

[BibT_eX]

[DOI]

IEEE Trans. Wirel. Commun., 2017

Modeling and Analyzing Millimeter Wave Cellular Systems.

[BibT_eX]

[DOI]

IEEE Trans. Commun., 2017

Channel Estimation for Hybrid Architecture-Based Wideband Millimeter Wave Systems.

[BibT_eX]

[DOI]

Kiran Venugopal

IEEE J. Sel. Areas Commun., 2017

Time-domain channel estimation for wideband millimeter wave systems with hybrid architecture.

[BibT_eX]

[DOI]

Kiran Venugopal

Proceedings of the 2017 IEEE International Conference on Acoustics, 2017

2016

Massive MIMO Combining with Switches.

[BibT_eX]

[DOI]

IEEE Wirel. Commun. Lett., 2016

Millimeter Wave Energy Harvesting.

[BibT_eX]

[DOI]

Talha Ahmed Khan

IEEE Trans. Wirel. Commun., 2016

Frequency Selective Hybrid Precoding for Limited Feedback Millimeter Wave Systems.

[BibT_eX]

[DOI]

IEEE Trans. Commun., 2016

Gains of Restricted Secondary Licensing in Millimeter Wave Cellular Systems.

[BibT_eX]

[DOI]

IEEE J. Sel. Areas Commun., 2016

Hybrid MIMO Architectures for Millimeter Wave Communications: Phase Shifters or Switches?

[BibT_eX]

[DOI]

Roi Méndez-Rial

Cristian Rusu

IEEE Access, 2016

Achievable Rates of Hybrid Architectures with Few-Bit ADC Receivers.

[BibT_eX]

[DOI]

Proceedings of the WSA 2016, 2016

Gram Schmidt based greedy hybrid precoding for frequency selective millimeter wave MIMO systems.

[BibT_eX]

[DOI]

Proceedings of the 2016 IEEE International Conference on Acoustics, 2016

Restricted Secondary Licensing for mmWave Cellular: How Much Gain Can Be Obtained?

[BibT_eX]

[DOI]

Proceedings of the 2016 IEEE Global Communications Conference, 2016

Dynamic subarray architecture for wideband hybrid precoding in millimeter wave massive MIMO systems.

[BibT_eX]

[DOI]

Sungwoo Park

Proceedings of the 2016 IEEE Global Conference on Signal and Information Processing, 2016

2015

Limited Feedback Hybrid Precoding for Multi-User Millimeter Wave Systems.

[BibT_eX]

[DOI]

IEEE Trans. Wirel. Commun., 2015

Channel estimation and hybrid combining for mmWave: Phase shifters or switches?

[BibT_eX]

[DOI]

Roi Méndez-Rial

Cristian Rusu

Proceedings of the 2015 Information Theory and Applications Workshop, 2015

Achievable rates of multi-user millimeter wave systems with hybrid precoding.

[BibT_eX]

[DOI]

Proceedings of the IEEE International Conference on Communication, 2015

Compressed sensing based multi-user millimeter wave systems: How many measurements are needed?

[BibT_eX]

[DOI]

Proceedings of the 2015 IEEE International Conference on Acoustics, 2015

Energy Coverage in Millimeter Wave Energy Harvesting Networks.

[BibT_eX]

[DOI]

Talha Ahmed Khan

Proceedings of the 2015 IEEE Globecom Workshops, San Diego, CA, USA, December 6-10, 2015, 2015

Opportunistic beam training with hybrid analog/digital codebooks for mmWave systems.

[BibT_eX]

[DOI]

Proceedings of the 2015 IEEE Global Conference on Signal and Information Processing, 2015

A tractable model for per user rate in multiuser millimeter wave cellular networks.

[BibT_eX]

[DOI]

Mandar N. Kulkarni

Jeffrey G. Andrews

Proceedings of the 49th Asilomar Conference on Signals, Systems and Computers, 2015

2014

Channel Estimation and Hybrid Precoding for Millimeter Wave Cellular Systems.

[BibT_eX]

[DOI]

IEEE J. Sel. Top. Signal Process., 2014

Coverage and capacity of millimeter-wave cellular networks.

[BibT_eX]

[DOI]

Tianyang Bai

IEEE Commun. Mag., 2014

Mimo precoding and combining solutions for millimeter-wave systems.

[BibT_eX]

[DOI]

Jianhua Mo

IEEE Commun. Mag., 2014

Single-sided adaptive estimation of multi-path millimeter wave channels.

[BibT_eX]

[DOI]

Proceedings of the 2014 IEEE 15th International Workshop on Signal Processing Advances in Wireless Communications (SPAWC), 2014

Initial beamforming for mmWave communications.

[BibT_eX]

[DOI]

Proceedings of the 48th Asilomar Conference on Signals, Systems and Computers, 2014

Multi-layer precoding for full-dimensional massive MIMO systems.

[BibT_eX]

[DOI]