13 citations · 35 across the 13 of their papers we have counts for
12 papers · 1 filter
Decentralized Interference-Aware Codebook Learning in Millimeter Wave MIMO Systems
Yu Zhang, Ahmed Alkhateeb
Beam codebooks are integral components of the future millimeter wave (mmWave) multiple input multiple output (MIMO) system to relax the reliance on the instantaneous channel state…
Zone-Specific CSI Feedback for Massive MIMO: A Situation-Aware Deep Learning Approach
Yu Zhang, Ahmed Alkhateeb
Massive MIMO basestations, operating with frequency-division duplexing (FDD), require the users to feedback their channel state information (CSI) in order to design the precoding m…
A Digital Twin Assisted Framework for Interference Nulling in Millimeter Wave MIMO Systems
Yu Zhang, Tawfik Osman, Ahmed Alkhateeb
Millimeter wave (mmWave) and terahertz MIMO systems rely on pre-defined beamforming codebooks for both initial access and data transmission. However, most of the existing codebooks…
Predicting Future CSI Feedback For Highly-Mobile Massive MIMO Systems
Yu Zhang, Ahmed Alkhateeb, Pranav Madadi +3
Massive multiple-input multiple-output (MIMO) system is promising in providing unprecedentedly high data rate. To achieve its full potential, the transceiver needs complete channel…
Learning Reflection Beamforming Codebooks for Arbitrary RIS and Non-Stationary Channels
Yu Zhang, Ahmed Alkhateeb
Reconfigurable intelligent surfaces (RIS) are expected to play an important role in future wireless communication systems. These surfaces typically rely on their reflection beamfor…
Reinforcement Learning of Beam Codebooks in Millimeter Wave and Terahertz MIMO Systems
Yu Zhang, Muhammad Alrabeiah, Ahmed Alkhateeb
Millimeter wave (mmWave) and terahertz MIMO systems rely on pre-defined beamforming codebooks for both initial access and data transmission. Being pre-defined, however, these codeb…