Downlink CSIT under compressed feedback: Joint vs. separate source-channel coding
Modeling CSI compression at a UE given downlink reference signals as a remote rate-distortion problem and comparing separate vs joint source-channel coding
FDD Massive MIMO Channel Training: Optimal Rate-Distortion Bounds and the Spectral Efficiency of ``One-Shot” Schemes
We study the rate-distortion bound in training spatially correlated MIMO channels in a FDD system via Downlink pilot transmission and Uplink feedback. IEEE Transactions on Wireless Communications, Sep. 2023.
Deep-Learning Aided Channel Training and Precoding in FDD Massive MIMO with Channel Statistics Knowledge
We propose a method for channel training and precoding in FDD massive MIMO based on deep neural networks, exploiting Downlink channel covariance knowledge. IEEE International Conference on Communications (ICC) 2023.
Dual-Polarized FDD Massive MIMO: A Comprehensive Framework
We propose a comprehensive scheme for realizing a massive multiple-input multiple-output (MIMO) system with dual-polarized antennas in frequency division duplexing (FDD) mode. IEEE Transactions on Wireless Communications, Feb. 2022.
WiFi-based channel impulse response estimation and localization via multi-band splicing
We study the problem of channel impulse response (CIR) estimation from commodity WiFi channel state information (CSI). IEEE Global Communications Conference (Globecomm), 2020.
FDD massive MIMO via UL/DL channel covariance extrapolation and active channel sparsification
We propose active channel sparsification, a method of training multi-user MIMO Downlink channels in FDD mode with any given pilot length, while maximizing the effective channel matrix rank. IEEE Transactions on Wireless Communications, 2019.