221 citations · 988 across the 21 of their papers we have counts for
5 papers · 1 filter
Robust Non-Coherent Beamforming for FDD Downlink Massive MIMO
François Rottenberg, Ming-Chun Lee, Thomas Choi +2
Designing beamforming techniques for the downlink (DL) of frequency division duplex (FDD) massive MIMO is known to be a challenging problem due to the difficulty of obtaining chann…
RCNet: Incorporating Structural Information into Deep RNN for MIMO-OFDM Symbol Detection with Limited Training
Zhou Zhou, Lingjia Liu, Shashank Jere +3
In this paper, we investigate learning-based MIMO-OFDM symbol detection strategies focusing on a special recurrent neural network (RNN) -- reservoir computing (RC). We first introd…
Channel Extrapolation for FDD Massive MIMO: Procedure and Experimental Results
Thomas Choi, François Rottenberg, Jorge Gomez-Ponce +4
Application of massive multiple-input multiple-output (MIMO) systems to frequency division duplex (FDD) is challenging mainly due to the considerable overhead required for downlink…
Self-Tuning Sectorization: Deep Reinforcement Learning Meets Broadcast Beam Optimization
Rubayet Shafin, Hao Chen, Young Han Nam +6
Beamforming in multiple input multiple output (MIMO) systems is one of the key technologies for modern wireless communication. Creating appropriate sector-specific broadcast beams…
How Many Antennas Do We Need for Massive MIMO Channel Sounding? - Validating Through Measurement
Thomas Choi, François Rottenberg, Peng Luo +2
This paper investigates the impact of the number of antennas (8 to 64) and the array configuration on massive MIMO channel parameters estimation for multiple propagation scenarios…