2 citations · 3 across the 4 of their papers we have counts for
6 papers
Going Beyond RF: How AI-enabled Multimodal Beamforming will Shape the NextG Standard
Debashri Roy, Batool Salehi, Stella Banou +7
Incorporating artificial intelligence and machine learning (AI/ML) methods within the 5G wireless standard promises autonomous network behavior and ultra-low-latency reconfiguratio…
Detection by Sampling: Massive MIMO Detector based on Langevin Dynamics
Nicolas Zilberstein, Chris Dick, Rahman Doost-Mohammady +2
Optimal symbol detection in multiple-input multiple-output (MIMO) systems is known to be an NP-hard problem. Hence, the objective of any detector of practical relevance is to get r…
Robust MIMO Detection using Hypernetworks with Learned Regularizers
Nicolas Zilberstein, Chris Dick, Rahman Doost-Mohammady +2
Optimal symbol detection in multiple-input multiple-output (MIMO) systems is known to be an NP-hard problem. Recently, there has been a growing interest to get reasonably close to…
Signal Processing Based Deep Learning for Blind Symbol Decoding and Modulation Classification
Samer Hanna, Chris Dick, Danijela Cabric
Blindly decoding a signal requires estimating its unknown transmit parameters, compensating for the wireless channel impairments, and identifying the modulation type. While deep le…
Combining Deep Learning and Linear Processing for Modulation Classification and Symbol Decoding
Samer Hanna, Chris Dick, Danijela Cabric
Deep learning has been recently applied to many problems in wireless communications including modulation classification and symbol decoding. Many of the existing end-to-end learnin…
Multiuser MIMO Beamforming with Full-duplex Open-loop Training
Xu Du, John Tadrous, Chris Dick +1
In this paper, full-duplex radios are used to continuously update the channel state information at the transmitter, which is required to compute the downlink precoding matrix in MI…