no code implementations • 20 Oct 2023 • Qing An, Mehdi Zafari, Chris Dick, Santiago Segarra, Ashutosh Sabharwal, Rahman Doost-Mohammady
As wireless communication systems strive to improve spectral efficiency, there has been a growing interest in employing machine learning (ML)-based approaches for adaptive modulation and coding scheme (MCS) selection.
1 code implementation • 26 Oct 2022 • Nicolas Zilberstein, Chris Dick, Rahman Doost-Mohammady, Ashutosh Sabharwal, Santiago Segarra
We propose a multiple-input multiple-output (MIMO) detector based on an annealed version of the \emph{underdamped} Langevin (stochastic) dynamic.
1 code implementation • 11 May 2022 • Nicolas Zilberstein, Chris Dick, Rahman Doost-Mohammady, Ashutosh Sabharwal, Santiago Segarra
Based on the proposed MIMO detector, we also design a robust version of the method by unfolding and parameterizing one term -- the score of the likelihood -- by a neural network.
1 code implementation • 24 Feb 2022 • Nicolas Zilberstein, Chris Dick, Rahman Doost-Mohammady, Ashutosh Sabharwal, Santiago Segarra
Optimal symbol detection in multiple-input multiple-output (MIMO) systems is known to be an NP-hard problem.
no code implementations • 13 Oct 2021 • Nicolas Zilberstein, Chris Dick, Rahman Doost-Mohammady, Ashutosh Sabharwal, Santiago Segarra
Our method is based on hypernetworks that generate the parameters of a neural network-based detector that works well on a specific channel.
