activity
20062023
most citedExperiment-driven Characterization of Full-Duplex Wireless Systems

1.5k citations · 4.1k across the 63 of their papers we have counts for

collaborators

67 papers

stat.ML2023

Solving Linear Inverse Problems using Higher-Order Annealed Langevin Diffusion

Nicolas Zilberstein, Ashutosh Sabharwal, Santiago Segarra

We propose a solution for linear inverse problems based on higher-order Langevin diffusion. More precisely, we propose pre-conditioned second-order and third-order Langevin dynamic…

cs.IT2023★ 3 cited

Full-Duplex Wireless for 6G: Progress Brings New Opportunities and Challenges

Besma Smida, Ashutosh Sabharwal, Gabor Fodor +3

The use of in-band full-duplex (FD) enables nodes to simultaneously transmit and receive on the same frequency band, which challenges the traditional assumption in wireless network…

cs.IT2023★ 35 cited

A Deep Reinforcement Learning-Based Resource Scheduler for Massive MIMO Networks

Qing An, Santiago Segarra, Chris Dick +2

The large number of antennas in massive MIMO systems allows the base station to communicate with multiple users at the same time and frequency resource with multi-user beamforming.…

eess.SP2022

Accelerated massive MIMO detector based on annealed underdamped Langevin dynamics

Nicolas Zilberstein, Chris Dick, Rahman Doost-Mohammady +2

We propose a multiple-input multiple-output (MIMO) detector based on an annealed version of the \emph{underdamped} Langevin (stochastic) dynamic. Our detector achieves state-of-the…

eess.SY2022

Consensus ADMM-Based Distributed Simultaneous Imaging & Communication

Nishant Mehrotra, Ashutosh Sabharwal, César A. Uribe

This paper takes the first steps toward enabling wireless networks to perform both imaging and communication in a distributed manner. We propose Distributed Simultaneous Imaging an…

math.OC2022

Distributed Generalized Wirtinger Flow for Interferometric Imaging on Networks

Sean M. Farrell, Ashok Veeraraghavan, Ashutosh Sabharwal +1

We study the problem of decentralized interferometric imaging over networks, where agents have access to a subset of local radar measurements and can compute pair-wise correlations…