35 citations · 41 across the 10 of their papers we have counts for
11 papers
Eunoia: Toward Application-Transparent, Scalable GPU Sharing in AI-RAN
Zongshen Wu, Marko Milenković, Jiarong Xing +1
The AI-RAN paradigm makes the next-generation cellular network more versatile by co-locating AI and RAN workloads on the same commodity hardware. While the GPU is a promising platf…
An Analytical and Experimental Study of Distributed Uplink Beamforming in the Presence of Carrier Frequency Offsets
Mehdi Zafari, Divyanshu Pandey, Rahman Doost-Mohammady
Realizing distributed multi-user beamforming (D-MUBF) in time division duplex (TDD)-based multi-user MIMO (MU-MIMO) systems faces significant challenges. One of the most fundamenta…
ADMM for Downlink Beamforming in Cell-Free Massive MIMO Systems
Mehdi Zafari, Divyanshu Pandey, Rahman Doost-Mohammady +1
In cell-free massive MIMO systems with multiple distributed access points (APs) serving multiple users over the same time-frequency resources, downlink beamforming is done through…
Multi-Provider Resource Scheduling in Massive MIMO Radio Access Networks
Qing An, Divyanshu Pandey, Rahman Doost-Mohammady +2
An important aspect of 5G networks is the development of Radio Access Network (RAN) slicing, a concept wherein the virtualized infrastructure of wireless networks is subdivided int…
ML-Based Feedback-Free Adaptive MCS Selection for Massive Multi-User MIMO
Qing An, Mehdi Zafari, Chris Dick +3
As wireless communication systems strive to improve spectral efficiency, there has been a growing interest in employing machine learning (ML)-based approaches for adaptive modulati…
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.…
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…
Annealed Langevin Dynamics for Massive MIMO Detection
Nicolas Zilberstein, Chris Dick, Rahman Doost-Mohammady +2
Solving the optimal symbol detection problem in multiple-input multiple-output (MIMO) systems is known to be NP-hard. Hence, the objective of any detector of practical relevance is…
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…
Leveraging Deliberately Generated Interferences for Multi-sensor Wireless RF Power Transmission
Raul G. Cid-Fuentes, M. Yousof Naderi, Rahman Doost-Mohammady +3
Wireless RF power transmission promises battery-less, resilient, and perpetual wireless sensor networks. Through the action of controllable Energy Transmitters (ETs) that operate a…