TA1a.4

Multiuser Fair Resource Allocation for Block-stationary Wireless Channels

Reza Ramezanpour, Santiago Segarra, Ashutosh Sabharwal, Rice University, United States
Session:
TA1a: Model-based Learning for Array Processing Lecture
Track:
Array Processing and Multisensor Systems
Location:
Heather
Presentation Time:
Tue, 29 Oct, 09:30 - 09:55 PT (UTC -8)
Session Co-Chairs:
Marius Pesavento, Technische Universität Darmstadt and Lukas Schynol, Technische Universität Darmstadt
Presentation
Discussion
Resources
No resources available.
Session TA1a
TA1a.1: Optimization of Iterative Blind Detection based on Expectation Maximization and Belief Propagation
Luca Schmid, Karlsruhe Institute of Technology, Germany; Tomer Raviv, Nir Shlezinger, Ben-Gurion University of the Negev, Israel; Laurent Schmalen, Karlsruhe Institute of Technology, Germany
TA1a.2: Enhancing Off-Grid One-Bit DOA Estimation with Learning-based Sparse Bayesian Approach for Non-Uniform Sparse Array
Yunqiao Hu, Shunqiao Sun, The University of Alabama, United States; Yimin D. Zhang, Temple University, United States
TA1a.3: Codebook-Based Downlink Beamforming with Imperfect CSI using Model-Driven Deep Learning
Lukas Schynol, Moritz Hemsing, Marius Pesavento, Technical University of Darmstadt, Germany
TA1a.4: Multiuser Fair Resource Allocation for Block-stationary Wireless Channels
Reza Ramezanpour, Santiago Segarra, Ashutosh Sabharwal, Rice University, United States
Contacts