@inproceedings{685721ea0d97431bb0b69eb8f4ed7eec,
title = "Multiuser Fair Resource Allocation for Block-stationary Wireless Channels",
abstract = "We develop a resource allocation method for down-link multiuser wireless communication, where a multi-antenna base station communicates with multiple mobile nodes. We consider block-stationary environments to model node mobility in wireless networks. Our contributions are two-fold. First, we propose an algorithm that jointly optimizes power and user selection. Second, we propose a learning-based alternative that reduces the complexity of the proposed optimization-based algorithm. Experiments demonstrate the effectiveness of the proposed methods in performing resource allocation with reduced complexity in block-stationary environments.",
keywords = "Machine Learning, Non-Stationary, Resource Allocation",
author = "Reza Ramezanpour and Santiago Segarra and Ashutosh Sabharwal",
note = "Publisher Copyright: {\textcopyright} 2024 IEEE.; 58th Asilomar Conference on Signals, Systems and Computers, ACSSC 2024 ; Conference date: 27-10-2024 Through 30-10-2024",
year = "2024",
doi = "10.1109/IEEECONF60004.2024.10942776",
language = "English (US)",
series = "Conference Record - Asilomar Conference on Signals, Systems and Computers",
publisher = "Institute of Electrical and Electronics Engineers Inc.",
pages = "591--595",
editor = "Matthews, {Michael B.}",
booktitle = "Conference Record of the 58th Asilomar Conference on Signals, Systems and Computers, ACSSC 2024",
address = "United States",
}