<div class="csl-bib-body">
<div class="csl-entry">Schwarz, S., Mendoza, C. F., Zan, M., Rupp, M., & Kaneko, M. (2025, December 4). <i>Multi-Agent Deep Reinforcement Learning for Mobile Wireless Systems: From Distributed Power Allocation to Auction-Based RIS Access</i> [Presentation]. EURECOM Communications Systems Seminar 2025 : COMSYS TALK, Sophia Antipolis, France. https://doi.org/10.34726/11739</div>
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dc.identifier.uri
http://hdl.handle.net/20.500.12708/224882
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dc.identifier.uri
https://doi.org/10.34726/11739
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dc.description.abstract
Wireless systems are becoming increasingly complex, with a growing number of parameters to tune, a rising variety and heterogeneity of devices and equipment, and continuously evolving, diverse quality-of-service requirements. While centralized optimization may be theoretically optimal, it is often impractical in real-world deployments. This creates a need for methods that support distributed optimization and coordination among the goals of individual agents (e.g., users, operators, applications), while maintaining or improving network efficiency with manageable computational effort. In this talk, we explore the principles behind using deep reinforcement learning (DRL) as a promising approach for optimizing distributed multi-agent wireless systems. We illustrate its application to cell-free MIMO power allocation and the assignment of reconfigurable intelligent surfaces (RISs) in multi-operator scenarios, highlighting both the potential benefits and the challenges introduced by non-stationary multi-agent environments.
en
dc.description.sponsorship
FWF - Österr. Wissenschaftsfonds
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dc.language.iso
en
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dc.rights.uri
http://creativecommons.org/licenses/by-nc-sa/4.0/
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dc.subject
wireless communications
en
dc.subject
reinforcement learning
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dc.subject
multi agent
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dc.subject
cell-free MIMO
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dc.subject
reconfigurable intelligent surfaces
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dc.title
Multi-Agent Deep Reinforcement Learning for Mobile Wireless Systems: From Distributed Power Allocation to Auction-Based RIS Access
en
dc.type
Presentation
en
dc.type
Vortrag
de
dc.rights.license
Creative Commons Namensnennung - Nicht-kommerziell - Weitergabe unter gleichen Bedingungen 4.0 International
de
dc.rights.license
Creative Commons Attribution-NonCommercial-ShareAlike 4.0 International
en
dc.identifier.doi
10.34726/11739
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dc.relation.grantno
PAT4490824
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dc.rights.holder
Stefan Schwarz
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dc.type.category
Presentation
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tuw.publication.invited
invited
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tuw.project.title
Wettbewerb und Koordination durch Verstärkungslernen in rekonfigurierbaren drahtlosen Ausbreitungsumgebungen
