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Attention-Enhanced DQN Scheduling for Multi-Link Devices in Synchronous N-STR Wi-Fi 7 Networks

  • University College Cork
  • Qena University

Research output: Chapter in Book/Report/Conference proceedingsConference proceedingpeer-review

Abstract

WiFi 7 IEEE (802.11be) introduced Multi-Link Operation (MLO) that enables its devices to communicate over multiple links to support evolving latency-sensitive and high-throughput applications. However, MLO requires advanced scheduling algorithms to optimize the operation. This paper models WiFi 7 scheduling as a constrained Markov Decision Process that optimizes throughput, delay, latency and fairness while capturing access constraints and traffic dynamics. We also develop an attention-enhanced Rainbow Deep Q-Network (DQN) scheduling framework that combines multi-head attention, distributional Q-learning, and prioritized experience replay. Simulation results show up to 2.3× throughput improvement, 6× delay reduction, and marked gains in packet drop rate and spectral efficiency over baseline Round Robin scheduling.

Original languageEnglish
Title of host publicationMSWiM 2025 - 27th International Conference on Modeling, Analysis and Simulation of Wireless and Mobile Systems
PublisherInstitute of Electrical and Electronics Engineers Inc.
Pages659-666
Number of pages8
ISBN (Electronic)9798331568733
DOIs
Publication statusPublished - 2025
Event27th International Conference on Modeling, Analysis and Simulation of Wireless and Mobile Systems, MSWiM 2025 - Barcelona, Spain
Duration: 27 Oct 202531 Oct 2025

Publication series

NameMSWiM 2025 - 27th International Conference on Modeling, Analysis and Simulation of Wireless and Mobile Systems

Conference

Conference27th International Conference on Modeling, Analysis and Simulation of Wireless and Mobile Systems, MSWiM 2025
Country/TerritorySpain
CityBarcelona
Period27/10/2531/10/25

UCC Futures

  • Future of Networks, Systems & Cybersecurity (NASC)

Keywords

  • DQN
  • DRL
  • MLO
  • N-STR
  • Wi-Fi 7

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