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Attention-enhanced DQN scheduling for multi-link devices in synchronous N-STR Wi-Fi 7 networks

  • 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 publication 2025 International Conference on Modeling, Analysis and Simulation of Wireless and Mobile Systems (MSWiM)
PublisherInstitute of Electrical and Electronics Engineers Inc.
Pages659-666
Number of pages8
ISBN (Electronic)9798331568733
DOIs
Publication statusPublished - 30 Dec 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 

Keywords

  • DQN
  • DRL
  • MLO
  • N-STR
  • Wi-Fi 7
  • [ComputerScience]

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