Environmental-Aware Scheduler for Trustworthy 6G Communication

Roya Khanzadeh; Fjolla Ademaj-Berisha; Andreas Springer; Hans-Peter Bernhard

doi:10.1109/ICUFN65838.2025.11169904

Environmental-Aware Scheduler for Trustworthy 6G Communication

Roya Khanzadeh, Fjolla Ademaj-Berisha, Andreas Springer, Hans-Peter Bernhard

Research output: Chapter in Book/Report/Conference proceeding › Conference proceedings › peer-review

Abstract

Trustworthiness is emerging as a critical design objective for 6G networks, ensuring consistent and reliable performance under dynamic conditions. While several studies have addressed its evaluation, enhancing trustworthiness through intelligent network optimization remains largely unexplored. This paper proposes a deep reinforcement learning-based scheduler that integrates environmental-aware knowledge from channel knowledge maps to optimize reliability, availability, and fairness aspects of trustworthiness. Compared to the round-robin scheduler, the proposed method improves reliability by over 300 it improves availability and fairness by 61.40.6 respectively, with just a 4.5aware scheduling solution for trustworthy 6G.

Original language	English
Title of host publication	The 16th International Conference on Ubiquitous and Future Networks
Pages	291-293
Number of pages	3
ISBN (Electronic)	9798331524876
DOIs	https://doi.org/10.1109/ICUFN65838.2025.11169904
Publication status	Published - 30 Sept 2025

Publication series

Name	International Conference on Ubiquitous and Future Networks, ICUFN
ISSN (Print)	2165-8528
ISSN (Electronic)	2165-8536

Fields of science

202030 Communication engineering
202037 Signal processing
202038 Telecommunications
202 Electrical Engineering, Electronics, Information Engineering

JKU Focus areas

Digital Transformation

Access to Document

10.1109/ICUFN65838.2025.11169904

Cite this

@inproceedings{3a74f3292c424654a4037f6d98fcf557,

title = "Environmental-Aware Scheduler for Trustworthy 6G Communication",

abstract = "Trustworthiness is emerging as a critical design objective for 6G networks, ensuring consistent and reliable performance under dynamic conditions. While several studies have addressed its evaluation, enhancing trustworthiness through intelligent network optimization remains largely unexplored. This paper proposes a deep reinforcement learning-based scheduler that integrates environmental-aware knowledge from channel knowledge maps to optimize reliability, availability, and fairness aspects of trustworthiness. Compared to the round-robin scheduler, the proposed method improves reliability by over 300 it improves availability and fairness by 61.40.6 respectively, with just a 4.5aware scheduling solution for trustworthy 6G.",

author = "Roya Khanzadeh and Fjolla Ademaj-Berisha and Andreas Springer and Hans-Peter Bernhard",

year = "2025",

month = sep,

day = "30",

doi = "10.1109/ICUFN65838.2025.11169904",

language = "English",

series = "International Conference on Ubiquitous and Future Networks, ICUFN",

pages = "291--293",

booktitle = "The 16th International Conference on Ubiquitous and Future Networks",

}

Environmental-Aware Scheduler for Trustworthy 6G Communication. / Khanzadeh, Roya; Ademaj-Berisha, Fjolla; Springer, Andreas et al.
The 16th International Conference on Ubiquitous and Future Networks. 2025. p. 291-293 (International Conference on Ubiquitous and Future Networks, ICUFN).

Research output: Chapter in Book/Report/Conference proceeding › Conference proceedings › peer-review

TY - GEN

T1 - Environmental-Aware Scheduler for Trustworthy 6G Communication

AU - Khanzadeh, Roya

AU - Ademaj-Berisha, Fjolla

AU - Springer, Andreas

AU - Bernhard, Hans-Peter

PY - 2025/9/30

Y1 - 2025/9/30

N2 - Trustworthiness is emerging as a critical design objective for 6G networks, ensuring consistent and reliable performance under dynamic conditions. While several studies have addressed its evaluation, enhancing trustworthiness through intelligent network optimization remains largely unexplored. This paper proposes a deep reinforcement learning-based scheduler that integrates environmental-aware knowledge from channel knowledge maps to optimize reliability, availability, and fairness aspects of trustworthiness. Compared to the round-robin scheduler, the proposed method improves reliability by over 300 it improves availability and fairness by 61.40.6 respectively, with just a 4.5aware scheduling solution for trustworthy 6G.

AB - Trustworthiness is emerging as a critical design objective for 6G networks, ensuring consistent and reliable performance under dynamic conditions. While several studies have addressed its evaluation, enhancing trustworthiness through intelligent network optimization remains largely unexplored. This paper proposes a deep reinforcement learning-based scheduler that integrates environmental-aware knowledge from channel knowledge maps to optimize reliability, availability, and fairness aspects of trustworthiness. Compared to the round-robin scheduler, the proposed method improves reliability by over 300 it improves availability and fairness by 61.40.6 respectively, with just a 4.5aware scheduling solution for trustworthy 6G.

UR - https://www.scopus.com/pages/publications/105018736232

U2 - 10.1109/ICUFN65838.2025.11169904

DO - 10.1109/ICUFN65838.2025.11169904

M3 - Conference proceedings

T3 - International Conference on Ubiquitous and Future Networks, ICUFN

SP - 291

EP - 293

BT - The 16th International Conference on Ubiquitous and Future Networks

ER -

Environmental-Aware Scheduler for Trustworthy 6G Communication

Abstract

Publication series

Fields of science

JKU Focus areas

Access to Document

Other files and links

JKU LIT - SAL Intelligent Wireless Systems Lab (IWS Lab)

Cite this

Environmental-Aware Scheduler for Trustworthy 6G Communication

Abstract

Publication series

Fields of science

JKU Focus areas

Access to Document

Other files and links

Projects

JKU LIT - SAL Intelligent Wireless Systems Lab (IWS Lab)

Cite this