2022
DOI: 10.48550/arxiv.2202.03997
|View full text |Cite
Preprint
|
Sign up to set email alerts
|

Wi-Fi Rate Adaptation using a Simple Deep Reinforcement Learning Approach

Abstract: The increasing complexity of recent Wi-Fi amendments is making optimal Rate Adaptation (RA) a challenge. The use of classic algorithms or heuristic models to address RA is becoming unfeasible due to the large combination of configuration parameters along with the variability of the wireless channel. Machine Learning-based solutions have been proposed in the state of art, to deal with this complexity. However, they typically use complex models and their implementation in real scenarios is difficult.We propose a… Show more

Help me understand this report

Search citation statements

Order By: Relevance

Paper Sections

Select...

Citation Types

0
0
0

Publication Types

Select...

Relationship

0
0

Authors

Journals

citations
Cited by 0 publications
references
References 17 publications
(20 reference statements)
0
0
0
Order By: Relevance

No citations

Set email alert for when this publication receives citations?