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 A Study on Reinforcement Learning Algorithm for Multi-Spectrum Channel Access 


Vol. 48,  No. 12, pp. 1568-1576, Dec.  2023
10.7840/kics.2023.48.12.1568


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  Abstract

This paper compares and analyzes performance by applying various reinforcement learning algorithms for multi-spectrum channel access in an 802.11ax-based wireless communication environment. In this paper, we present a channel access technology that uses reinforcement learning to prevent collisions and optimally utilizes channel resources. The application of this technology will help improve communication speed and develop future frequency utilization technology.

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[IEEE Style]

J. Chae, J. Park, K. Choi, "A Study on Reinforcement Learning Algorithm for Multi-Spectrum Channel Access," The Journal of Korean Institute of Communications and Information Sciences, vol. 48, no. 12, pp. 1568-1576, 2023. DOI: 10.7840/kics.2023.48.12.1568.

[ACM Style]

Jun-byung Chae, Jong-in Park, and Kae-won Choi. 2023. A Study on Reinforcement Learning Algorithm for Multi-Spectrum Channel Access. The Journal of Korean Institute of Communications and Information Sciences, 48, 12, (2023), 1568-1576. DOI: 10.7840/kics.2023.48.12.1568.

[KICS Style]

Jun-byung Chae, Jong-in Park, Kae-won Choi, "A Study on Reinforcement Learning Algorithm for Multi-Spectrum Channel Access," The Journal of Korean Institute of Communications and Information Sciences, vol. 48, no. 12, pp. 1568-1576, 12. 2023. (https://doi.org/10.7840/kics.2023.48.12.1568)
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