Machine Learning-Based Detection Mechanism of Random Access Preambles 


Vol. 46,  No. 2, pp. 264-267, Feb.  2021
10.7840/kics.2021.46.2.264


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  Abstract

In this paper, we propose a machine learning-based random access preamble detection method to improve the preamble detection performance in the cellular random access procedure. A convolutional neural network is developed for processing received preamble signals efficiently. The proposed technique shows a 3dB performance gain over conventional schemes given the same false detection alarm probability.

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  Cite this article

[IEEE Style]

H. S. Jang, H. Lee, M. Yun, D. Kim, "Machine Learning-Based Detection Mechanism of Random Access Preambles," The Journal of Korean Institute of Communications and Information Sciences, vol. 46, no. 2, pp. 264-267, 2021. DOI: 10.7840/kics.2021.46.2.264.

[ACM Style]

Han Seung Jang, Hoon Lee, Munseop Yun, and Daeik Kim. 2021. Machine Learning-Based Detection Mechanism of Random Access Preambles. The Journal of Korean Institute of Communications and Information Sciences, 46, 2, (2021), 264-267. DOI: 10.7840/kics.2021.46.2.264.

[KICS Style]

Han Seung Jang, Hoon Lee, Munseop Yun, Daeik Kim, "Machine Learning-Based Detection Mechanism of Random Access Preambles," The Journal of Korean Institute of Communications and Information Sciences, vol. 46, no. 2, pp. 264-267, 2. 2021. (https://doi.org/10.7840/kics.2021.46.2.264)

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pISSN : 1226 - 4717
eISSN : 2287 - 3880