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001-es BibID:	BIBFORM126267
Első szerző:	Talbi, Djamila (mérnök informatikus)
Cím:	Analysis of the B5G/6G Communication Power Entropy Patterns Based on Generative AI Methods / Djamila Talbi, Zoltan Gal
Dátum:	2024
Megjegyzések:	Moving toward new and higher frequencies would bring the 6G communication network into practice. Using a new MAC mechanism will enhance and overcome the THz challenges. Our paper focused on analyzing the entropy interdependence between two subsystems, normal and lucky mobile terminals. The two introduced entropy metrics play a crucial role in interpreting the interdependence of the two subsystems. However, the lack of data obliged us to use GAN and its methods to generate similar data. Therefore, we used four different GAN methods plus the standard GAN to obtain the most significant data, and we determined the similarity using six different similarity metrics. The results showed that cosine and correlation similarities are not appropriate to capture the similarity, meanwhile, the rest; dynamic time warping, Frechet inception, root mean square error, and peak signal-to-noise ratio agreed that DCGAN was the one who generated the most accurate data series compared to the rest.
ISBN:	9798350387889
Tárgyszavak:	Műszaki tudományok Informatikai tudományok konferenciacikk folyóiratcikk 6G B5G Entropy MAC Mechanism Generative Adversarial Networks Adversarial Autoencoder Deep Convolutional GAN Least Squares GAN Wasserstein GAN
Megjelenés:	IEEE Xplore. - 2024 (2024), p. 1-6. -
További szerzők:	Gál Zoltán (1966-) (informatikus)
Pályázati támogatás:	TKP2021-NKTA-34 Egyéb
Internet cím:	Szerző által megadott URL DOI Intézményi repozitóriumban (DEA) tárolt változat
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