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Volumn , Issue , 2018, Pages

Channel Agnostic End-to-End Learning Based Communication Systems with Conditional GAN

Author keywords

[No Author keywords available]

Indexed keywords

CHANNEL CAPACITY; CHANNEL STATE INFORMATION; COMMUNICATION CHANNELS (INFORMATION THEORY); FADING CHANNELS; GAUSSIAN NOISE (ELECTRONIC); RAYLEIGH FADING; SIGNAL RECEIVERS; TRANSFER FUNCTIONS; WHITE NOISE;

EID: 85063534469     PISSN: None     EISSN: None     Source Type: Conference Proceeding    
DOI: 10.1109/GLOCOMW.2018.8644250     Document Type: Conference Paper
Times cited : (268)

References (15)
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  • 6
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    • Power of deep learning for channel estimation and signal detection in OFDM systems
    • Feb.
    • H. Ye, G. Y. Li, and B.-H. F. Juang, "Power of deep learning for channel estimation and signal detection in OFDM systems, " IEEE Wireless Commun. Lett., no. 7, pp. 114-117, Feb. 2018.
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    • Ye, H.1    Li, G.Y.2    Juang, B.-H.F.3
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    • Farsad, N.1    Rao, M.2    Goldsmith, A.3
  • 8
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    • An introduction to deep learning for the physical layer
    • Dec.
    • T. O'Shea and J. Hoydis, "An introduction to deep learning for the physical layer, " IEEE Trans. on Cogn. Commun. Netw., vol. 3, no. 4, pp. 563-575, Dec. 2017.
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    • O'Shea, T.1    Hoydis, J.2
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    • Generative adversarial nets
    • I. Goodfellow et al., "Generative adversarial nets, " in Proc. NIPS, pp. 2672-2680, 2014.
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    • Goodfellow, I.1


* 이 정보는 Elsevier사의 SCOPUS DB에서 KISTI가 분석하여 추출한 것입니다.