딥러닝을 활용한 무선 전송 및 접속 기술 동향
Research Trends on Wireless Transmission and Access Technologies Using Deep Learning
- 한국전자통신연구원
- 전자통신동향분석
- 전자통신동향분석 제33권 제5호
- : KCI등재
- 2018.10
- 13 - 23 (11 pages)
Deep learning is a promising solution to a number of complex problems based on its inherent capability to approximate almost all types of functions without the demand for handcrafted feature extraction. New wireless transmission and access schemes based on deep learning are being increasingly proposed as substitutes for existing approaches, providing a lower complexity and better performance gain. Among such schemes, a communications system is viewed as an end-to-end autoencoder. The learning process applied in autoencoders can automatically deal with some nonlinear or unknown properties in communications systems. Deep learning can also be used to optimize each processing block for required tasks such as channel decoding, signal detection, and multiple access. On top of recent related research trends, we suggest appropriate research approaches for communications systems to adopt deep learning.
Abstract
Ⅰ. 머리말
Ⅱ. 딥러닝과 무선통신기술
Ⅲ. 딥러닝 활용 무선전송 기술 동향
Ⅳ. 딥러닝 활용 무선접속 기술 동향
Ⅴ. 맺음말
참고문헌