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Channel Estimation using Temporal Convolutional Networks for V2X Communications
Juan D. Jovane
,
Chia Han Lee
電機工程學系
研究成果
:
Conference contribution
›
同行評審
2
引文 斯高帕斯（Scopus）
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Keyphrases
Art Performance
9%
Bit Error Rate
9%
Channel Estimation
100%
Channel Estimator
9%
Channel Variation
9%
Computational Complexity
18%
Deep Neural Network
27%
Estimation Scheme
9%
Frequency Domain Interpolation
9%
IEEE 802.11p
9%
Long Short-term Memory
81%
Memory Data
27%
Memory-based
27%
Network Architecture
9%
Network Data
27%
Neural Network
9%
Order of Magnitude
9%
Parallelization
9%
Pilot-aided
100%
Pilot-aided Channel Estimation
9%
Reliable Test
9%
Satisfactory Performance
9%
Spectro-temporal
18%
Temporal Averaging
18%
Temporal Convolutional Network
100%
Traditional Data
9%
Training Time
9%
V2X Communication
100%
Vehicle-to-everything Communication
9%
Computer Science
Art Performance
11%
channel estimate
11%
Channel Estimation
100%
Computational Complexity
22%
Deep Neural Network
33%
Estimation Scheme
11%
Frequency Domain
11%
Long Short-Term Memory Network
100%
Network Architecture
11%
Parallelism
11%
Temporal Convolutional Network
100%
Engineering
Aided Channel Estimation
8%
Bit Error Rate
8%
Channel Estimation
100%
Channel Variation
8%
Computational Complexity
16%
Deep Neural Network
25%
Estimation Scheme
8%
Frequency Domain
8%
Long Short-Term Memory
75%
Parallelism
8%
Pilot Data
100%
Time Domain
8%