4 citations · 8 across the 5 of their papers we have counts for
7 papers · 1 filter
Accumulated Polar Feature-based Deep Learning for Efficient and Lightweight Automatic Modulation Classification with Channel Compensation Mechanism
Chieh-Fang Teng, Ching-Yao Chou, Chun-Hsiang Chen +1
In next-generation communications, massive machine-type communications (mMTC) induce severe burden on base stations. To address such an issue, automatic modulation classification (…
Low-Complexity LSTM-Assisted Bit-Flipping Algorithm for Successive Cancellation List Polar Decoder
Chun-Hsiang Chen, Chieh-Fang Teng, An-Yeu Wu
Polar codes have attracted much attention in the past decade due to their capacity-achieving performance. The higher decoding capacity is required for 5G and beyond 5G (B5G). Altho…
Unsupervised Learning for Neural Network-based Polar Decoder via Syndrome Loss
Chieh-Fang Teng, An-Yeu Wu
With the rapid growth of deep learning in many fields, machine learning-assisted communication systems had attracted lots of researches with many eye-catching initial results. At t…
Convolutional Neural Network-aided Bit-flipping for Belief Propagation Decoding of Polar Codes
Chieh-Fang Teng, Kuan-Shiuan Ho, Chen-Hsi Wu +2
Known for their capacity-achieving abilities, polar codes have been selected as the control channel coding scheme for 5G communications. To satisfy the needs of high throughput and…
Neural Network-based Equalizer by Utilizing Coding Gain in Advance
Chieh-Fang Teng, Han-Mo Ou, An-Yeu Wu
Recently, deep learning has been exploited in many fields with revolutionary breakthroughs. In the light of this, deep learning-assisted communication systems have also attracted m…
Polar Feature Based Deep Architectures for Automatic Modulation Classification Considering Channel Fading
Chieh-Fang Teng, Ching-Chun Liao, Chun-Hsiang Chen +1
To develop intelligent receivers, automatic modulation classification (AMC) plays an important role for better spectrum utilization. The emerging deep learning (DL) technique has r…