Wan-Ting Shih
National Chiao Tung University
8 Papers
Wan-Ting Shih is an academic researcher from National Chiao Tung University. The author has contributed to research in topics: Computer science & MIMO. The author has an hindex of 4, co-authored 5 publications. Previous affiliations of Wan-Ting Shih include National Sun Yat-sen University.
Chat about Author
Papers
Deep Learning for Massive MIMO CSI Feedback
TL;DR: In this article, a deep learning-based CSI sensing and recovery mechanism is proposed to learn to effectively use channel structure from training samples, which can recover CSI with significantly improved reconstruction quality compared with existing compressive sensing-based methods.
849
•Posted Content
Deep Learning for Massive MIMO CSI Feedback
TL;DR: In this article, a novel CSI sensing and recovery network that learns to effectively use channel structure from training samples is proposed. But, the CSI reconstruction quality is not significantly improved compared with existing compressive sensing (CS)-based methods.
640
Lightweight Convolutional Neural Networks for CSI Feedback in Massive MIMO
TL;DR: A DL-based CSI feedback network is developed in this study to complete the feedback of CSI effectively but this network cannot be effectively applied to the mobile terminal due to its excessive number of parameters and high computational complexity.
Reliable OFDM Receiver With Ultra-Low Resolution ADC
TL;DR: This work proposes a novel Q-OFDM channel estimator by extending the generalized Turbo (GTurbo) framework formerly applied for optimal detection, and integrates a type of robust linear OFDMChannel estimator into the original GTurbo framework, and derive its corresponding extrinsic information to guarantee its convergence.
•Posted Content
Lightweight Convolutional Neural Networks for CSI Feedback in Massive MIMO
TL;DR: In this paper, a DL-based CSI feedback network was proposed to complete the feedback of CSI effectively in frequency division duplex mode of massive multiple-input multiple-output (MIMO) systems.
11