7 papers · 1 filter
Interference-Aware Super-Constellation Design for NOMA
Mojtaba Vaezi, Xinliang Zhang
Non-orthogonal multiple access (NOMA) has gained significant attention as a potential next-generation multiple access technique. However, its implementation with finite-alphabet in…
Deep Autoencoder-based Z-Interference Channels with Perfect and Imperfect CSI
Xinliang Zhang, Mojtaba Vaezi
A deep autoencoder (DAE)-based structure for endto-end communication over the two-user Z-interference channel (ZIC) with finite-alphabet inputs is designed in this paper. The propo…
Interference-Aware Constellation Design for Z-Interference Channels with Imperfect CSI
Xinliang Zhang, Mojtaba Vaezi, Lizhong Zheng
A deep autoencoder (DAE)-based end-to-end communication over the two-user Z-interference channel (ZIC) with finite-alphabet inputs is designed in this paper. The design is for impe…
Complex Rotation-based Linear Precoding for Physical Layer Multicasting and SWIPT
Xinliang Zhang, Mojtaba Vaezi
With the goal of improving spectral efficiency, complex rotation-based precoding and power allocation schemes are developed for two multiple-input multiple-output (MIMO) communicat…
SVD-Embedded Deep Autoencoder for MIMO Communications
Xinliang Zhang, Mojtaba Vaezi, Timothy J. O'Shea
Using a deep autoencoder (DAE) for end-to-end communication in multiple-input multiple-output (MIMO) systems is a novel concept with significant potential. DAE-aided MIMO has been…
Deep Learning based Precoding for the MIMO Gaussian Wiretap Channel
Xinliang Zhang, Mojtaba Vaezi
A novel precoding method based on supervised deep neural networks is introduced for the multiple-input multiple-output Gaussian wiretap channel. The proposed deep learning (DL)-bas…