An Unsupervised Deep Unfolding Framework for Robust Symbol-Level Precoding

An Unsupervised Deep Unfolding Framework for Robust Symbol-Level Precoding

Symbol Level Precoding (SLP) has attracted significant research interest due to its ability to exploit interference for energy-efficient transmission. This paper proposes an unsupervised deep-neural network (DNN) based SLP framework. Instead of naively training a DNN architecture for SLP without con...

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Bibliographic Details
Main Authors: Abdullahi Mohammad, Christos Masouros, Yiannis Andreopoulos
Format: Article
Language:English
Published: IEEE 2023-01-01
Series:IEEE Open Journal of the Communications Society
Subjects:
Symbol level precoding
constructive interference
downlink beamforming
power minimization
deep neural networks
Online Access:https://ieeexplore.ieee.org/document/10111043/

Internet

https://ieeexplore.ieee.org/document/10111043/

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