Artificial intelligence (AI) has shown great potential in channel state information (CSI)
feedback problems. However, the existing works focus on further improving the performance …

Deep learning (DL) methods have been widely used for channel state information (CSI)
feedback to reduce the feedback overhead. CSI feedback mainly includes full CSI feedback …

This paper is based on the background of the 2nd Wireless Communication Artificial
Intelligence (AI) Competition (WAIC) which is hosted by IMT-2020 (5G) Promotion Group …

Recently, the autoencoder framework has shown great potential in reducing the feedback
overhead of the downlink channel state information (CSI). In this work, we further find that …

In this paper, we give a systematic description of the 1st Wireless Communication Artificial
Intelligence (AI) Competition (WAIC) which is hosted by IMT-2020 (5G) Promotion Group …

Deep learning has shown promise in enhancing channel state information (CSI) feedback.
However, many studies indicate that better feedback performance often accompanies higher …

In this paper, we introduce a novel scheme for the separate training of deep learning-based
autoencoders used for Channel State Information (CSI) feedback. Our distinct training …

Deep learning has been introduced to improve implicit channel state information (CSI)
feedback, and it significantly outperforms codebook-based feedback methods used in …

Recently, the autoencoder (AE) has been widely used in channel state information (CSI)
feedback to improve feedback performance. In practical systems, the user equipment (UE) …

The muti-task Channel State Information (CSI) feedback is a downlink CSI feedback
approach. It focuses on Clustered Delay Line (CDL) channel models as the channel …