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AI Enlightens Wireless Communication: Analyses, Solutions and Opportunities on CSI Feedback

2021/06/12 by Han Xiao, Xiao, Han, Zhiqin Wang +16
Computer Science · Engineering · #Algorithm #Artificial intelligence #Channel (broadcasting) #Channel state information #Competition (biology) #Computer science #FOS: Electrical engineering #Full-Duplex Wireless Communications #Preprocessor #Quantization (signal processing) #Radar Systems and Signal Processing #Signal Processing (eess.SP) #Telecommunications #Wireless #Wireless Signal Modulation Classification #Wireless network #eess.SP #electronic engineering #information engineering

paper · pdf · doi:10.48550/arxiv.2106.06759

published in arXiv (Cornell University) (Cornell University)

openalex publication_date 2021/06/12 · arxiv created 2021/06/15 · arxiv updated 2021/06/16 · openalex created_date 2021/06/22 · openalex updated_date 2026/08/06

Abstract

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 5G+AI Work Group. Firstly, the framework of full channel state information (F-CSI) feedback problem and its corresponding channel dataset are provided. Then the enhancing schemes for DL-based F-CSI feedback including i) channel data analysis and preprocessing, ii) neural network design and iii) quantization enhancement are elaborated. The final competition results composed of different enhancing schemes are presented. Based on the valuable experience of 1st WAIC, we also list some challenges and potential study areas for the design of AI-based wireless communication systems.

Citations

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