CSI Compression using Channel Charting
Not on the map. Why?
Abstract (arXiv)
Reaping the benefits of multi-antenna communication systems in frequency division duplex (FDD) requires channel state information (CSI) reporting from mobile users to the base station (BS). Over the last decades, the amount of CSI to be collected has become very challenging owing to the dramatic increase of the number of antennas at BSs. To mitigate the overhead associated with CSI reporting, compressed CSI techniques have been proposed with the idea of recovering the original CSI at the BS from its compressed version sent by the mobile users. Channel charting is an unsupervised dimensionality reduction method that consists in building a radio-environment map from CSIs. Such a method can be considered in the context of the CSI compression problem, since a chart location is, by definition, a low-dimensional representation of the CSI. In this paper, the performance of channel charting for a task-based CSI compression application is studied. A comparison of the proposed method against baselines on realistic synthetic data is proposed, showing promising results.
Key facts. Cited by 1 paper in the map (data through 7 Oct 2026). Builds on 18 of its 28 references that are in the map. First posted on arXiv 16 Dec 2024.
Builds on
18 of 28 references.
References · 18
- 2020Fourier Features Let Networks Learn High Frequency Functions in Low Dimensional Domainscited by 2,170
- 2018On the Spectral Bias of Neural Networkscited by 1,321
- 2019Frequency Principle: Fourier Analysis Sheds Light on Deep Neural Networkscited by 360
- 2019Towards Understanding the Spectral Bias of Deep Learningcited by 173
- 2022Sionna: An Open-Source Library for Next-Generation Physical Layer Researchcited by 143
- 2019DeepMIMO: A Generic Deep Learning Dataset for Millimeter Wave and Massive MIMO Applicationscited by 121
- 2018Channel Charting: Locating Users within the Radio Environment using Channel State Informationcited by 40
- 2022Overview of Deep Learning-based CSI Feedback in Massive MIMO Systemscited by 35
- 2019Multi-resolution CSI Feedback with deep learning in Massive MIMO Systemcited by 29
- 2022Leveraging triplet loss and nonlinear dimensionality reduction for on-the-fly channel chartingcited by 10
- 2021Efficient channel charting via phase-insensitive distance computationcited by 8
- 2022Channel charting based beamformingcited by 5
6 more
- 2023Channel Charting in Real-World Coordinatescited by 5
- 2023Model-based learning for location-to-channel mappingcited by 4
- 2023Augmenting Channel Charting with Classical Wireless Source Localization Techniquescited by 4
- 2023Model-based Deep Learning for Beam Prediction based on a Channel Chartcited by 4
- 2023Channel Charting for Streaming CSI Datacited by 3
- 2024Model-based learning for multi-antenna multi-frequency location-to-channel mappingcited by 3
Built on by
Citing papers per year: 2025: 1.
1 paper.