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Conference Paper
Time-Varying Channel Tracking Based on Compressed Sensing
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- Authors
- Aoran Liu, Yuning Yu, Dalin Zhang, Pengqi Zhu, Jose Rodrıguez-Pineiro, Xuefeng Yin, Juyul Lee, Myung-Don Kim
- Issue Date
- 2023-11
- Citation
- Conference on Antenna Measurements and Applications (CAMA) 2023, pp.381-386
- Language
- English
- Type
- Conference Paper
- Abstract
- Autonomous vehicles and integrated sensing and communication (ISAC) are two key use cases for the sixth generation (6G) communications. Since both are typically utilized in time-varying scenarios, they are strongly dependent on effective propagation channel tracking strategies. compressed sensing (CS) provides a powerful method for decomposing time-domain signals into sparse-domain representations. In this paper, a time-varying channel tracking method based on CS is proposed and its ability proven by realistic simulations. The proposed method not only provides a representation of the channel variation over time related to the physical characteristics of the propagation environment, but also enables to easily establish a trade-off between the reconstruction accuracy (related to the amount of sparse coefficients used) and computational complexity. The proposed method aims to establish the foundations for time-varying ISAC applications in the context of 6G.
- KSP Keywords
- Autonomous vehicle, Channel Tracking, Compressed sensing, Computational complexity, Integrated sensing, Over time, Physical characteristics, Propagation Channel, Realistic simulation, Reconstruction accuracy, Time-varying channels