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Speeding up Training of Linear Predictors for Multi-Antenna Frequency-Selective Channels via Meta-Learning
An efficient data-driven prediction strategy for multi-antenna frequency-selective channels must operate based on a small number of pilot symbols. This paper proposes novel channel-prediction algorithms that address this goal by integrating transfer and meta-learning with a reduced-rank parametrizat...
| Autores principales: | , |
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| Formato: | Online Artículo Texto |
| Lenguaje: | English |
| Publicado: |
MDPI
2022
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| Materias: | |
| Acceso en línea: | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC9600732/ https://www.ncbi.nlm.nih.gov/pubmed/37420383 http://dx.doi.org/10.3390/e24101363 |