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- W4285158013 abstract "The next-generation communications impose requirements on integrated sensing and communication. However, the non-line-of-sight propagation in indoor complex environments poses great challenges to common localization techniques. In this letter, we propose a signal denoising network based on the transformer and temporal attention to improve the angle-of-arrival estimation accuracy. In the proposed network, the channel impulse response is denoised and reconstructed to mitigate errors. Then, two database are constructed based on self-built ultra-wideband transceivers in indoor environments for validation. Results show that the proposed network outperforms other machine learning methods in terms of angle-of-arrival estimation accuracy." @default.
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- W4285158013 date "2022-10-01" @default.
- W4285158013 modified "2023-09-23" @default.
- W4285158013 title "A Transformer-Based Signal Denoising Network for AoA Estimation in NLoS Environments" @default.
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- W4285158013 doi "https://doi.org/10.1109/lcomm.2022.3187661" @default.
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