6G OFDM Communications with High Mobility Transceivers and Scatterers via Angle-Domain Processing and Deep Learning
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| Main Authors: | , , , |
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| Format: | Preprint |
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2026
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| _version_ | 1866917210085130240 |
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| author | Marchese, Mauro Keskin, Musa Furkan Wymeersch, Henk Savazzi, Pietro |
| author_facet | Marchese, Mauro Keskin, Musa Furkan Wymeersch, Henk Savazzi, Pietro |
| contents | High-mobility communications, which are crucial for next-generation wireless systems, cause the orthogonal frequency division multiplexing (OFDM) waveform to suffer from strong intercarrier interference (ICI) due to the Doppler effect. In this work, we propose a novel receiver architecture for OFDM that leverages the angular domain to separate multipaths. A block-type pilot is sent to estimate direction-of-arrivals (DoAs), propagation delays, and channel gains of the multipaths. Subsequently, a decision-directed (DD) approach is employed to estimate and iteratively refine the Dopplers. Two different approaches are investigated to provide initial Doppler estimates: an error vector magnitude (EVM)-based method and a deep learning (DL)-based method. Simulation results reveal that the DL-based approach allows for constant bit error rate (BER) performance up to the maximum 6G speed of 1000 km/h. |
| format | Preprint |
| id |
arxiv_https___arxiv_org_abs_2601_12970 |
| institution | arXiv |
| publishDate | 2026 |
| record_format | arxiv |
| spellingShingle | 6G OFDM Communications with High Mobility Transceivers and Scatterers via Angle-Domain Processing and Deep Learning Marchese, Mauro Keskin, Musa Furkan Wymeersch, Henk Savazzi, Pietro Signal Processing High-mobility communications, which are crucial for next-generation wireless systems, cause the orthogonal frequency division multiplexing (OFDM) waveform to suffer from strong intercarrier interference (ICI) due to the Doppler effect. In this work, we propose a novel receiver architecture for OFDM that leverages the angular domain to separate multipaths. A block-type pilot is sent to estimate direction-of-arrivals (DoAs), propagation delays, and channel gains of the multipaths. Subsequently, a decision-directed (DD) approach is employed to estimate and iteratively refine the Dopplers. Two different approaches are investigated to provide initial Doppler estimates: an error vector magnitude (EVM)-based method and a deep learning (DL)-based method. Simulation results reveal that the DL-based approach allows for constant bit error rate (BER) performance up to the maximum 6G speed of 1000 km/h. |
| title | 6G OFDM Communications with High Mobility Transceivers and Scatterers via Angle-Domain Processing and Deep Learning |
| topic | Signal Processing |
| url | https://arxiv.org/abs/2601.12970 |