When Does a Neural Receiver Help? Calibration-Drift Benchmarking and Detect-and-Rollback for 5G/6G NR
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arXiv
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| Format: | Preprint |
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2026
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| _version_ | 1866916046635532288 |
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| author | Elnashar, Ayman |
| author_facet | Elnashar, Ayman |
| contents | Convolutional neural receivers such as DeepRx outperform minimum mean-square error physical uplink shared channel detection on in distribution channel and waveform configurations, but their behavior under calibration drift when transmitter or channel parameters depart from the training envelope is poorly characterized. |
| format | Preprint |
| id |
arxiv_https___arxiv_org_abs_2605_26157 |
| institution | arXiv |
| publishDate | 2026 |
| record_format | arxiv |
| spellingShingle | When Does a Neural Receiver Help? Calibration-Drift Benchmarking and Detect-and-Rollback for 5G/6G NR Elnashar, Ayman Information Theory Systems and Control Convolutional neural receivers such as DeepRx outperform minimum mean-square error physical uplink shared channel detection on in distribution channel and waveform configurations, but their behavior under calibration drift when transmitter or channel parameters depart from the training envelope is poorly characterized. |
| title | When Does a Neural Receiver Help? Calibration-Drift Benchmarking and Detect-and-Rollback for 5G/6G NR |
| topic | Information Theory Systems and Control |
| url | https://arxiv.org/abs/2605.26157 |