Finetuning wireless receivers to a specific deployment scenario can yield significant error-rate performance improvements without increasing processing complexity. However, site-specific finetuning has so far only been demonstrated on synthetic channel data and lacks real-world benchmarks. In this work, we empirically study site-specific finetuning of neural receivers using real-world 5G NR physical uplink shared channel (PUSCH) data collected with an over-the-air testbed at ETH Zurich across three scenarios: (i) a small laboratory, (ii) a large office floor, and (iii) a high-mobility outdoor environment. Our results confirm substantial error-rate performance improvements from site-specific finetuning, consistent with earlier findings based on synthetic channel data. Moreover, we demonstrate that these improvements generalize across different user-equipment hardware and deployment scenarios.

翻译：将无线接收器针对特定部署场景进行微调，可在不增加处理复杂度的前提下显著提升误码率性能。然而，站点特定微调迄今仅在合成信道数据上得到验证，缺乏真实世界的基准测试。在本工作中，我们利用苏黎世联邦理工学院空中测试平台采集的真实世界5G NR物理上行共享信道数据，通过实证研究探讨了神经接收器的站点特定微调，涵盖三种场景：(i)小型实验室，(ii)大型办公楼层，以及(iii)高移动性室外环境。我们的结果证实了站点特定微调带来的误码率性能显著提升，这与早期基于合成信道数据的研究结论一致。此外，我们证明了这些改进在不同用户设备硬件和部署场景中均具有泛化能力。