[
    {
        "id": "osp-16401",
        "type": "article-journal",
        "title": "SR-TTA: Spatial-Redundancy Test-Time Adaptation for Interference-Robust Respiration Sensing",
        "author": [
            {
                "family": "Liu",
                "given": "Jingyuan"
            },
            {
                "family": "Chang",
                "given": "Zheng"
            },
            {
                "family": "Xiong",
                "given": "Haoqiu"
            },
            {
                "family": "Cui",
                "given": "Zhuangzhuang"
            },
            {
                "family": "Pollin",
                "given": "Sofie"
            }
        ],
        "URL": "https://omanscience.com/en/articles/sr-tta-spatial-redundancy-test-time-adaptation-for-interference-robust-respiration-sensing",
        "language": "en",
        "issued": {
            "date-parts": [
                [
                    2026
                ]
            ]
        },
        "abstract": "Future 6G networks aim to expose sensing as a native service by reusing communication infrastructure. We study respiration sensing on a cell-free massive multiple-input multiple-output (MIMO) base station, where a 64-antenna channel must be fused into a breathing waveform. The state-of-the-art hand-crafted fusion is near-optimal in benign conditions. It collapses, however, under strong in-band motion interference, whose frequency falls inside the respiration band. We show that a learned complex-weight beamformer recovers respiration by spatial nulling, and that the remaining gap to a per-recording oracle can be closed at deployment by label-free test-time adaptation. Crucially, we identify which label-free signal makes this work. Frequency- and variance-based criteria cannot separate an in-band interferer from breathing. Our spatial-redundancy test-time adaptation (SR-TTA), which maximizes consistency across random antenna subsets under an out-of-band spectral veto, preserves benign performance in our tests. The respiration-rate error drops from 5.8 to 0.8 breaths per minute (bpm) under simulated in-band interference, and the pipeline maps onto the Open Radio Access Network (O-RAN) architecture as O-RAN distributed-unit (O-DU) range-gating, an adaptation xApp, and a calibration rApp. On real testbed recordings, a one-time cross-subject calibration plus SR-TTA reduces failures from 47% to 7%, drawing level with the hand-crafted combiner using label-free test-time adaptation."
    }
]