A MIMO Wireless Channel Foundation Model via CIR-CSI Consistency

• URL: http://arxiv.org/abs/2502.11965v1
• Date: Mon, 17 Feb 2025 16:13:40 GMT
• Title: A MIMO Wireless Channel Foundation Model via CIR-CSI Consistency
• Authors: Jun Jiang, Wenjun Yu, Yunfan Li, Yuan Gao, Shugong Xu,
• Abstract summary: This paper treats Channel State Information (CSI) and Channel Impulse Response (CIR) as naturally aligned multi-modal data. By effectively capturing the joint representations of both CIR and CSI, CSI-CLIP exhibits remarkable adaptability across scenarios.
• Score: 19.658024410165112
• License:
• Abstract: In the field of artificial intelligence, self-supervised learning has demonstrated superior generalization capabilities by leveraging large-scale unlabeled datasets for pretraining, which is especially critical for wireless communication models to adapt to a variety of scenarios. This paper innovatively treats Channel State Information (CSI) and Channel Impulse Response (CIR) as naturally aligned multi-modal data and proposes the first MIMO wireless channel foundation model, named CSI-CLIP. By effectively capturing the joint representations of both CIR and CSI, CSI-CLIP exhibits remarkable adaptability across scenarios and robust feature extraction capabilities. Experimental results show that in positioning task, CSI-CLIP reduces the mean error distance by 22%; in beam management task, it increases accuracy by 1% compared to traditional supervised methods, as well as in the channel identification task. These improvements not only highlight the potential and value of CSI-CLIP in integrating sensing and communication but also demonstrate its significant advantages over existing techniques. Moreover, viewing CSI and CIR as multi-modal pairs and contrastive learning for wireless channel foundation model open up new research directions in the domain of MIMO wireless communications.

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