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| Main Authors: | , , , |
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| Format: | Preprint |
| Published: |
2025
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| Subjects: | |
| Online Access: | https://arxiv.org/abs/2512.23470 |
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| _version_ | 1866909977716719616 |
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| author | Jiang, Wenjun Yuan, Xiaojun Liu, Chenchen Teng, Boyu |
| author_facet | Jiang, Wenjun Yuan, Xiaojun Liu, Chenchen Teng, Boyu |
| contents | Channel knowledge map (CKM) is a promising paradigm for environment-aware communications by establishing a deterministic mapping between physical locations and channel parameters. Existing CKM construction methods focus on quasi-static propagation environment. This paper develops a dynamic CKM construction method for multiple-input multiple-output orthogonal frequency division multiplexing (MIMO-OFDM) systems. We establish a dynamic channel model that captures the coexistence of quasi-static and dynamic scatterers, as well as the impacts of antenna rotation and synchronization errors. Based on this model, we formulate the problem of dynamic CKM construction within a Bayesian inference framework and design a two-stage approximate Bayesian inference algorithm. In stage I, a high-performance algorithm is developed to jointly infer quasi-static channel parameters and calibrate synchronization errors from historical measurements. In stage II, by leveraging the quasi-static parameters as informative priors, a low-complexity algorithm is designed to estimate dynamic parameters from limited real-time measurements. Simulation results validate the superiority of the proposed method and demonstrate its effectiveness in enabling low-overhead, high-performance channel estimation in dynamic environments. |
| format | Preprint |
| id |
arxiv_https___arxiv_org_abs_2512_23470 |
| institution | arXiv |
| publishDate | 2025 |
| record_format | arxiv |
| spellingShingle | Dynamic Channel Knowledge Map Construction in MIMO-OFDM Systems Jiang, Wenjun Yuan, Xiaojun Liu, Chenchen Teng, Boyu Information Theory Channel knowledge map (CKM) is a promising paradigm for environment-aware communications by establishing a deterministic mapping between physical locations and channel parameters. Existing CKM construction methods focus on quasi-static propagation environment. This paper develops a dynamic CKM construction method for multiple-input multiple-output orthogonal frequency division multiplexing (MIMO-OFDM) systems. We establish a dynamic channel model that captures the coexistence of quasi-static and dynamic scatterers, as well as the impacts of antenna rotation and synchronization errors. Based on this model, we formulate the problem of dynamic CKM construction within a Bayesian inference framework and design a two-stage approximate Bayesian inference algorithm. In stage I, a high-performance algorithm is developed to jointly infer quasi-static channel parameters and calibrate synchronization errors from historical measurements. In stage II, by leveraging the quasi-static parameters as informative priors, a low-complexity algorithm is designed to estimate dynamic parameters from limited real-time measurements. Simulation results validate the superiority of the proposed method and demonstrate its effectiveness in enabling low-overhead, high-performance channel estimation in dynamic environments. |
| title | Dynamic Channel Knowledge Map Construction in MIMO-OFDM Systems |
| topic | Information Theory |
| url | https://arxiv.org/abs/2512.23470 |