Decentralized Expectation Propagation for Semi-Blind Channel Estimation in Cell-Free Networks
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arXiv
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| Hauptverfasser: | , |
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| Format: | Preprint |
| Veröffentlicht: |
2024
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| _version_ | 1866913526946201600 |
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| author | Zhao, Zilu Slock, Dirk |
| author_facet | Zhao, Zilu Slock, Dirk |
| contents | This paper serves as a correction to the conference version. In this work, we explore uplink communication in cell-free (CF) massive multiple-input multiple-output (MaMIMO) systems, employing semi-blind transmission structures to mitigate pilot contamination. We propose a simplified, decentralized method based on Expectation Propagation (EP) for semi-blind channel estimation. By utilizing orthogonal pilots, we preprocess the received signals to establish a simplified equivalent factorization scheme for the transmission process. Moreover, this study integrates Central Limit Theory (CLT) with EP, eliminating the need to introduce new auxiliary variables in the factorization scheme. We also refine the algorithm by assessing the variable scales involved. Finally, a decentralized approach is proposed to significantly reduce the computational demands on the Central Processing Unit (CPU). |
| format | Preprint |
| id |
arxiv_https___arxiv_org_abs_2410_01303 |
| institution | arXiv |
| publishDate | 2024 |
| record_format | arxiv |
| spellingShingle | Decentralized Expectation Propagation for Semi-Blind Channel Estimation in Cell-Free Networks Zhao, Zilu Slock, Dirk Information Theory Signal Processing This paper serves as a correction to the conference version. In this work, we explore uplink communication in cell-free (CF) massive multiple-input multiple-output (MaMIMO) systems, employing semi-blind transmission structures to mitigate pilot contamination. We propose a simplified, decentralized method based on Expectation Propagation (EP) for semi-blind channel estimation. By utilizing orthogonal pilots, we preprocess the received signals to establish a simplified equivalent factorization scheme for the transmission process. Moreover, this study integrates Central Limit Theory (CLT) with EP, eliminating the need to introduce new auxiliary variables in the factorization scheme. We also refine the algorithm by assessing the variable scales involved. Finally, a decentralized approach is proposed to significantly reduce the computational demands on the Central Processing Unit (CPU). |
| title | Decentralized Expectation Propagation for Semi-Blind Channel Estimation in Cell-Free Networks |
| topic | Information Theory Signal Processing |
| url | https://arxiv.org/abs/2410.01303 |