Signal Detection for Ultra-Massive MIMO: An Information Geometry Approach
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arXiv
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| Main Authors: | , , , , |
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| Format: | Preprint |
| Published: |
2024
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| _version_ | 1866909060958257152 |
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| author | Yang, Jiyuan Chen, Yan Gao, Xiqi Slock, Dirk Xia, Xiang-Gen |
| author_facet | Yang, Jiyuan Chen, Yan Gao, Xiqi Slock, Dirk Xia, Xiang-Gen |
| contents | In this paper, we propose an information geometry approach (IGA) for signal detection (SD) in ultra-massive multiple-input multiple-output (MIMO) systems. We formulate the signal detection as obtaining the marginals of the a posteriori probability distribution of the transmitted symbol vector. Then, a maximization of the a posteriori marginals (MPM) for signal detection can be performed. With the information geometry theory, we calculate the approximations of the a posteriori marginals. It is formulated as an iterative m-projection process between submanifolds with different constraints. We then apply the central-limit-theorem (CLT) to simplify the calculation of the m-projection since the direct calculation of the m-projection is of exponential-complexity. With the CLT, we obtain an approximate solution of the m-projection, which is asymptotically accurate. Simulation results demonstrate that the proposed IGA-SD emerges as a promising and efficient method to implement the signal detector in ultra-massive MIMO systems. |
| format | Preprint |
| id |
arxiv_https___arxiv_org_abs_2401_02043 |
| institution | arXiv |
| publishDate | 2024 |
| record_format | arxiv |
| spellingShingle | Signal Detection for Ultra-Massive MIMO: An Information Geometry Approach Yang, Jiyuan Chen, Yan Gao, Xiqi Slock, Dirk Xia, Xiang-Gen Information Theory In this paper, we propose an information geometry approach (IGA) for signal detection (SD) in ultra-massive multiple-input multiple-output (MIMO) systems. We formulate the signal detection as obtaining the marginals of the a posteriori probability distribution of the transmitted symbol vector. Then, a maximization of the a posteriori marginals (MPM) for signal detection can be performed. With the information geometry theory, we calculate the approximations of the a posteriori marginals. It is formulated as an iterative m-projection process between submanifolds with different constraints. We then apply the central-limit-theorem (CLT) to simplify the calculation of the m-projection since the direct calculation of the m-projection is of exponential-complexity. With the CLT, we obtain an approximate solution of the m-projection, which is asymptotically accurate. Simulation results demonstrate that the proposed IGA-SD emerges as a promising and efficient method to implement the signal detector in ultra-massive MIMO systems. |
| title | Signal Detection for Ultra-Massive MIMO: An Information Geometry Approach |
| topic | Information Theory |
| url | https://arxiv.org/abs/2401.02043 |