Precise Analysis of Covariance Identifiability for Activity Detection in Grant-Free Random Access
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arXiv
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| Autori principali: | , , , |
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| Natura: | Preprint |
| Pubblicazione: |
2024
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| _version_ | 1866910469439094784 |
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| author | Luo, Shengsong Ma, Junjie Xu, Chongbin Wang, Xin |
| author_facet | Luo, Shengsong Ma, Junjie Xu, Chongbin Wang, Xin |
| contents | We consider the identifiability issue of maximum likelihood based activity detection in massive MIMO based grant-free random access. A prior work by Chen et al. indicates that the identifiability undergoes a phase transition for commonly-used random signatures. In this paper, we provide an analytical characterization of the boundary of the phase transition curve. Our theoretical results agree well with the numerical experiments. |
| format | Preprint |
| id |
arxiv_https___arxiv_org_abs_2406_01138 |
| institution | arXiv |
| publishDate | 2024 |
| record_format | arxiv |
| spellingShingle | Precise Analysis of Covariance Identifiability for Activity Detection in Grant-Free Random Access Luo, Shengsong Ma, Junjie Xu, Chongbin Wang, Xin Signal Processing Information Theory We consider the identifiability issue of maximum likelihood based activity detection in massive MIMO based grant-free random access. A prior work by Chen et al. indicates that the identifiability undergoes a phase transition for commonly-used random signatures. In this paper, we provide an analytical characterization of the boundary of the phase transition curve. Our theoretical results agree well with the numerical experiments. |
| title | Precise Analysis of Covariance Identifiability for Activity Detection in Grant-Free Random Access |
| topic | Signal Processing Information Theory |
| url | https://arxiv.org/abs/2406.01138 |