Eigenvalue Based Active User Enumeration for Grant-Free Access Under Carrier Frequency Offsets
Fuente:
arXiv
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| Natura: | Preprint |
| Pubblicazione: |
2024
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| _version_ | 1866929581304315904 |
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| author | Hara, Takanori |
| author_facet | Hara, Takanori |
| contents | This paper investigates a grant-free non-orthogonal multiple access (GF-NOMA) system in the presence of carrier frequency offsets. We propose two schemes for enumerating active users in such a GF-NOMA system, which is equivalent to estimating the sparsity level. Both schemes utilize a short common pilot and the eigenvalues of the sample covariance matrix of the received signal. The two schemes differ in their treatment of noise variance: one exploits known variance information, while the other is designed to function without this knowledge. Simulation results demonstrate the effectiveness of the proposed schemes in terms of the normalized root-mean-squared error. |
| format | Preprint |
| id |
arxiv_https___arxiv_org_abs_2408_05988 |
| institution | arXiv |
| publishDate | 2024 |
| record_format | arxiv |
| spellingShingle | Eigenvalue Based Active User Enumeration for Grant-Free Access Under Carrier Frequency Offsets Hara, Takanori Information Theory Signal Processing This paper investigates a grant-free non-orthogonal multiple access (GF-NOMA) system in the presence of carrier frequency offsets. We propose two schemes for enumerating active users in such a GF-NOMA system, which is equivalent to estimating the sparsity level. Both schemes utilize a short common pilot and the eigenvalues of the sample covariance matrix of the received signal. The two schemes differ in their treatment of noise variance: one exploits known variance information, while the other is designed to function without this knowledge. Simulation results demonstrate the effectiveness of the proposed schemes in terms of the normalized root-mean-squared error. |
| title | Eigenvalue Based Active User Enumeration for Grant-Free Access Under Carrier Frequency Offsets |
| topic | Information Theory Signal Processing |
| url | https://arxiv.org/abs/2408.05988 |