Soft Interference Cancellation for Random Coding in Massive Gaussian Multiple-Access
In 2017, Polyanskiy showed that the trade-off between power and bandwidth efficiency for massive Gaussian random access is governed by two fundamentally different regimes: low power and high power. For both regimes, tight performance bounds were found by Zadik et al., in 2019. This work utilizes rec...
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| Format: | Article |
| Language: | English |
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MDPI AG
2021-04-01
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| Series: | Entropy |
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| Online Access: | https://www.mdpi.com/1099-4300/23/5/539 |
| _version_ | 1797536022051946496 |
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| author | Ralf R. Müller |
| author_facet | Ralf R. Müller |
| author_sort | Ralf R. Müller |
| collection | DOAJ |
| description | In 2017, Polyanskiy showed that the trade-off between power and bandwidth efficiency for massive Gaussian random access is governed by two fundamentally different regimes: low power and high power. For both regimes, tight performance bounds were found by Zadik et al., in 2019. This work utilizes recent results on the exact block error probability of Gaussian random codes in additive white Gaussian noise to propose practical methods based on iterative soft decoding to closely approach these bounds. In the low power regime, this work finds that orthogonal random codes can be applied directly. In the high power regime, a more sophisticated effort is needed. This work shows that power-profile optimization by means of linear programming, as pioneered by Caire et al. in 2001, is a promising strategy to apply. The proposed combination of orthogonal random coding and iterative soft decoding even outperforms the existence bounds of Zadik et al. in the low power regime and is very close to the non-existence bounds for message lengths around 100 and above. Finally, the approach of power optimization by linear programming proposed for the high power regime is found to benefit from power imbalances due to fading which makes it even more attractive for typical mobile radio channels. |
| first_indexed | 2024-03-10T11:53:41Z |
| format | Article |
| id | doaj.art-062595a26a5f4148970486326175851d |
| institution | Directory Open Access Journal |
| issn | 1099-4300 |
| language | English |
| last_indexed | 2024-03-10T11:53:41Z |
| publishDate | 2021-04-01 |
| publisher | MDPI AG |
| record_format | Article |
| series | Entropy |
| spelling | doaj.art-062595a26a5f4148970486326175851d2023-11-21T17:29:19ZengMDPI AGEntropy1099-43002021-04-0123553910.3390/e23050539Soft Interference Cancellation for Random Coding in Massive Gaussian Multiple-AccessRalf R. Müller0Institute for Digital Communications, Friedrich-Alexander Universität Erlangen-Nürnberg, 91058 Erlangen, GermanyIn 2017, Polyanskiy showed that the trade-off between power and bandwidth efficiency for massive Gaussian random access is governed by two fundamentally different regimes: low power and high power. For both regimes, tight performance bounds were found by Zadik et al., in 2019. This work utilizes recent results on the exact block error probability of Gaussian random codes in additive white Gaussian noise to propose practical methods based on iterative soft decoding to closely approach these bounds. In the low power regime, this work finds that orthogonal random codes can be applied directly. In the high power regime, a more sophisticated effort is needed. This work shows that power-profile optimization by means of linear programming, as pioneered by Caire et al. in 2001, is a promising strategy to apply. The proposed combination of orthogonal random coding and iterative soft decoding even outperforms the existence bounds of Zadik et al. in the low power regime and is very close to the non-existence bounds for message lengths around 100 and above. Finally, the approach of power optimization by linear programming proposed for the high power regime is found to benefit from power imbalances due to fading which makes it even more attractive for typical mobile radio channels.https://www.mdpi.com/1099-4300/23/5/539multiple-accesssuccessive cancellationiterative decodingfinite blocklengthblock error probabilityrandom coding |
| spellingShingle | Ralf R. Müller Soft Interference Cancellation for Random Coding in Massive Gaussian Multiple-Access Entropy multiple-access successive cancellation iterative decoding finite blocklength block error probability random coding |
| title | Soft Interference Cancellation for Random Coding in Massive Gaussian Multiple-Access |
| title_full | Soft Interference Cancellation for Random Coding in Massive Gaussian Multiple-Access |
| title_fullStr | Soft Interference Cancellation for Random Coding in Massive Gaussian Multiple-Access |
| title_full_unstemmed | Soft Interference Cancellation for Random Coding in Massive Gaussian Multiple-Access |
| title_short | Soft Interference Cancellation for Random Coding in Massive Gaussian Multiple-Access |
| title_sort | soft interference cancellation for random coding in massive gaussian multiple access |
| topic | multiple-access successive cancellation iterative decoding finite blocklength block error probability random coding |
| url | https://www.mdpi.com/1099-4300/23/5/539 |
| work_keys_str_mv | AT ralfrmuller softinterferencecancellationforrandomcodinginmassivegaussianmultipleaccess |