Reweighted regularised variable step size normalised least mean square-based iterative channel estimation for multicarrier-interleave division multiple access systems
This study focuses on channel estimation scheme in multicarrier-interleave division multiple access (MC-IDMA)-based wireless communications. Specifically, a new adaptive algorithm is derived and proposed for implementation of the channel estimation in the MC-IDMA system. The proposed algorithm is na...
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| Vydané v: | IET signal processing Ročník 10; číslo 8; s. 947 - 954 |
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| Hlavný autor: | |
| Médium: | Journal Article |
| Jazyk: | English |
| Vydavateľské údaje: |
The Institution of Engineering and Technology
01.10.2016
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| Predmet: | |
| ISSN: | 1751-9675, 1751-9683, 1751-9683 |
| On-line prístup: | Získať plný text |
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| Shrnutí: | This study focuses on channel estimation scheme in multicarrier-interleave division multiple access (MC-IDMA)-based wireless communications. Specifically, a new adaptive algorithm is derived and proposed for implementation of the channel estimation in the MC-IDMA system. The proposed algorithm is named reweighted regularised variable step size normalised least mean square (R-RVSSNLMS). The proposed algorithm-based channel estimator exploits inherent sparsity in the orthogonal frequency division multiplexing channels in order to enhance its performance. Computer simulation results that show the comparison of the performance of the R-RVSSNLMS-based channel estimator with that of the channel estimators based on some families of least mean square algorithms are documented in this study. The results show that the performance of the proposed R-RVSSNLMS-based channel estimator is better than that of the other conventional estimators presented in this study. However, the proposed channel estimator exhibits negligible high computational complexity in comparison with other channel estimators considered in this study for the MC-IDMA system. |
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| Bibliografia: | ObjectType-Article-1 SourceType-Scholarly Journals-1 ObjectType-Feature-2 content type line 23 |
| ISSN: | 1751-9675 1751-9683 1751-9683 |
| DOI: | 10.1049/iet-spr.2016.0008 |