دورية أكاديمية
Activity Detection for Massive Random Access using Covariance-based Matching Pursuit ...
| العنوان: | Activity Detection for Massive Random Access using Covariance-based Matching Pursuit ... |
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| المؤلفون: | Marata, Leatile, Ollila, Esa, Alves, Hirley |
| بيانات النشر: | arXiv |
| سنة النشر: | 2024 |
| المجموعة: | DataCite Metadata Store (German National Library of Science and Technology) |
| مصطلحات موضوعية: | Signal Processing eess.SP, FOS Electrical engineering, electronic engineering, information engineering |
| الوصف: | The Internet of Things paradigm heavily relies on a network of a massive number of machine-type devices (MTDs) that monitor changes in various phenomena. Consequently, MTDs are randomly activated at different times whenever a change occurs. This essentially results in relatively few MTDs being active simultaneously compared to the entire network, resembling targeted sampling in compressed sensing. Therefore, signal recovery in machine-type communications is addressed through joint user activity detection and channel estimation algorithms built using compressed sensing theory. However, most of these algorithms follow a two-stage procedure in which a channel is first estimated and later mapped to find active users. This approach is inefficient because the estimated channel information is subsequently discarded. To overcome this limitation, we introduce a novel covariance-learning matching pursuit algorithm that bypasses explicit channel estimation. Instead, it focuses on estimating the indices of the active ... : submitted to IEEE IoT journal ... |
| نوع الوثيقة: | article in journal/newspaper report |
| اللغة: | unknown |
| DOI: | 10.48550/arxiv.2405.02741 |
| الإتاحة: | https://doi.org/10.48550/arxiv.2405.02741Test https://arxiv.org/abs/2405.02741Test |
| حقوق: | Creative Commons Attribution 4.0 International ; https://creativecommons.org/licenses/by/4.0/legalcodeTest ; cc-by-4.0 |
| رقم الانضمام: | edsbas.CFD6C0F4 |
| قاعدة البيانات: | BASE |
| DOI: | 10.48550/arxiv.2405.02741 |
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