Full metadata record
DC Field | Value | Language |
---|---|---|
dc.contributor.author | 남해운 | - |
dc.date.accessioned | 2024-01-02T04:31:19Z | - |
dc.date.available | 2024-01-02T04:31:19Z | - |
dc.date.issued | 2020-12 | - |
dc.identifier.citation | 2020 International Conference on Information and Communication Technology Convergence (ICTC), article no. 9289566, Page. 424.0-426.0 | - |
dc.identifier.issn | 2162-1233 | - |
dc.identifier.uri | https://ieeexplore.ieee.org/document/9289566?arnumber=9289566&SID=EBSCO:edseee | en_US |
dc.identifier.uri | https://repository.hanyang.ac.kr/handle/20.500.11754/188008 | - |
dc.description.abstract | We consider a compressive wideband spectrum sensing for low-power IoT devices as secondary users(SUs). We present the proposed scheme for cost-effective compressive sensing for wideband spectrum sensing with a large number of distributed SUs. SUs have a single RF-chain for the compressive sensing and the measurement samples obtained at each SU are sent to the fusion center. The fusion center performs the proposed algorithm which estimates the minimum measurement samples for the reconstruction process. Among the total measurement samples by SUs, the rest of the samples except for the minimum number of samples are used for cooperative spectrum sensing. The original signal vector with the minimum measurement samples is reconstructed and cooperative gain is obtained by using the remainder of measurement samples effectively. We compare the performance of the proposed algorithm with the conventional compressive sensing scheme and the result shows that the proposed algorithm has better performance specially at the high sparsity order region. | - |
dc.description.sponsorship | This work was supported by the research fund of Signal Intelligence Research Center supervised by the Defense Acquisition Program Administration and the Agency for Defense Development of Korea. | - |
dc.language | en | - |
dc.publisher | IEEE | - |
dc.subject | Compressive sensing | - |
dc.subject | Wideband spectrum sensing | - |
dc.subject | Sparsity order estimation | - |
dc.subject | Signal recovery | - |
dc.title | Wideband spectrum sensing using low-power IoT device | - |
dc.type | Article | - |
dc.identifier.doi | 10.1109/ICTC49870.2020.9289566 | - |
dc.relation.page | 424.0-426.0 | - |
dc.relation.journal | 2020 International Conference on Information and Communication Technology Convergence (ICTC) | - |
dc.contributor.googleauthor | Kim, Hyeongyun | - |
dc.contributor.googleauthor | Ahn, Junil | - |
dc.contributor.googleauthor | Nam, Haewoon | - |
dc.sector.campus | E | - |
dc.sector.daehak | 공학대학 | - |
dc.sector.department | 전자공학부 | - |
dc.identifier.pid | hnam | - |
dc.identifier.article | 9289566 | - |
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