Distributed Compressed Spectrum Sensing via Cooperative Support Fusion
Spectrum sensing in wideband cognitive radio (CR) networks faces several significant practical challenges, such as extremely high sampling rates required for wideband processing, impact of frequency-selective wireless fading and shadowing, and limitation in power and computing resources of single co...
| Main Authors: | , , , |
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| Format: | Article |
| Language: | English |
| Published: |
Hindawi - SAGE Publishing
2013-12-01
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| Series: | International Journal of Distributed Sensor Networks |
| Online Access: | https://doi.org/10.1155/2013/862320 |
| _version_ | 1797765156313235456 |
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| author | Zha Song Huang Jijun Liu Peiguo He Jianguo |
| author_facet | Zha Song Huang Jijun Liu Peiguo He Jianguo |
| author_sort | Zha Song |
| collection | DOAJ |
| description | Spectrum sensing in wideband cognitive radio (CR) networks faces several significant practical challenges, such as extremely high sampling rates required for wideband processing, impact of frequency-selective wireless fading and shadowing, and limitation in power and computing resources of single cognitive radio. In this paper, a distributed compressed spectrum sensing scheme is proposed to overcome these challenges. To alleviate the sampling bottleneck, compressed sensing mechanism is used at each CR by utilizing the inherent sparsity of the monitored wideband spectrum. Specifically, partially known support (PKS) of the sparse spectrum is incorporated into local reconstruction procedure, which can further reduce the required sampling rate to achieve a given recovery quality or improve the quality given the same sampling rate. To mitigate the impact of fading and shadowing, multiple CRs exploit spatial diversity by exchanging local support information among them. The fused support information is used to guide local reconstruction at individual CRs. In consideration of limited power per CR, local support information percolates over the network via only one-hop local information exchange. Simulation results testify the effectiveness of the proposed scheme by comparing with several existing schemes in terms of detection performance, communication load, and computational complexity. Moreover, the impact of system parameters is also investigated through simulations. |
| first_indexed | 2024-03-12T20:07:03Z |
| format | Article |
| id | doaj.art-b60db3af36cd40d0bde023b1dbe63997 |
| institution | Directory Open Access Journal |
| issn | 1550-1477 |
| language | English |
| last_indexed | 2024-03-12T20:07:03Z |
| publishDate | 2013-12-01 |
| publisher | Hindawi - SAGE Publishing |
| record_format | Article |
| series | International Journal of Distributed Sensor Networks |
| spelling | doaj.art-b60db3af36cd40d0bde023b1dbe639972023-08-02T02:03:30ZengHindawi - SAGE PublishingInternational Journal of Distributed Sensor Networks1550-14772013-12-01910.1155/2013/862320862320Distributed Compressed Spectrum Sensing via Cooperative Support FusionZha SongHuang JijunLiu PeiguoHe JianguoSpectrum sensing in wideband cognitive radio (CR) networks faces several significant practical challenges, such as extremely high sampling rates required for wideband processing, impact of frequency-selective wireless fading and shadowing, and limitation in power and computing resources of single cognitive radio. In this paper, a distributed compressed spectrum sensing scheme is proposed to overcome these challenges. To alleviate the sampling bottleneck, compressed sensing mechanism is used at each CR by utilizing the inherent sparsity of the monitored wideband spectrum. Specifically, partially known support (PKS) of the sparse spectrum is incorporated into local reconstruction procedure, which can further reduce the required sampling rate to achieve a given recovery quality or improve the quality given the same sampling rate. To mitigate the impact of fading and shadowing, multiple CRs exploit spatial diversity by exchanging local support information among them. The fused support information is used to guide local reconstruction at individual CRs. In consideration of limited power per CR, local support information percolates over the network via only one-hop local information exchange. Simulation results testify the effectiveness of the proposed scheme by comparing with several existing schemes in terms of detection performance, communication load, and computational complexity. Moreover, the impact of system parameters is also investigated through simulations.https://doi.org/10.1155/2013/862320 |
| spellingShingle | Zha Song Huang Jijun Liu Peiguo He Jianguo Distributed Compressed Spectrum Sensing via Cooperative Support Fusion International Journal of Distributed Sensor Networks |
| title | Distributed Compressed Spectrum Sensing via Cooperative Support Fusion |
| title_full | Distributed Compressed Spectrum Sensing via Cooperative Support Fusion |
| title_fullStr | Distributed Compressed Spectrum Sensing via Cooperative Support Fusion |
| title_full_unstemmed | Distributed Compressed Spectrum Sensing via Cooperative Support Fusion |
| title_short | Distributed Compressed Spectrum Sensing via Cooperative Support Fusion |
| title_sort | distributed compressed spectrum sensing via cooperative support fusion |
| url | https://doi.org/10.1155/2013/862320 |
| work_keys_str_mv | AT zhasong distributedcompressedspectrumsensingviacooperativesupportfusion AT huangjijun distributedcompressedspectrumsensingviacooperativesupportfusion AT liupeiguo distributedcompressedspectrumsensingviacooperativesupportfusion AT hejianguo distributedcompressedspectrumsensingviacooperativesupportfusion |