A robust cyclic-feature detection against noise uncertainty
The detection performance of cyclic-feature detection is much better than energy detection. However, noise uncertainty will degrade its performance severely. Aiming at this problem, a cyclic-feature detection method resisting to noise uncertainty was proposed. It was proved that the noise cyclic spe...
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| Format: | Article |
| Language: | zho |
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Beijing Xintong Media Co., Ltd
2016-10-01
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| Series: | Dianxin kexue |
| Subjects: | |
| Online Access: | http://www.telecomsci.com/zh/article/doi/10.11959/j.issn.1000-0801.2016211/ |
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| _version_ | 1841529961807085568 |
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| author | Qiang CHEN Ming JIN Jingwen TONG |
| author_facet | Qiang CHEN Ming JIN Jingwen TONG |
| author_sort | Qiang CHEN |
| collection | DOAJ |
| description | The detection performance of cyclic-feature detection is much better than energy detection. However, noise uncertainty will degrade its performance severely. Aiming at this problem, a cyclic-feature detection method resisting to noise uncertainty was proposed. It was proved that the noise cyclic spectrum components at different cycle frequencies were independent and identically distributed in two-dimensional cyclic spectrum. Based on this, the noise distribution at the cycle peak was estimated using all values except the spectrum peak positions of licensed user signal, and decision threshold was obtained without noise power prior knowledge, so as to avoid the influence of noise uncertainties. Simulation results demonstrate that the performance of the proposed method is close to that of cyclic-feature detection method with known noise power. |
| format | Article |
| id | doaj-art-5666d69a55494d53b0b4fffbe4bb25cf |
| institution | Kabale University |
| issn | 1000-0801 |
| language | zho |
| publishDate | 2016-10-01 |
| publisher | Beijing Xintong Media Co., Ltd |
| record_format | Article |
| series | Dianxin kexue |
| spelling | doaj-art-5666d69a55494d53b0b4fffbe4bb25cf2025-01-15T03:14:17ZzhoBeijing Xintong Media Co., LtdDianxin kexue1000-08012016-10-0132717659607034A robust cyclic-feature detection against noise uncertaintyQiang CHENMing JINJingwen TONGThe detection performance of cyclic-feature detection is much better than energy detection. However, noise uncertainty will degrade its performance severely. Aiming at this problem, a cyclic-feature detection method resisting to noise uncertainty was proposed. It was proved that the noise cyclic spectrum components at different cycle frequencies were independent and identically distributed in two-dimensional cyclic spectrum. Based on this, the noise distribution at the cycle peak was estimated using all values except the spectrum peak positions of licensed user signal, and decision threshold was obtained without noise power prior knowledge, so as to avoid the influence of noise uncertainties. Simulation results demonstrate that the performance of the proposed method is close to that of cyclic-feature detection method with known noise power.http://www.telecomsci.com/zh/article/doi/10.11959/j.issn.1000-0801.2016211/spectrum sensingcyclic-feature detectionnoise uncertainty |
| spellingShingle | Qiang CHEN Ming JIN Jingwen TONG A robust cyclic-feature detection against noise uncertainty Dianxin kexue spectrum sensing cyclic-feature detection noise uncertainty |
| title | A robust cyclic-feature detection against noise uncertainty |
| title_full | A robust cyclic-feature detection against noise uncertainty |
| title_fullStr | A robust cyclic-feature detection against noise uncertainty |
| title_full_unstemmed | A robust cyclic-feature detection against noise uncertainty |
| title_short | A robust cyclic-feature detection against noise uncertainty |
| title_sort | robust cyclic feature detection against noise uncertainty |
| topic | spectrum sensing cyclic-feature detection noise uncertainty |
| url | http://www.telecomsci.com/zh/article/doi/10.11959/j.issn.1000-0801.2016211/ |
| work_keys_str_mv | AT qiangchen arobustcyclicfeaturedetectionagainstnoiseuncertainty AT mingjin arobustcyclicfeaturedetectionagainstnoiseuncertainty AT jingwentong arobustcyclicfeaturedetectionagainstnoiseuncertainty AT qiangchen robustcyclicfeaturedetectionagainstnoiseuncertainty AT mingjin robustcyclicfeaturedetectionagainstnoiseuncertainty AT jingwentong robustcyclicfeaturedetectionagainstnoiseuncertainty |