Wideband spectrum sensing based on advanced sub-Nyquist sampling structure
Abstract As the bandwidth increases, the high-speed sampling rate becomes the bottleneck for the development of wideband spectrum sensing. Wideband spectrum sensing with sub-Nyquist sampling attracts more attention and modulated wideband converter (MWC) is an attractive sub-Nyquist sampling system....
| Main Authors: | , , , |
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| Format: | Article |
| Language: | English |
| Published: |
SpringerOpen
2022-05-01
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| Series: | EURASIP Journal on Advances in Signal Processing |
| Subjects: | |
| Online Access: | https://doi.org/10.1186/s13634-022-00874-3 |
| _version_ | 1818210242027061248 |
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| author | Xue Wang Qian Chen Min Jia Xuemai Gu |
| author_facet | Xue Wang Qian Chen Min Jia Xuemai Gu |
| author_sort | Xue Wang |
| collection | DOAJ |
| description | Abstract As the bandwidth increases, the high-speed sampling rate becomes the bottleneck for the development of wideband spectrum sensing. Wideband spectrum sensing with sub-Nyquist sampling attracts more attention and modulated wideband converter (MWC) is an attractive sub-Nyquist sampling system. For the purpose of breaking the system structure limit, an advanced sub-Nyquist sampling framework is proposed to simplify the MWC system structure, adopting the single sampling channel structure with a frequency shifting module to acquire the sub-Nyquist sampling values. In order to recover the signal support information, the sensing matrix must be built according to the only one mixing function. Most existing support recovery methods rely on some prior knowledge about the spectrum sparsity, which is difficult to acquire in practical electromagnetic environment. To address this problem, we propose an adaptive residual energy detection algorithm (ARED), which bypasses the need for the above-mentioned prior knowledge. Simulation results show that, without requiring the aforementioned prior knowledge, the ARED algorithm based on the advanced sub-Nyquist sampling framework has the similar performance as MWC and even higher than MWC in some cases using only one sampling channel. |
| first_indexed | 2024-12-12T05:13:29Z |
| format | Article |
| id | doaj.art-1e570dcae2464c2db23dd3a63587c868 |
| institution | Directory Open Access Journal |
| issn | 1687-6180 |
| language | English |
| last_indexed | 2024-12-12T05:13:29Z |
| publishDate | 2022-05-01 |
| publisher | SpringerOpen |
| record_format | Article |
| series | EURASIP Journal on Advances in Signal Processing |
| spelling | doaj.art-1e570dcae2464c2db23dd3a63587c8682022-12-22T00:36:49ZengSpringerOpenEURASIP Journal on Advances in Signal Processing1687-61802022-05-012022112010.1186/s13634-022-00874-3Wideband spectrum sensing based on advanced sub-Nyquist sampling structureXue Wang0Qian Chen1Min Jia2Xuemai Gu3School of Measurement and Communication Engineering, Harbin University of Science and TechnologySchool of Measurement and Communication Engineering, Harbin University of Science and TechnologyHarbin Institute of TechnologyHarbin Institute of TechnologyAbstract As the bandwidth increases, the high-speed sampling rate becomes the bottleneck for the development of wideband spectrum sensing. Wideband spectrum sensing with sub-Nyquist sampling attracts more attention and modulated wideband converter (MWC) is an attractive sub-Nyquist sampling system. For the purpose of breaking the system structure limit, an advanced sub-Nyquist sampling framework is proposed to simplify the MWC system structure, adopting the single sampling channel structure with a frequency shifting module to acquire the sub-Nyquist sampling values. In order to recover the signal support information, the sensing matrix must be built according to the only one mixing function. Most existing support recovery methods rely on some prior knowledge about the spectrum sparsity, which is difficult to acquire in practical electromagnetic environment. To address this problem, we propose an adaptive residual energy detection algorithm (ARED), which bypasses the need for the above-mentioned prior knowledge. Simulation results show that, without requiring the aforementioned prior knowledge, the ARED algorithm based on the advanced sub-Nyquist sampling framework has the similar performance as MWC and even higher than MWC in some cases using only one sampling channel.https://doi.org/10.1186/s13634-022-00874-3Wideband spectrum sensingModulated wideband converterSub-Nyquist samplingCorrect support recoveryBlind spectrum sensing |
| spellingShingle | Xue Wang Qian Chen Min Jia Xuemai Gu Wideband spectrum sensing based on advanced sub-Nyquist sampling structure EURASIP Journal on Advances in Signal Processing Wideband spectrum sensing Modulated wideband converter Sub-Nyquist sampling Correct support recovery Blind spectrum sensing |
| title | Wideband spectrum sensing based on advanced sub-Nyquist sampling structure |
| title_full | Wideband spectrum sensing based on advanced sub-Nyquist sampling structure |
| title_fullStr | Wideband spectrum sensing based on advanced sub-Nyquist sampling structure |
| title_full_unstemmed | Wideband spectrum sensing based on advanced sub-Nyquist sampling structure |
| title_short | Wideband spectrum sensing based on advanced sub-Nyquist sampling structure |
| title_sort | wideband spectrum sensing based on advanced sub nyquist sampling structure |
| topic | Wideband spectrum sensing Modulated wideband converter Sub-Nyquist sampling Correct support recovery Blind spectrum sensing |
| url | https://doi.org/10.1186/s13634-022-00874-3 |
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