| Autor: |
Dayou Hou, Tansheng Qian, Jia Zhao, Peijun Li, Xiao Zhuolei |
| Rok vydání: |
2021 |
| Předmět: |
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| Zdroj: |
2021 IEEE 5th Information Technology,Networking,Electronic and Automation Control Conference (ITNEC). |
| DOI: |
10.1109/itnec52019.2021.9586840 |
| Popis: |
In the cognitive radio (CR) technology that has developed vigorously in recent years, the existing spectrum sensing algorithms have low detection performance in low signal-to-noise ratio(SNR). The optimal correlation window size and optimal spectral correlation ratio under different SNR signals are studied, and an adaptive correlation window energy detection algorithm is proposed in this paper. The algorithm uses rough resolution detection for spectrum sensing, and then uses adaptive spectral correlation ratio and correlation window size parameters for fine resolution detection, which can solve the problem of poor detection performance when detecting low SNR signals. The simulation results show that under the condition of ensuring the detection performance, the SNR is reduced by about 3dB compared to the existing algorithm. |
| Databáze: |
OpenAIRE |
| Externí odkaz: |
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