Dynamic digital channelized sub-band detection algorithm based on eigenvalue distribution

被引：0
|
作者：
Li X. [1 ]
Wan H. [1 ]
Shi M. [1 ]
Wang X. [1 ]
机构：
[1] School of Telecommunications Engineering, Xidian University, Xi'an
来源：
Xi Tong Gong Cheng Yu Dian Zi Ji Shu/Systems Engineering and Electronics | 2024年 / 46卷 / 05期
关键词：
dynamic digital channelized receive; eigenvalue detection; random matrix; sub-band signal detection;
D O I：
10.12305/j.issn.1001-506X.2024.05.33
中图分类号：
学科分类号：
摘要：
The dynamic digital channelized receiving structure detects all sub-bands to determine if there is a signal. The detection results provide a basis for processing the integrated filter bank, so it plays a vital role in the receiving structure. Since the poor performance of the traditional detection algorithm under low signal-to-noise ratio(SNR),a novel detection algorithm based on the ratio of the difference between the maximum and minimum eigen values to the average eigenvalue is proposed according to the random matrix theory. The detection threshold of the algorithm is derived by using the limit distribution law of the average eigenvalue and the minimum eigenvalue. Then, the algorithm is optimized according to the eigenvalue information obtained from all sub-band data. Finally, the performance of the proposed algorithm under different factors is analyzed in the dynamic digital channelized receiving structure, which shows that the algorithm can overcome the effects of the low SNR and perform better in the sub-band detection process. © 2024 Chinese Institute of Electronics. All rights reserved.
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页码：1801 / 1809
页数：8
相关论文
共 30 条
  • [1] WANG L, WANG K D, ZHAO R Q, Et al., An efficient real-time digital channelization method based on frequency-domain windowing, Proc. of the 4th International Conference on Information Communication and Signal Processing, pp. 533-537, (2021)
  • [2] GHELFI P, SCOTTI F, ONORI D, Et al., Photonics for ultrawide-band RF spectral analysis in electronic warfare applications, IEEE Journal of Selected Topics in Quantum Electronics, 25, 4, (2019)
  • [3] CHENG X, WANG X., Development and conception of construction of complex electromagnetic environment and efficiency eva-luation, Radar & ECM, 41, 4, pp. 11-14, (2021)
  • [4] LIAO H S., A study of key technologies of signal processing for communication reconnaissance, (2011)
  • [5] ZHANG J J, LI J., RF channelization technology, (2022)
  • [6] HU J P., Research on dynamic channelization technique for broadband wireless signal reconnaissance, (2016)
  • [7] ARJOUNE Y, MRABET Z E, GHAZI H E, Et al., Spectrum sensing: enhanced energy detection technique based on noise measurement, Proc. of the IEEE 8th Annual Computing and Communication Workshop and Conference, pp. 828-834, (2018)
  • [8] SHERBIN M K, SINDHU V., Cyclostationary feature detection for spectrum sensing in cognitive radio network, Proc. of the International Conference on Intelligent Computing and Control Systems, pp. 1250-1254, (2019)
  • [9] AWIN F, ABDELRAHEEM E, TEPE K., Blind spectrum sensing approaches for interweaved cognitive radio system: a tutorial and short course, IEEE Communications Surveys Tutorials, 21, 1, pp. 238-259, (2019)
  • [10] YUCEK T, ARSLAN H., A survey of spectrum sensing algorithms for cognitive radio applications, IEEE Communications Surveys Tutorials, 11, 1, pp. 116-130, (2009)
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