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Design and Implementation of Electromagnetic Spectrum Sensing Load Based on Software Radio

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Abstract

This study proposed the design and implementation method of an electromagnetic spectrum sensing load based on software radio. In view of small volume and low energy of micro-nano satellites, the load adopted the hardware structure based on software radio architecture to receive broadband radio signal. The sampling signal was then preprocessed by the window function so as to suppress frequency spectrum leakage. The designed load is featured by reasonable design and favorable software performances, which can achieve the electromagnetic spectrum sensing for the radio signal within the frequency range of 70–6000 MHz. Meanwhile, the load possesses the parameter re-settings and on-orbit reconstruction functions so as to ensure various types of special spectrum sensing tasks.

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REFERENCES

  1. Wu, Q.H. and Ren, H., New paradigm of electromagnetic spectrum space: spectrum situation, J. Nanjing Univ. Aeronaut. Astronautics, 2016, vol. 48, no. 5, pp. 625–633.

    Google Scholar 

  2. Di, B.Y., Song, L., Li, Yo., and Poor, H.V., Ultra-dense LEO: integration of satellite access networks into 5G and beyond, IEEE Wireless Commun., 2019, vol. 26, no. 2, pp. 62-69. https://doi.org/10.1109/MWC.2019.1800301

    Article  Google Scholar 

  3. Yuan J., Bao X.Y., Sun X., et al., Analysis and suggestions on orbit and spectrum resources trend for Mega LEO constellations, Space Debris Res., 2021, vol. 21, pp. 48–57.

    Google Scholar 

  4. Li G., Wang W. and Wu Q.H., Cognitive intelligent spectrum management and control for low-earth-orbit satellite systems, ZTE Technol. J., 2021, vol. 27, no. 5, p. 5.

    Google Scholar 

  5. Lagunas, E., Sharma, Sh.K., Maleki, S., Chatzinotas, S., and Ottersten, B., Resource allocation for cognitive satellite communications with incumbent terrestrial networks, IEEE Trans. Cognit. Commun. Networking, 2015, vol. 1, no. 3, pp. 305–317. https://doi.org/10.1109/TCCN.2015.2503286

    Article  Google Scholar 

  6. Agrawal, S.K., Samant, A., and Yadav, S.K., Spectrum sensing in cognitive radio networks and metacognition for dynamic spectrum sharing between radar and communication system: A review, Phys. Commun., 2022, vol. 52, p. 101673. https://doi.org/10.1016/j.phycom.2022.101673

    Article  Google Scholar 

  7. Bharati, S., and Podder, P., Adaptive PAPR reduction scheme for OFDM using SLM with the fusion of proposed clipping and filtering technique in order to diminish PAPR and signal distortion, Wireless Personal Commun., 2020, vol. 113, no. 4, pp. 2271–2288. https://doi.org/10.1007/s11277-020-07323-0

    Article  Google Scholar 

  8. Podder, P., Bharati, S., Robel, M., Alam, R., Raihan-Al-Masud, M., and Rahman, M.A., Uplink and downlink spectral efficiency estimation for multi antenna MIMO user, Innovations in Bio-Inspired Computing and Applications. IBICA 2019, Abraham, A., Panda, M., Pradhan, S., Garcia-Hernandez, L., Ma, K., Eds., Advances in Intelligent Systems and Computing, vol. 1180, Cham: Springer, 2019, pp. 285–294. https://doi.org/10.1007/978-3-030-49339-4_29

  9. Goswami, P.K., and Goswami, G., A corner truncated fractal slot ultrawide spectrum sensing antenna for wireless cognitive radio sensor network, Int. J. Commun. Syst., 2021, vol. 34, no. 4, p. e4710. https://doi.org/10.1002/dac.4710

    Article  Google Scholar 

  10. Yakkati, R.R., Yakkati, R.R., Tripathy, R.K., and Cenkeramaddi, L.R., Radio frequency spectrum sensing by automatic modulation classification in cognitive radio system using multiscale deep CNN, IEEE Sens. J., 2022, vol. 22, no. 1, pp. 926–938. https://doi.org/10.1109/JSEN.2021.3128395

    Article  Google Scholar 

  11. Cui, C.M., Qin, G.Q. and Wu, Q.Y., Implementation of double-threshold spectrum sensing based on USRP2920 and differential energy detection, Commun. Technol., 2022, vol. 55, no. 1, p. 7.

    Google Scholar 

  12. Zhuang, Z.Y. and Ban, T., Design of an ADS-B signal receiver based on software defined radio, Telecommun. Eng., 2021, vol. 61, no. 7, p. 6.

    Google Scholar 

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Authors and Affiliations

  1. Unmanned Systems Research Center, National Innovation Institute of Defense Technology, Academy of Military Science, 100071, Beijing, China

    Jiang-Yi Qin, Kai Wang, Xian-Bin Li, Fei Zhang & Ming Tang

Authors
  1. Jiang-Yi Qin
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  2. Kai Wang
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  3. Xian-Bin Li
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  4. Fei Zhang
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  5. Ming Tang
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Correspondence to Kai Wang.

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Jiang-Yi Qin, Wang, K., Li, XB. et al. Design and Implementation of Electromagnetic Spectrum Sensing Load Based on Software Radio. Aut. Control Comp. Sci. 57, 317–325 (2023). https://doi.org/10.3103/S0146411623030082

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  • DOI: https://doi.org/10.3103/S0146411623030082

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