Skip to main content

Advertisement

SpringerLink
Log in

Gannet optimization algorithm enabled framework for spectrum sensing in OFDM based CR network

  • Original Paper
  • Published:
Wireless Networks Aims and scope Submit manuscript

Abstract

The emergence of the fifth generation (5G) mobile communication network highly promoted the enhancement of broadband wireless communication. One of the famous physical transmission technologies in regard to wireless communication is orthogonal frequency division multiplexing (OFDM) and the requirements of cognitive radio (CR) met by this OFDM. Spectrum sensing (SS) is a key enabling function in CR to improve utilization spectrum and eases the spectrum resources. Among more other modulation methods, OFDM is broadly utilized in various next generation and current wireless communications systems. This paper enables SS in OFDM based CR using proposed gannet optimization algorithm (GOA). Firstly, simulation is undergone and signal is received from OFDM based CR network. Here, generation of test statistics, such as signal energy, Eigen statistics, matched filter and wavelets done to ensure efficient CR communication without interference. Furthermore, fusion center undergoes fusion process, at which weights determined by proposed GOA and decision is finally processed. GOA diving patterns used for exploring the optimal region with in the search space and then enable exploitation phase to ensure better solution to compute weight vector. This research is evaluated by various performance metrics, such as mean square error and also bit error rate with values of 0.007 and 0.023, correspondingly for SNR of 20 dB with Nakagami fading channel.

This is a preview of subscription content, log in via an institution to check access.

Access this article

Log in via an institution

Price excludes VAT (USA)
Tax calculation will be finalised during checkout.

Instant access to the full article PDF.

Institutional subscriptions

Fig. 1
Fig. 2
Fig. 3
Fig. 4
Fig. 5
Fig. 6

Similar content being viewed by others

References

  1. Pan, G., Li, J., & Lin, F. (2020). A cognitive radio spectrum sensing method for an OFDM signal based on deep learning and cycle spectrum. International Journal of Digital Multimedia Broadcasting, 2020, 1–10.

    Article  Google Scholar 

  2. Tian, J., Cheng, P., Chen, Z., Li, M., Hu, H., Li, Y., & Vucetic, B. (2019). A machine learning-enabled spectrum sensing method for OFDM systems. IEEE Transactions on Vehicular Technology, 68(11), 11374–11378.

    Article  Google Scholar 

  3. Ahmad, H. B. (2019). Ensemble classifier based spectrum sensing in cognitive radio networks. Wireless Communications and Mobile Computing. https://doi.org/10.1155/2019/9250562

    Article  Google Scholar 

  4. Soni, B., Patel, D. K., & López-Benítez, M. (2020). Long short-term memory based spectrum sensing scheme for cognitive radio using primary activity statistics. IEEE Access, 8, 97437–97451.

    Article  Google Scholar 

  5. El Bahi, F. Z., Ghennioui, H., & Zouak, M. (2019). Spectrum sensing technique of OFDM signal under noise uncertainty based on mean ambiguity function for cognitive radio. Physical Communication, 33, 142–150.

    Article  Google Scholar 

  6. Meena, M., & Rajendran, V. (2022). Spectrum sensing and resource allocation for proficient transmission in cognitive radio with 5G. IETE Journal of Research, 68(3), 1772–1788.

    Article  Google Scholar 

  7. Karthikeyan, C. S., & Suganthi, M. (2017). Optimized spectrum sensing algorithm for cognitive radio. Wireless Personal Communications, 94, 2533–2547.

    Article  Google Scholar 

  8. Clancy, T. C., III. (2006). Dynamic spectrum access in cognitive radio networks. University of Maryland.

    Google Scholar 

  9. Ali, A., & Hamouda, W. (2016). Advances on spectrum sensing for cognitive radio networks: Theory and applications. IEEE Communications Surveys & Tutorials, 19(2), 1277–1304.

    Article  Google Scholar 

  10. Cadena Muñoz, E., Pedraza Martínez, L. F., & Hernandez, C. A. (2020). Rényi entropy-based spectrum sensing in mobile cognitive radio networks using software defined radio. Entropy, 22(6), 626.

    Article  Google Scholar 

  11. Pan, J. S., Zhang, L. G., Wang, R. B., Snášel, V., & Chu, S. C. (2022). Gannet optimization algorithm: A new metaheuristic algorithm for solving engineering optimization problems. Mathematics and Computers in Simulation, 202, 343–373.

    Article  MathSciNet  MATH  Google Scholar 

  12. Mahmoud, H. A., & Arslan, H. (2008). Sidelobe suppression in OFDM-based spectrum sharing systems using adaptive symbol transition. IEEE Communications Letters, 12(2), 133–135.

    Article  Google Scholar 

  13. Patel, A., Ram, H., Jagannatham, A. K., & Varshney, P. K. (2017). Robust cooperative spectrum sensing for MIMO cognitive radio networks under CSI uncertainty. IEEE Transactions on Signal Processing, 66(1), 18–33.

    Article  MathSciNet  MATH  Google Scholar 

  14. Chowdary, K. U., & Rao, B. P. (2020). Hybrid mixture model based on a hybrid optimization for spectrum sensing to improve the performance of MIMO–OFDM systems. International Journal of Pattern Recognition and Artificial Intelligence, 34(07), 2058008.

    Article  Google Scholar 

  15. Arjoune, Y., & Kaabouch, N. (2019). A comprehensive survey on spectrum sensing in cognitive radio networks: Recent advances, new challenges, and future research directions. Sensors, 19(1), 126.

    Article  Google Scholar 

  16. Zhao, Y., Wu, Y., Wang, J., Zhong, X., & Mei, L. (2014). Wavelet transform for spectrum sensing in Cognitive Radio networks. In 2014 International Conference on Audio, Language and Image Processing, IEEE pp. 565–569.

  17. Raghunatharao, D., Prasad, T. J., & Giri Prasad, M. N. (2020). Optimal pilot-based channel estimation in cognitive radio. Wireless Personal Communications, 114, 2801–2819.

    Article  Google Scholar 

  18. Rao, D. R., Prasad, T. J., & Prasad, M. G. (2022). Deep Learning based Cooperative Spectrum Sensing with Crowd Sensors using Data Cleansing Algorithm. In 2022 International Conference on Edge Computing and Applications (ICECAA), IEEE pp. 1276–1281.

  19. Pan, J. S., Sun, B., Chu, S. C., Zhu, M., & Shieh, C. S. (2023). A parallel compact gannet optimization algorithm for solving engineering optimization problems. Mathematics, 11(2), 439.

    Article  MathSciNet  Google Scholar 

  20. Mansouri, N., & Sharafaddini, A. M. (2022). An efficient gannet optimization algorithm for feature selection based on sensitivity and specificity. Journal of Algorithms and Computation, 54(2), 49–69.

    Google Scholar 

  21. Samala, S., Chandraprakash, T., & Rao, P. R. (2020). Design and Analysis of Channel Estimation of MIMO-OFDM using Whale Swarm Optimization. In IOP Conference Series: Materials Science and Engineerin, IOP Publishing, Vol. 981, No. 3, p. 032042.

  22. Gupta, V., Beniwal, N. S., Singh, K. K., & Sharan, S. N. (2020). Cooperative spectrum sensing optimization using meta-heuristic algorithms. Wireless Personal Communications, 113, 1755–1773.

    Article  Google Scholar 

  23. Rao, D. R., Prasad, T. J., & Prasad, M. N. G. (2022). Affirmed crowd sensor selection based cooperative spectrum sensing. International Journal on Recent and Innovation Trends in Computing and Communication, 10(10), 65–77.

    Article  Google Scholar 

Download references

Author information

Authors and Affiliations

  1. Jawaharlal Nehru Technological University Anantapur, Ananthapuramu, Andhrapradesh, India

    D. Raghunatha Rao

  2. RGM College of Engineering and Technology (Autonomous), Jawaharlal Nehru Technological University Anantapur, Ananthapuramu, Andhrapradesh, India

    T. Jayachandra Prasad

  3. ECE Department, JNTUA College of Engineering Ananthapuramu, Constituent College of Jawaharlal Nehru Technological University, Anantapur, Ananthapuramu, Andhrapradesh, India

    M. N. Giri Prasad

Authors
  1. D. Raghunatha Rao
    View author publications

    You can also search for this author in PubMed Google Scholar

  2. T. Jayachandra Prasad
    View author publications

    You can also search for this author in PubMed Google Scholar

  3. M. N. Giri Prasad
    View author publications

    You can also search for this author in PubMed Google Scholar

Corresponding author

Correspondence to D. Raghunatha Rao.

Additional information

Publisher's Note

Springer Nature remains neutral with regard to jurisdictional claims in published maps and institutional affiliations.

Rights and permissions

Springer Nature or its licensor (e.g. a society or other partner) holds exclusive rights to this article under a publishing agreement with the author(s) or other rightsholder(s); author self-archiving of the accepted manuscript version of this article is solely governed by the terms of such publishing agreement and applicable law.

Reprints and permissions

About this article

Check for updates. Verify currency and authenticity via CrossMark

Cite this article

Rao, D.R., Prasad, T.J. & Prasad, M.N.G. Gannet optimization algorithm enabled framework for spectrum sensing in OFDM based CR network. Wireless Netw 29, 2863–2872 (2023). https://doi.org/10.1007/s11276-023-03351-3

Download citation

  • Accepted:

  • Published:

  • Issue Date:

  • DOI: https://doi.org/10.1007/s11276-023-03351-3

Keywords

Search

Navigation