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Intelligent and Reliable Cognitive 5G Networks Using Whale Optimization Techniques

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Advances in Swarm Intelligence

Part of the book series: Studies in Computational Intelligence ((SCI,volume 1054))

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Abstract

In forthcoming networks for high definition radio large bandwidth, low latency and several emergence applications like e-health, Industrial IOT, smart transportation etc. will be conquered by 5G networks. Therefore, more capacity and consequently efficient spectrum sensing will be an awful prerequisite for huge demand for certain applications. In this field of research, attempts have been made to develop new techniques to improve the reliability and channel capacity in 5G Networks using WOA, LDPC and Cognitive Concepts. The results have been presented in the form of various plots and graphs.

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References

  1. Haddad, M., Hayar, A.M.: Mobile Communications Group, Institute Eurecom, Merqueen Debbah ,SUPELEC,Plateau de Moulon, 3 rue Joliot-Curie Spectral efficiency of Cognitive Radio systems. IEEE (2007)

    Google Scholar 

  2. Zhang, S., Xu, X., Wu, Y., Lu, L.: Huawei Technologies, Co. Ltd., Shanghai, Chin 5G: Towards Energy-Efficient, Low-Latency and High-Reliable Communications Networks. ©2014 IEEE (2014)

    Google Scholar 

  3. Cayamcela, M.E.M., Lim, W.: Artificial Intelligence in 5G Technology: A Survey. IEEE (2018)

    Google Scholar 

  4. Pirinen, P.: Centre for wireless communications. In: A Brief Overview of 5G Research Activities. University of Oulu, Finland. ICST (2014)

    Google Scholar 

  5. Niu, K., Chen, K., Lin, J., Zhang, Q.T.: Polar codes: primary concepts and practical decoding algorithms. IEEE Commun. Mag. (2014)

    Google Scholar 

  6. Yao, M., Sohul, M., Marojevic, V., Reed, J.H.: Artificial intelligence-defined 5G radio access networks. IEEE Commun. Mag. (2019)

    Google Scholar 

  7. Navarro-Ortiz, J., Romero-Diaz, P., Sendra, S., Ameigeiras, P., Ramos-Munoz, J.J., Lopez-Soler, J.M.: A survey on 5G usage scenarios and traffic models. IEEE Commun. Surv. Tutor.

    Google Scholar 

  8. Strutz, T.: 2010–2014, 2016. Low-Density Parity-Check codes—An introduction, TStrutz Tutorial on LDPC codes (2016)

    Google Scholar 

  9. Pham, Q.-V., Mirjalili, S., Kumar, N., Alazab, M., Hwang, W.-J.: Whale Optimization Algorithm With Applications to Resource Allocation in Wireless Networks. IEEE (2020)

    Google Scholar 

  10. Arora, K., Singh, J., Randhawa, Y.S.: A Survey on Channel Coding Techniques for 5G Wireless Networks. Springer Science Business Media, LLC, Part of Springer Nature (2019)

    Google Scholar 

  11. Bae, J.H., Abotabl, A., Lin, H.-P., Song, K.-B., Lee, J.: An overview of channel coding for 5G NR cellular communications. SIP 8(e17), 1 of 14 © The Authors (2019). https://creativecommons.org/licenses/by/4.0/

  12. Richardson, T., Kudekar, S.: Design of low-density, parity check codes for 5G new radio. IEEE Commun. Mag. (2018)

    Google Scholar 

  13. Andrews, J.G., et al.: What will 5G be? IEEE J. Sel. Areas Commun. 32(6), 1065–1082 (2014)

    Article  Google Scholar 

  14. Shukurillaevich, U.B., Sattorivich, R.O., Amrillojonovich, R.U.: 5G Technology Evolution. IEEE (2019)

    Google Scholar 

  15. Mirjalili, S.: A School of Information and Communication Technology. Griffith University, Nathan Campus, Brisbane, QLD 4111, Australia, Andrew Lewis Griffith College, Mt Gravatt, Brisbane, QLD 4122, Australia The Whale Optimization Algorithm 2016 Elsevier (2016)

    Google Scholar 

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Correspondence to Javaid Ahmad Sheikh .

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Bashir, J., Sheikh, J.A., Bhat, Z.A. (2023). Intelligent and Reliable Cognitive 5G Networks Using Whale Optimization Techniques. In: Biswas, A., Kalayci, C.B., Mirjalili, S. (eds) Advances in Swarm Intelligence. Studies in Computational Intelligence, vol 1054. Springer, Cham. https://doi.org/10.1007/978-3-031-09835-2_10

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