An Efficient Cooperative Spectrum Sensing Method Using Renyi Entropy Weighted Optimal Likelihood Ratio for CRN

Authors

  • Sandip B. Shrote Shri Guru Gobind Singhji Institute of Engineering and Technology, Nanded, India
  • Sadhana D. Poshattiwar Shri Guru Gobind Singhji Institute of Engineering and Technology, Nanded, India

DOI:

https://doi.org/10.26636/jtit.2023.3.1360

Keywords:

cognitive radio, eigen statistics, optimal weight, signal energy, spectrum sensing

Abstract

The main concept behind employing cognitive radio is to enable secondary users (SUs) or unlicensed users to utilize the available spectrum. Spectrum sensing methods detect the existence of primary users (PUs) and have become the main topic of research in the CRN industry and in academia. This paper proposes a new framework based on the Adam gradient descent (Adam GD) algorithm to develop a spectrum sensing mechanism used in CRNs and detecting the availability of free channels. The signal's components are extracted from the received signal and the spectrum is searched for availability which is detected through a fusion center using the proposed algorithm. The proposed Adam GD algorithm attains the maximum detection probability rate and the minimum false alarm probability of 0.71 and 0.39, respectively, for a Rayleigh channel.

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Published

2023-09-01

Issue

No. 3 (2023)

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ARTICLES FROM THIS ISSUE

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Copyright (c) 2023 Journal of Telecommunications and Information Technology

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How to Cite

[1]
S. B. Shrote and S. D. Poshattiwar, “An Efficient Cooperative Spectrum Sensing Method Using Renyi Entropy Weighted Optimal Likelihood Ratio for CRN”, JTIT, vol. 93, no. 3, pp. 41–48, Sep. 2023, doi: 10.26636/jtit.2023.3.1360.