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<p>Cognitive radio (CR) technology is a new approach to the enhancement of the utilization of the electromagnetic spectrum. The problem of spectrum scarcity mainly stems from inefficient and irregular allocation of frequency bands. This problem is solved by CR systems by allowing better use of the available spectrum by other technologies. In this work, an adaptive energy detection method for the efficient operation of spectrum sensing (SS) in cognitive radio systems is proposed. The proposed approach engages a dynamic threshold energy detection scheme where enhanced energy of the primary signals is detected for the side lobe signals and a generalized energy detector. Depending on the activity of primary users (PU’s), the scheme determines decision thresholds based on the uncertainty in the noise value. The given adaptive mechanism enhances the detection probability (Pd) and reduces the false alarm probability (Pfa) to produce effective spectrum sensing. The results show that the proposed scheme attains the highest Pd (0.85) and the lowest Pfa (0.71), thus surpassing existing SS techniques. </p>

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An adaptive energy detection scheme using estimation of noise uncertainty for cognitive radio

  • 期刊论文

  • 发表日期：

    2025年5月24日

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  • Anita Venugopal,
  • Ashu Gautam,
  • S. Suma,
  • P. Anbarasu,
  • Shailesh V. Kulkarni,
  • Girisha Ramhari Bombale

摘要

Cognitive radio (CR) technology is a new approach to the enhancement of the utilization of the electromagnetic spectrum. The problem of spectrum scarcity mainly stems from inefficient and irregular allocation of frequency bands. This problem is solved by CR systems by allowing better use of the available spectrum by other technologies. In this work, an adaptive energy detection method for the efficient operation of spectrum sensing (SS) in cognitive radio systems is proposed. The proposed approach engages a dynamic threshold energy detection scheme where enhanced energy of the primary signals is detected for the side lobe signals and a generalized energy detector. Depending on the activity of primary users (PU’s), the scheme determines decision thresholds based on the uncertainty in the noise value. The given adaptive mechanism enhances the detection probability (Pd) and reduces the false alarm probability (Pfa) to produce effective spectrum sensing. The results show that the proposed scheme attains the highest Pd (0.85) and the lowest Pfa (0.71), thus surpassing existing SS techniques.