A Double Threshold Energy Estimation Approach to Optimize Spectrum Sensing in Cognitive Radio Network


  • H Venkatesh Kumar Nagarjuna College of Engineering & Technology
  • M. N. Giriprasad Dept of ECE, JNTU College of Engineering,Anatapur, Andhra Pradesh, India




Cognitive Radio, Primary user, Secondary user, Energy detection, Double threshold Algorithm.


In cognitive radio network, detection of Spectrum is a new innovation to analyses exploitation of underutilized range to overcome the issue of spectrum shortage. One of the vital Spectrum detecting strategies for cognitive radio is energy detection. In this paper, energy detection method is proposed for cooperative and non-cooperative cognitive radio. In this work we introduce new scheme for the spectrum sensing which is based on the improved double threshold method. Results demonstrate that detection probability increases whenever signal to noise ratio (SNR) and false alarm probability increases. Here, we discuss about advancement of threshold value along with energy identification for enhancing the outcome of spectrum sensing. Setting threshold value to reduce spectrum sensing fault, shrinks collision probability with primary user, enhance the value of available spectrum, hence enhancing aggregate spectrum efficiency. In any case, when deciding threshold level, spectrum sensing limitation should additionally be fulfilled since it promises least protection level of Primary User(PU) and utilization level of empty range. To minimize spectrum detecting lapse for given range detecting imperative, we determine an ideal adaptable threshold level by using the spectrum detecting lapse capacity and imperative which is given by imbalance condition. Simulation results demonstrate that the proposed plan gives better spectrum sensing results.

Author Biography

H Venkatesh Kumar, Nagarjuna College of Engineering & Technology



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How to Cite

Kumar, H. V., & Giriprasad, M. N. (2015). A Double Threshold Energy Estimation Approach to Optimize Spectrum Sensing in Cognitive Radio Network. Discoveries in Agriculture and Food Sciences, 3(4), 46. https://doi.org/10.14738/tnc.34.1406