Cognitive Radio is a modern domain that presents the best solution to address the spectrum scarcity problems. Several cognitive radios standards undergo high Peak to Average Power Ratio (PAPR) that might deform transmitted signals. This work presents a model for spectrum sensing based on optimization enabled PAPR exploiting hybrid Gaussian Mixture Model (GMM). The energy, Eigen statistics, and PAPR minimization block are developed uses the hybrid technique to predict the spectrum availability. To technique network with PAPR, the recently modeled optimization method called Improved Grey Wolf Optimization (GWO)-Dragonfly algorithm (DA) is proposed. The GMM is facilitates exploiting energy, Eigen statistics, besides through PAPR. The GMM is altered using an optimization technique, called Improved GWO-DA optimization algorithm. The PAPR is minimized by optimally altering the parameters by developed Improved GWO-DA. The channel availability is calculated by presenting Eigen statistics, energy, and PAPR as input. The efficiency of developed Improved GWO-DA is shown with maximum detection probability, minimum PAPR, and minimum Bit Error Rate (BER) correspondingly.
Buy article PDF