Affirmed Crowd Sensor Selection based Cooperative Spectrum Sensing

The Cooperative Spectrum sensing model is gaining importance among the cognitive radio network sharing groups. While the crowd-sensing model (technically the cooperative spectrum sensing) model has positive developments, one of the critical challenges plaguing the model is the false or manipulated crowd sensor data, which results in implications for the secondary user’s network. Considering the efficacy of the spectrum sensing by crowd-sensing model, it is vital to address the issues of falsifications and manipulations, by focusing on the conditions of more accurate determination models. Concerning this, a method of avoiding falsified crowd sensors from the process of crowd sensors centric cooperative spectrum sensing has portrayed in this article. The proposal is a protocol that selects affirmed crowd sensor under diversified factors of the decision credibility about spectrum availability. An experimental study is a simulation approach that evincing the competency of the proposal compared to the other contemporary models available in recent literature

SMOOTHED DOPPLER PROFILE IN MST RADAR DATA-THE MODIFIED CEPSTRUM APPROACH

ABSTRACT The concept of cepstrum thresholding (CT) is applied to estimate smoothed nonparametric spectrum. The CT method is applied to Mesosphere, Stratosphere and Troposphere (MST) radar data for spectral cleaning. This method is not superior as compared with the conventional Periodogram method. So, to enhance the spectral visibility in Doppler Profile (DP), the CT technique is modified. The modified cepstrum (MC) is developed and implemented, to validate, it is applied to radar data. An adaptive spectral moment's estimation technique is utilized for analyzing the Doppler spectra of the MST radar signals. From the Doppler frequency components, the radial velocities in the direction of the zonal (U), meridional (V), and vertical (W) are estimated. In turn, the wind velocity is estimated from U and V components. The proposed method works well even at higher altitudes and results are compared with the traditional methods such as Peak detection technique and the matched filter. Keywords: MST radar, cepstrum thresholding, doppler shift, matched filter, spectral peak detection, spectral moments. INTRODUCTION National Atmospheric Research Laboratory (NARL) at Gadanki (13.47°N, 79.18°E), India has been operating 53 MHz atmospheric Mesosphere, Stratosphere and Troposphere (MST) radar for studying structure and dynamics of lower, middle and upper atmosphere The method adopted for identifying the signal and computing the three low-order spectral moments is central to the problem of extracting information from the Doppler spectrum of the MST radar signal. The conventional method of analyzing the MST radar spectral data is based on identifying the most prominent peak of the Doppler spectrum for each range gate and computing the three low order spectral moments and signal-to noise ratio (SNR) using the expressions given by The method of adaptive moments estimation was presented to perform consistently well at distinct SNR conditions of atmospheric signal