Performance of Fading Channels on Energy Detection Based Spectrum Sensing

Abstract

Spectrum sensing is the main feature of cognitive radio technology. Spectrum sensing gives an idea of detecting the presence of the primary users in a licensed spectrum. In this paper we compare the theoretical results of detection probability of different fading environments like Rayleigh, Rician, Nakagami-m, Weibull fading channels with the simulation results using energy detection based spectrum sensing. The numerical results are plotted as f P Vs d P for different SNR values, fading parameters. It is observed that Weibull fading channel performance is better than other fading channels by using energy detection in spectrum sensing. A MATLAB simulation test bench has been implemented to know the performance of energy detection in different fading channel environment.

Implementation of Spectrum Sensing for Maximum Throughput & Better Probability of Detection using Energy Detector

“…Three distinctive recognition strategies have been Acquainted in Range detecting with realize the opportunity groups: Energy detection, Matched filter detection and Cyclostationary detection. Out of these three, Energy Detection is used most widely due to the complexity that present in remaining two strategies [5]. Assume that the received signal is as follows:…”

“…When w and x are modelled as zero-mean Gaussian random variables normally distributed with variances = N 0 W and the metric follows a chi-squared distribution with 2N degrees of freedom. Where N 0 represents single sided noise power spectral density and W represents single sided single bandwidth [5].…”

“…In the same way throughput can be increased by implementing spectrum sensing by using energy detector [5]. Spectrum sensing detects unused spectrum and use that vacant spectrum band by the secondary user without harmful interference to the primary user.…”

Performance of Energy Detector for Cognitive Radio System over AWGN and Rayleigh Channel

“…After convert receive signal to digital we assume it have N samples data denoted by y i where i=1…..N and the test statistic will be (8) And the distribution will convert to normal distribution will follow as (9) The metrics of performance will change to, (10) (11) In [12], over fading statistics, as Rayleigh fading channel the signal amplitude follows a Rayleigh distribution, the γ follows an exponential law which is the probability density function(pdf) given by: (12) Where is mean value of γ, or = E(γ) with E(.) denotes the mathematical expectation.…”

Performance of Fading Channels on Asynchronous OFDM Based Cognitive Radio Networks

“…In [12],we compare the theoretical results of detection probability of different fading environments like Rayleigh, Rician, Nakagami-m, Weibull fading channels with the simulation results using energy detection based spectrum sensing.…”