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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.

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Summary The proposed cooperative spectrum sensing (CSS) network is equipped with multiple antennas and an improved energy detector (IED) scheme at each cognitive radio (CR). Each CR in the network receives the information about the primary user (PU) in the form of binary decisions at multiple antennas. Diversity technique called selection combining (SC) scheme is used at multiple antennas to select the maximum value of sensing information present at multiple antennas. Finally, sensing information will be passed to the fusion center (FC) through reporting channel, and the final decision about PU is made at FC using fusion rules. Initially, we have derived the novel missed detection probability expressions for AWGN channel, Rayleigh, and Rician fading environments. Later, the closed form of optimized expressions for proposed CSS network parameters are derived to achieve an optimal performance. The closed form of optimized expressions such as number of CR users (Nopt), normalize threshold value (λn,opt), and an arbitrary power of the received signal (popt) are derived under various fading environments. The performance is evaluated using complementary receiver operating characteristics (CROC) and total error rate curves. The MATLAB‐based simulations are evaluated with the strong support of theoretical expressions. Finally, various simulation parameters such as sensing channel SNR, the error rate in reporting channel, threshold value, and number of antennas at each CR are considered in the simulation to show the effect on the performance of proposed CSS network.

In this paper, performance analysis for optimization of cooperative spectrum sensing (CSS) network in Nakagami-m and Weibull fading environments and comparison between them are presented. First, we derive the novel analytic expressions for probabilities of missed detection and false alarm for CSS network in both fading channels, assuming improved energy detector (IED) and selection combining (SC) diversity at each cognitive radios (CRs). Next, we optimize the network parameters such as number of CRs, energy detector arbitrary parameter, and normalized detection threshold at CR to obtain the optimal performance of CSS network. The impacts of several network parameters like: multiple antennas at each CR, number of CRs in CSS network, Nakagami and Weibull fading parameters, and sensing channel SNR on the performance of CSS network are investigated. The performance comparison between conventional and improved energy detectors has also been highlighted in this paper.