Optimal Number of Cognitive Users in K-out-of-M Rule

In this letter, we obtain a generalized expression for the optimal number of cognitive users (CUs), M, for the K-out-of-M rule that minimizes the Bayes risk at the fusion center (FC) over noisy control channels. We show that many existing and new results for optimal M are special cases of the proposed solution. Numerical results are presented using energy detector. However, the expressions for optimal M obtained in this letter are applicable to any detector used in cooperative spectrum sensing

Joint Optimization of both m and K for the m-out-of-K Rule for Cooperative Spectrum Sensing

In this paper, we present closed form expressions that jointly optimizes the fusion rule (m) and the number of secondary users (K) for the m-out-of-K rule by minimizing the Bayes risk at the fusion center (FC) in the presence of erroneous reporting channels and then show that various existing and new results are special cases of the proposed solution. The results are applicable to any detector used in cooperative spectrum sensing (CSS). Numerical results are presented using energy detector (ED) which shows that CSS obtained using joint optimized values of m and K results in significant performance improvement

Performance Analysis of Improved Energy Detector With Hardware Impairments for Accurate Spectrum Sensing

The impact of transceiver hardware impairments on the accuracy of spectrum sensing cannot be ignored in low-cost and high data rate cognitive radio systems. Nevertheless, ideal hardware for spectrum sensing is widely assumed in the technical literature. This paper presents a novel method for evaluating the improved energy detector (IED) statistics using alpha-mu distribution over additive white Gaussian noise (AWGN) and Nakagami-m fading channel by considering transceiver hardware imperfections. Moreover, the performance of the IED over AWGN channel is highlighted by the area under the receiver operating curve. Furthermore, the average probability of detection is evaluated for both fading and non-fading environments. An asymptotic analysis studies detection probability over fading channels at a low average signal-to-noiseratio region. Moreover, p-order law combining and p-order law selecting diversity techniques are proposed to increase the performance of the detector. Our simulation results demonstrate that the diversity techniques significantly improve the detector performance