Original citationHorgan, D.; Murphy C. C. (2013) Abstract-Previous research has identified several exact methods for the evaluation of the probability of detection for energy detectors operating on Nakagami-m faded channels. However, these methods rely on discrete summations of complicated functions, and so can take a prohibitively long time to evaluate. In this paper, three approximations for the probability of detection in Nakagami-m faded channels, having distinct regions of applicability, are derived. All have closed forms, and enable the fast and accurate computation of key performance metrics.
The method by which individual decisions are combined in cooperative \ud
cognitive radio networks is crucial to minimising the overall \ud
probabilities of false alarm and missed detection. In this paper, \ud
general expressions for these probabilities are derived for a double \ud
threshold energy detector-based network, and an analytical solution for \ud
the optimal value of voting rule is found so that the overall \ud
probability of error is minimised. Simulation results show that there \ud
are significant advantages to the use of double threshold energy \ud
detector-based networks as opposed to their single threshold-based \ud
counterparts; additional simulations verify that the analytical solution\ud
is optimal
Recent studies in cooperative energy detection have focused on the optimization of the threshold value and fusion center voting rule in an effort to minimize the sensing error probability. However, such studies operate under the assumption that the signal to noise ratio is equal at every node, which is rarely the case in practice.In this paper, generalized formulas for the optimal threshold value and optimal fusion center voting rule are derived for hard decision energy detector-based spectrum sensing networks where the signal to noise ratio is distinct at each node. It is shown that the implementation of this solution requires more data to be transmitted than the optimal soft decision scheme, which is known to have superior performance.
In this paper, the performance of energy detector-based spectrum sensor networks is examined under the constraints of the IEEE 802.22 draft specification. Additive white Gaussian noise (AWGN) channels are first considered, and a closed form solution for sample complexity is derived for networks of any size. Rayleigh, Nakagami and Rice fading channel models are also examined, with numerical results demonstrating the effect of these models on the required sample complexity for varying numbers of cooperating nodes.Based on these results, the relationship between the sample complexity for AWGN, Rayleigh and Nakagami channels is examined. Through data fitting, an approximate model is derived, allowing the sample complexity for Rayleigh and Nakagami channels to be computed easily. The model is shown to be accurate across a range of practical values.
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