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In order to improve the prediction accuracy of cognitive radio spectrum and providing more reliable spectrum access for the subsequent spectrum detection, the dynamic fuzzy neural network is applied to predict the cognitive radio spectrum, and prove its feasibility. Simulation results show that the algorithm has higher accuracy than the general spectral prediction algorithm.
Predicting the licensed or primary user (PU) channel state future has been widely investigated in the recent literature, this study introduce a new approach for predicting PU channel state based on time series and hidden Markov model (HMM). In this new approach we model the primary user channel state detection sequence, which can be represented by; PU channel “idle” or “occupied” as a time series...
Variational Bayes (VB) is applied in Cognitive Radio (CR) to handle the intractability of Bayes' rule in Hidden Markov Model (HMM) when we evaluate parameters to estimate a primary user's (PU's) states but without any information on a PU. It can also avoid a probable overfitting problem caused by maximum likelihood (ML) algorithm. With the advantage of conjugating to complete-data likelihood in HMM...
Power control is one of the key technologies in cognitive radio network. This article integrates game element into power control algorithm in cognitive radio. On the basis of traditional model, an improved cost function is presented. Combined with game theory, the existence and uniqueness of Nash equilibrium solution of the game model is proved. Simulation results suggest that the convergence of the...
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