Abstract
The Cognitive radio network (CR) is a widespread technology in which the Secondary users are assumed to be of the winning users to acquire the spectrum by reducing the false alarm possibilities and the false detection of the user assumed to be original user in nature is restricted with the usage of Spectrum monitoring agents. The collaborative spectrum sensing (CSS) is an approach that will identify the false intruder in the CR networks, here it is proposed with the Enhanced Q-Learning model with Coalition Game approach (EQLCG) to outline the energy enhancement. Besides an approach on Greedy Bidding is used to allocate the spectrum to the winning secondary user (SU) based on the idle primary user to strengthen the spectrum sensing. The winning secondary user forms a communication establishment with the neighbouring SU to eradicate the miss detection probability based on group level cooperation. The simulation experiment analyses the cluster level security with energy monitoring that has been performed using the analysis of interference by applying the coalition game theory modelling and the information obscured by the attacker is reduced with the usage of enhanced Q-learning, and the results prove that overhead is substantially monitored. The proposed paper enhances the security in physical layer with energy conservation and maintains the spectrum usage for application purpose. The proposed simulation approach reduces the miss detection and false alarm probabilistic approach while compared with Stackelberg and Bayesian game models.
Highlights
The demand in wireless communication has emerged widespread in the spectrum management and spectrum handling market
The wireless communications perform a key role in the modern era for making efficient communication; besides Cognitive radio network (CR) networks have been best known for the spectrum allocation in the modern digital world
The miss detection and false alarm probability is mitigated with the best selection of secondary users (SU), and the coalition game theory approach works on with the collaborative spectrum sensing (CSS) of SU to allocate the spectrum, this mechanism proposes an energy efficient in CR networks and the spectrum access by SU is done with the idle spectrum in primary users (PU) in a secured manner without causing interference between them [1]
Summary
The Cognitive radio network (CR) is a widespread technology in which the Secondary users are engaged in acquiring the idle spectrum from the primary user. The collaborative spectrum sensing (CSS) is an approach that will identify the false intruder in the CR networks, here it is proposed with the Enhanced Q-Learning model with Coalition Game approach (EQLCG) to outline the energy enhancement. Besides an approach on Greedy Bidding is used to allocate the spectrum to the winning secondary user (SU) based on the idle primary user to strengthen the spectrum sensing. The simulation experiment analyses the cluster level security with energy monitoring that has been performed using the analysis of interference by applying the coalition game theory modelling and the information obscured by the attacker is reduced with the usage of enhanced Q-learning, and the results prove that overhead is substantially monitored. The proposed simulation approach reduces the miss detection and false alarm probabilistic approach while compared with Stackelberg and Bayesian game models
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