Optimization of Ant Colony for Next Generation Wireless Cognitive Networks

In this work, spectrum handoff process carried out by secondary users according to priority classes in cognitive radio network is proposed. Network structure design of analytical and simulation models is simulated with RIVERBED software. Moreover, deciding on the most suitable spectrum handoff process is determined by using artificial intelligence techniques. Using multi parameter decision making processes is the objective of our work. Optimization of the spectrum handoff number with the help of ant colony algorithm is the main goal of our work. By studying similar aspects of cognitive radio networks and ant colony algorithms, the number of handoff is reduced within the most appropriate scenario.

Optimization of Ant Colony for Next Generation Wireless Cognitive Networks

In this work, the spectrum handoff process carried out by secondary users according to priority classes in cognitive radio networks is proposed. The network structure design of analytical and simulation models is simulated with the RIVERBED software. Moreover, deciding on the most suitable spectrum handoff process is determined by using artificial intelligence techniques. Using multi-parameter decision-making processes is the objective of our work. Optimization of the spectrum handoff number with the help of an ant colony algorithm is the main goal of our work. By studying similar aspects of cognitive radio networks and ant colony algorithms, the number of handoffs is reduced within the most appropriate scenario.

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