The cognitive radio technology (CR) is an emerging technology used to solve the problem of spectrum scarcity. The CR has the ability to detect, to learn about the environment and intelligently adapt its parameters in the most appropriate way to provide the optimal service to users. In this document, we introduce a new algorithm called Dragonfly algorithm. This algorithm is used to adapt the transmission parameters and to optimize the quality of service (QoS). The dragonfly algorithm (DA) is a new meta-heuristic optimization algorithm based on the simulation of the swarming behavior of dragonfly individuals. The DA was developed on the basis of hunting and migration strategies of dragonflies. The hunting technique is known as a static swarm (feeding), in which all members of a swarm can fly in small groups over a small area to discover food sources. The migration strategy of dragonflies is called dynamic swarm (migratory). In this phase, the dragonflies are willing to soar in larger groups, and as a result, the swarm can migrate. The proposed algorithm was used to optimize QoS performance in terms of minimum power consumption, bit error rate (BER), maximum throughput, minimum interference and maximum spectral efficiency. The results obtained are compared with two other algorithms known as Genetic Algorithm (GA) and Simulated Annealing (SA).
Key words: Cognitive radio, Metaheuristic, QoS, Dragonfly Algorithm, GA, SA.
You can reach the full manuscript (in French) in the ResearchGate repository.