On applying firefly algorithm for cognitive radio networks

The misusing of the radio spectrum, which is a rare therefore an expensive resource, has given birth to the paradigm of cognitive radio (CR). This latter aims at sensing a communication slot in the spectrum, and adapting the transmission parameters to the dynamic variations of wireless channel within the slot. Adapting these parameters to ensure the users quality of service (QoS) could be challenging in a multicarrier context, particularly with the increase of the number of subcarriers. Due to its simplicity and its proven speed of convergence and offered performance, the recently proposed firefly algorithm (FFA) is extended and adapted to tune the transmission parameters in multicarrier cognitive systems. It is shown that the proposed algorithm outperforms the usually adopted particle swarm optimization (PSO) technique in terms of convergence speed and quality of solution.