Spectrum handoff reduction in cognitive radio networks using evolutionary algorithms

Handoff reduction is considered one of the most exciting challenges in the study of cognitive radio networks. Spectrum handoff occurs between channels when a licensed user needs to access a channel which is currently occupied by an unlicensed user. Once the entry of the authorized user has been detected, the secondary user must move to an idle channel. This process continues until the unlicensed user finishes his transmission. This paper addresses the problem of spectrum mobility in a known radio electric environment, guiding secondary users through routes created with bio-inspired algorithms. The authors formulate a spectrum allocation scheme for multiple secondary users using two bio-inspired algorithms. The simulation results indicate that the Max feeding optimization algorithm proposed offers robustness and low complexity, which makes it a solution that is more in line with the spectrum allocation problem in cognitive radio networks.