A bio-inspired fast swarming algorithm for dynamic radio access

The goal of this paper is to propose a bio-inspired algorithm for decentralized dynamic access in cognitive radio systems. We study an improved social foraging swarm model that lets every node allocate its resources (power/bits) in the frequency regions where the interference is minimum while avoiding collisions with other nodes. The proposed approach adapts its behavior with respect to the interference power perceived by every node, thus increasing the speed of convergence and reducing the reaction time needed by the algorithm to react to dynamic changes in the environment. The presence of random disturbances such as link failures, quantization noise and estimation errors is taken into account in the convergence analysis. Numerical results illustrate the performance of the proposed algorithm.