Efficient swarm intelligent algorithm for power control game in cognitive radio networks

Cognitive radio networks (CRNs) are applied to solve spectrum scarcity. In this study, the authors propose an efficient power control game to improve its performance based on outage probability of primary user in a spectrum-underlay CRN. The interference threshold deduced from outage probability and normalised signal to interference plus noise ratio are used to develop a novel non-linear pricing function, which is a key element of obtaining Pareto improvement in non-cooperative power control game. In addition, an efficient swarm intelligent algorithm originated from eco-group activities is designed in detail to accelerate the convergence speed and improve the energy-efficiency. Theoretical analysis and simulation results are presented to prove the effectiveness and superiority of the proposed power control game.