Optimized Power Control Algorithm Based on Differential Game Theory in Cognitive Radio Networks
Shasha Zhao, Lidan Qin, Xiaoyu Zhou, Dengyin Zhang · 2022 41st Chinese Control Conference (CCC) · 2022
An optimized power control algorithm based on differential game theory is proposed. According to the dynamic nature of network, differential game theory is applied to investigate the power control of the cognitive radio network in the proposed algorithm. The time continuity of the network is considered. The power control strategy selections of the secondary users (cognitive users) are modeled as a differential game model. Both the current income and the long-term significance of the strategy of the users are taken into consideration. Based on the proposed model, the open-loop Nash equilibrium solution is obtained. The simulation results show that the proposed algorithm can effectively control the transmit power of the secondary user to reach a steady state, maximize the revenue of the users and improve the performance of the system.