一种支持时延约束的卫星认知网络功率控制算法

针对卫星通信网频谱资源利用率低下的问题，以信道有效容量最大化为优化目标，提出了一种支持时延约束的卫星Underlay认知无线网络功率控制与优化算法。首先根据网络拓扑结构建立了功率干扰模型，通过引入时域信道相关系数，推导了完全与非完全信道环境下基于时延约束的认知用户有效容量优化目标函数，并利用Lagrange方法求解得到不同场景下认知用户的最佳功率调整策略，简化了功率控制优化过程，最后通过实验仿真分析了影响认知用户信道有效容量的因素。结果表明，该算法能够根据业务时延约束条件和信道衰落特性变化动态调整认知用户的最佳发送功率，与等功率分配算法相比认知用户的信道有效容量得到了明显提高。

Power allocation algorithm supporting delay constraints for satellite cognitive radio networks

A power allocation algorithm supporting delay constrains which maximizes the channel effective capacity of secondary users for satellite “Underlay” cognitive radio networks is proposed to improve the spectrum utilization of a satellite communication system. A power interference model is established based on the topology of satellite cognitive radio networks first, and then the object functions of effective capacity are derived both in perfect and imperfect channel state information environments. The Lagrange method is used to obtain the optimized transmitting power of secondary users by introducing the time-domain channel correlation coefficient. Optimized power adjusting strategies under different scenes are discussed while the power allocating and optimizing process is simpli-fied. Factors which affect the effective capacity of secondary users are analyzed by simulation. The results indicate that the proposed power allocation algorithm can adjust the transmitting power of secondary users according to delay constrains with channel fading char-acteristics, and the channel effective capacity of secondary users is improved obviously compared to the traditional equal power alloca-tion policy.