认知无线网络的Rubinstein博弈频谱共享方法研究

Rubinstein Game Spectrum Sharing Algorithm for Cognitive Radio

针对传统的功率控制算法限制认知用户的发射功率而影响其服务质量(Quality of Service, QoS)的问题,提出了一种基于功率控制的多人Rubinstein博弈频谱分配算法。该算法通过牛顿迭代公式降低认知用户的发射功率并依据各个用户间的干扰得到相应的链路质量;将经济学中的贴现因子与用户的链路质量建立映射关系;通过链路质量调整认知用户子博弈顺序使得网络总传输速率达到一个相对稳定的状态。仿真结果表明:多个认知用户在同一信道下共享频谱时,采用多人Rubinstein博弈算法对系统的总传输速率有明显的提升,使系统处于稳定且高速的传输状态并节省了一半以上的频谱分配时间。

In order to solve the problem that the traditional power control algorithm limits the transmit power of secondary users and affects its QoS( Quality of Service), a multi-person Rubinstein game spectrum allocation algorithm based on power control is proposed. The proposed algorithm reduces the transmit power of cognitive users by Neton’s iterative formula and obtains the corresponding link quality according to the interference between users. The mapping between the discount factor of the game model and the link quality of the user is used to adjust the cognitive based on the link quality. The user sub-game sequence makes the total transmission rate of the network reach a relatively stable state. Simulations show that when the multiple secondary users share the spectrum under the same channel, the multi-person Rubinstein game algorithm significantly improves the total transmission rate of the system, and makes the system in a stable and high-speed transmission state,and also saves more than half of the spectrum allocation time.