CAJ | 학술논문

研究了分布式无线网络中，没有任何信息交换、也没有环境变化先验知识情况下的动态信道接入算法。运用图型博弈模型对用户的实际拓扑进行建模分析，证明了此博弈模型存在纯策略纳什均衡并且此纳什均衡是全局最优解。同时，采用multi-Q学习求解模型的纯策略纳什均衡解。仿真实验验证了multi-Q学习能获得较高的系统容量以及在图型博弈模型中用户的效用主要由节点的度决定，而与用户数量无直接关系。
연구료분포식무선망락중，몰유임하신식교환、야몰유배경변화선험지식정황하적동태신도접입산법。운용도형박혁모형대용호적실제탁복진행건모분석，증명료차박혁모형존재순책략납십균형병차차납십균형시전국최우해。동시，채용multi-Q학습구해모형적순책략납십균형해。방진실험험증료multi-Q학습능획득교고적계통용량이급재도형박혁모형중용호적효용주요유절점적도결정，이여용호수량무직접관계。
For the problem of dynamic channel selection in unknown distributed environment without a priori knowledge and information exchange, multi-Q learning was proposed. The dynamic channel selection problem was formulated the existence of pure strategy Nash equilibrium in graphical game was proved. At the same time, the pure strategy Nash equi-librium was proved to be global optimal solution. Simulation results show that multi-Q learning achieves high system capacity and utility of users in the graphical game are determined mainly by the degree of the node without direct relationship to the number of users.