按需认知导频信道的动态干扰最小化路由博弈
Dynamic Interference Minimization Routing Game for On-Demand Cognitive Pilot Channel
摘要：
在本文中，我们介绍了一种分布式的动态路由算法，为次用户（SU），以最大限度地减少他们对主用户（PU）的干扰，在多跳认知无线电（CR）网络。我们使用具有松弛因子的中轴作为参考路径，其取决于PU的状态。沿着轴，我们构建了一个层次结构的多个源到达认知导频信道（CPC）基站。我们使用一个时间和空间的动态非合作博弈模型之间的相互作用，以及从PU的网络的多跳结构的SU的影响。提出了一种多阶段虚拟游戏学习算法，用于多跳CR网络中的分布式路由。利用逆向归纳法得到了封闭形式的动态博弈的混合（行为）纳什均衡策略集。该算法以最优的分布式方式使SU节点到CPC基站路由路径上的总体干扰和平均分组延迟最小化
英文摘要：
In this paper, we introduce a distributed dynamic routing algorithm for secondary users (SUs) to minimize their interference with the primary users (PUs) in multi-hop cognitive radio (CR) networks. We use the medial axis with a relaxation factor as a reference path which is contingent on the states of the PUs. Along the axis, we construct a hierarchical structure for multiple sources to reach cognitive pilot channel (CPC) base stations. We use a temporal and spatial dynamic non-cooperative game to model the interactions among SUs as well as their influences from PUs in the multi-hop structure of the network. A multi-stage fictitious play learning is used for distributed routing in multi-hop CR networks. We obtain a set of mixed (behavioral) Nash equilibrium strategies of the dynamic game in closed form by backward induction. The proposed algorithm minimizes the overall interference and the average packet delay along the routing path from SU nodes to CPC base stations in an optimal and distributed manner
机构、总结、中文摘要均由AI分析而来，可能存在错误，请以论文正文为准。
