认知通信机会容量最大化的信道分配研究

通过数值分析表明认知用户的均匀分配将最大化认知无线网络通信机会容量。在此基础上进一步设计了最优的认知用户数和相应的信道分配算法。理论推导和数值分析表明,最优认知用户数主要取决于主用户信道数与相应的认知用户通信需求概率。同时发现,在一定主用户通信需求概率下,存在一个最优的认知用户通信需求概率,使认知无线网络通信机会容量最大。该算法为相应情况的认知无线网络配置提供了一定的理论依据。

Channel Allocation with Maximum Communication Opportunity Capacity in Cognitive Radio Networks

A numerical analysis is presented to show that the uniform allocation of cognitive users can maximize the communication opportunity capacity of cognitive radio networks. The optimal number of cognitive users and the corresponding algorithm of channel allocation are presented in this paper. Theory derivation and numerical analysis show that the optimal number of cognitive users is determined by the number of primary users, Channels and the communication requirement probability of cognitive users. In a given communication requirement probability of primary users, there is an optimal communication requirement probability of cognitive users which maximizes the communication opportunity capacity of cognitive radio networks. The proposed algorithm provides a theory basis for the configuration of cognitive radio networks.