多目标遗传算法求解认知无线电SUL维持问题

Solving SUL maintaining problem of cognitive radio with multiobjective evolutionary algorithm

当某个一级用户重新出现时,二级用户必须马上让出属于此一级用户的频谱,此时就存在着如何维持二级用户链接(Secondary Users’Link,SUL)的问题。基于CORVUS系统的"冗余子信道"模型在SUL原有的N个子信道基础上再使用X个冗余子信道进行二级用户之间的通信。只要传输过程中受干扰的子信道个数少于X,接收端就可以从N+X个子信道中恢复出正确信息来,从而解决了SUL维持的问题。但尚未有一种有效的办法以求解最优的N和X。将SUL维持问题建模为一个多目标优化问题,提出了一种基于多目标遗传算法的SUL维持算法SULEA。SULEA能够根据不同的用户服务需求动态地选择适应度函数来求解最优的N和X,Matlab实验证明了SULEA的正确性和有效性。

When some primary users re-emergence,the secondary users must immediately give up the spectrum belonging to the primary users.At this point there is a problem on how to maintain the existence of the Secondary Users＇Link（SUL）.The redundant sub channels model based on CORVUS system use another X redundant sub channels besides the original N sub channels for the communications among secondary users.As long as the interfered sub channels during the transmission are less than X,the receiver can restore the correct information from the N＋X sub channels,thus solving the SUL maintaining problem.However so far,there is no effective way to solve the optimal N and X.This paper models the SUL maintaining problem as a multiobjective optimization problem,develops a new SUL maintaining algorithm called SULEA based on a multiobjective evolutionary algorithm.SULEA can dynamically select the fitness functions according to the user＇s different service need,so as to solve the optimal N and X,and the results of Matlab simulation experiment testify the validity of SULEA.