摘要
采用连续时间马尔科夫链对有缓冲机制的认知系统进行建模和分析,针对过多的认知用户接入会导致业务中断的特点,设计算法控制认知用户的接入概率,在满足用户中断概率限制的前提下最大化系统容量。仿真结果表明,在使用该算法的系统中,用户的接入概率与系统吞吐量随中断概率限制的增大而增大,中断概率限制下的最大接入概率即为最大化系统容量的接入概率,用户中断概率限制的满足是以牺牲系统吞吐量为代价的。同时,引入缓冲机制能够提高用户的接入概率和系统容量。
We built and analyzed the model of the cognitive radio system with buffering by continuous time Markov. Aimed at the character that the access of overmany users will result in the forced termination of the service, we designed an algorithm to control access probability of the cognitive users, which maximizes system throughput in the precondition of satisfying the forced termination limitation. The simulation result shows that, in the system using the algorithm, the user access probability and system throughput increase with the forced termination limitation. Also the largest access probability under the forced termination limitation is the access probability which can maximize the system throughput. The system satisfies the forced termination limitation at the sacrifice of throughput. At the same time, the simulation indicates that the introduction of buffering can improve the user access probability and the system throughput performance.
出处
《计算机科学》
CSCD
北大核心
2012年第3期79-82,共4页
Computer Science
基金
东莞市高等院校科研机构科技计划项目(2011108102030)资助
关键词
认知无线电
缓冲机制
接入控制
马尔科夫链
中断概率
Cognitive radio, Buffering,Access control, Markov chain, Forced termination probability
