论文部分内容阅读
为了刻画认知无线网络中次级用户数据请求的批量到达行为,针对动态频谱分配策略,建立一种传输可中断的批量到达排队模型.假设主用户数据包的到达率服从参数为λ2的指数分布,次级用户数据包的批量到达过程服从参数为Λ的泊松分布,批量大小服从参数为α的几何分布;假设成功传输一个次级用户数据包的需要的时间服从参数为μ1的指数分布,采用M arkov链方法进行排队模型的稳态分析,给出次级用户数据包平均延迟的封闭解.通过建立收益函数,证明纳什均衡下的批量到达率高于社会最优下的批量到达率.面向次级用户给出收费方案,实现动态频谱分配策略的社会最优.
In order to characterize the batch arrival of sub-user data requests in cognitive wireless networks, a batch transmission queuing model is established for dynamic allocation of spectrum.It is assumed that the arrival rate of primary user data packets follows the exponential distribution with parameter λ2 , The sub-user packet’s batch arrival process obeys the Poisson distribution with parameter Λ, and the batch size obeys the geometric distribution with parameter α. Assuming the time required to successfully transmit a sub-user packet follows the exponential distribution with parameter μ1, The steady state analysis of queuing model with M arkov chain method is given, and the closed-form solution to the average delay of sub-user data packets is given. By establishing the revenue function, it is proved that the batch arrival rate under Nash equilibrium is higher than the batch arrival rate under social optimum. Targeting sub-users to provide charging scheme and realizing social optimum of dynamic spectrum allocation strategy.