The transmission delay of realtime video packet mainly depends on the sensing time delay(short-term factor) and the entire frame transmission delay(long-term factor).Therefore,the optimization problem in the spectrum ...The transmission delay of realtime video packet mainly depends on the sensing time delay(short-term factor) and the entire frame transmission delay(long-term factor).Therefore,the optimization problem in the spectrum handoff process should be formulated as the combination of microscopic optimization and macroscopic optimization.In this paper,we focus on the issue of combining these two optimization models,and propose a novel Evolution Spectrum Handoff(ESH)strategy to minimize the expected transmission delay of real-time video packet.In the microoptimized model,considering the tradeoff between Primary User's(PU's) allowable collision percentage of each channel and transmission delay of video packet,we propose a mixed integer non-linear programming scheme.The scheme is able to achieve the minimum sensing time which is termed as an optimal stopping time.In the macro-optimized model,using the optimal stopping time as reward function within the partially observable Markov decision process framework,the EHS strategy is designed to search an optimal target channel set and minimize the expected delay of packet in the long-term real-time video transmission.Meanwhile,the minimum expected transmission delay is obtained under practical cognitive radio networks' conditions,i.e.,secondary user's mobility,PU's random access,imperfect sensing information,etc..Theoretical analysis and simulation results show that the ESH strategy can effectively reduce the transmission delay of video packet in spectrum handoff process.展开更多
针对异构环境下不同业务类型用户对于接入网络的不同服务质量(quality of service,Qo S)需求,该文提出了一种基于马尔可夫决策模型的切换选择算法.建立基于软件定义网络(software defined network,SDN)的异构无线网络架构,以实现对异构...针对异构环境下不同业务类型用户对于接入网络的不同服务质量(quality of service,Qo S)需求,该文提出了一种基于马尔可夫决策模型的切换选择算法.建立基于软件定义网络(software defined network,SDN)的异构无线网络架构,以实现对异构网络的通透控制.利用马尔可夫过程预测下一时刻的网络状态以得到采取动作后的一次回报,依据网络的不同状态属性针对实时用户和非实时用户分别构建立即回报函数,并采用层次分析法确定属性权重;基于状态动作对构建期望回报函数,采用逐次逼近的迭代方式得到使长期期望回报最大的切换策略.仿真结果表明,该方法针对不同业务类型用户均能选取最优切换策略,同时降低阻塞率,提高了用户的Qo S和无线网络的资源利用率.展开更多
基金supported by the National Natural Science Foundation of China under Grant No.61301101
文摘The transmission delay of realtime video packet mainly depends on the sensing time delay(short-term factor) and the entire frame transmission delay(long-term factor).Therefore,the optimization problem in the spectrum handoff process should be formulated as the combination of microscopic optimization and macroscopic optimization.In this paper,we focus on the issue of combining these two optimization models,and propose a novel Evolution Spectrum Handoff(ESH)strategy to minimize the expected transmission delay of real-time video packet.In the microoptimized model,considering the tradeoff between Primary User's(PU's) allowable collision percentage of each channel and transmission delay of video packet,we propose a mixed integer non-linear programming scheme.The scheme is able to achieve the minimum sensing time which is termed as an optimal stopping time.In the macro-optimized model,using the optimal stopping time as reward function within the partially observable Markov decision process framework,the EHS strategy is designed to search an optimal target channel set and minimize the expected delay of packet in the long-term real-time video transmission.Meanwhile,the minimum expected transmission delay is obtained under practical cognitive radio networks' conditions,i.e.,secondary user's mobility,PU's random access,imperfect sensing information,etc..Theoretical analysis and simulation results show that the ESH strategy can effectively reduce the transmission delay of video packet in spectrum handoff process.
文摘针对异构环境下不同业务类型用户对于接入网络的不同服务质量(quality of service,Qo S)需求,该文提出了一种基于马尔可夫决策模型的切换选择算法.建立基于软件定义网络(software defined network,SDN)的异构无线网络架构,以实现对异构网络的通透控制.利用马尔可夫过程预测下一时刻的网络状态以得到采取动作后的一次回报,依据网络的不同状态属性针对实时用户和非实时用户分别构建立即回报函数,并采用层次分析法确定属性权重;基于状态动作对构建期望回报函数,采用逐次逼近的迭代方式得到使长期期望回报最大的切换策略.仿真结果表明,该方法针对不同业务类型用户均能选取最优切换策略,同时降低阻塞率,提高了用户的Qo S和无线网络的资源利用率.
