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
异构车联网中车辆终端分布不均匀会导致切换失败率高及网络吞吐量下降,针对此问题,本文提出了一种基于模糊层次分析的垂直切换算法.首先对候选网络进行筛选,对网络筛选所依据的条件是切换时刻对于候选网络负载状态的预测,然后利用模糊...异构车联网中车辆终端分布不均匀会导致切换失败率高及网络吞吐量下降,针对此问题,本文提出了一种基于模糊层次分析的垂直切换算法.首先对候选网络进行筛选,对网络筛选所依据的条件是切换时刻对于候选网络负载状态的预测,然后利用模糊层次分析法(fuzzy analytic hierarchy process,FAHP)确定各属性权重,并利用逼近理想解排序(technigue for order preference by similarity to ideal solution,TOPSIS)算法进行判决,选取最优网络进行切换.仿真结果表明,在不同车辆终端数量的场景下,本文算法能够降低切换失败率,减少切换时延,提高系统的网络吞吐量.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.
文摘异构车联网中车辆终端分布不均匀会导致切换失败率高及网络吞吐量下降,针对此问题,本文提出了一种基于模糊层次分析的垂直切换算法.首先对候选网络进行筛选,对网络筛选所依据的条件是切换时刻对于候选网络负载状态的预测,然后利用模糊层次分析法(fuzzy analytic hierarchy process,FAHP)确定各属性权重,并利用逼近理想解排序(technigue for order preference by similarity to ideal solution,TOPSIS)算法进行判决,选取最优网络进行切换.仿真结果表明,在不同车辆终端数量的场景下,本文算法能够降低切换失败率,减少切换时延,提高系统的网络吞吐量.
