Due to its opportunistic spectrum sharing capability, cognitive radio （CR） has been proposed as a fundamental solution to alleviate the contradiction between spectrum scarcity and inefficient utilization of licensed...Due to its opportunistic spectrum sharing capability, cognitive radio （CR） has been proposed as a fundamental solution to alleviate the contradiction between spectrum scarcity and inefficient utilization of licensed spectrum. In CR system （CRS）, to efficiently utilize the spectrum resource, one important issue is to allocate the sensing and transmission duration reasonably. In this paper, the evaluation metric of energy efficiency, which represented the total number of bits that were delivered with per joule of energy consumed, is adopted to evaluate the proposed scheme. We study a joint design of energy efficient sensing and transmission durations to maximize energy efficiency capacity （EEC） of CRS. The tradeoff between EEC and sensing and transmission durations are formulized as an optimization problem under constraints on target detection probability of secondary users （SUs） and toleration interference threshold of primary users （PUs）. To obtain the optimal solution, optimizing sensing duration and transmission duration will be first performed separately. Then, a joint optimization iterative algorithm is proposed to search the optimal pair of sensing and transmission durations. Analytical and simulation results show that there exists a unique duration pair where the EEC is maximized, and that the EEC of the proposed joint optimization algorithm outperforms that of existed algorithms. Furthermore, the simulation results also reveal that the performance of the proposed low complexity iterative algorithm is comparable with that of the exhaustive search scheme.展开更多
车辆的快速移动、拓扑动态变化,给车联网VANETs(Vehicular ad hoc Networks)的数据传输提出了挑战。分簇是有效解决VANETs数据传输问题之一。利用分簇技术将车辆划分不同的簇,每个簇产生1个簇头,簇头负责簇间通信,有利于提高数据传输效...车辆的快速移动、拓扑动态变化,给车联网VANETs(Vehicular ad hoc Networks)的数据传输提出了挑战。分簇是有效解决VANETs数据传输问题之一。利用分簇技术将车辆划分不同的簇,每个簇产生1个簇头,簇头负责簇间通信,有利于提高数据传输效率。为此,提出基于模糊逻辑的簇头产生FLCHS(Fuzzy Logic based Cluster Head Selection)算法。利用车辆的速度、密度和链路质量决策簇头,进而优化簇头选择过程。仿真结构表明,与LID算法相比,提出的FLCHS算法的簇头寿命提高了近20%,数据传输率提高了近45%。展开更多
基金supported by the National Natural Science Foundation of China (61001116)the National Science and Technology Major Project (2012ZX03003006)
文摘Due to its opportunistic spectrum sharing capability, cognitive radio （CR） has been proposed as a fundamental solution to alleviate the contradiction between spectrum scarcity and inefficient utilization of licensed spectrum. In CR system （CRS）, to efficiently utilize the spectrum resource, one important issue is to allocate the sensing and transmission duration reasonably. In this paper, the evaluation metric of energy efficiency, which represented the total number of bits that were delivered with per joule of energy consumed, is adopted to evaluate the proposed scheme. We study a joint design of energy efficient sensing and transmission durations to maximize energy efficiency capacity （EEC） of CRS. The tradeoff between EEC and sensing and transmission durations are formulized as an optimization problem under constraints on target detection probability of secondary users （SUs） and toleration interference threshold of primary users （PUs）. To obtain the optimal solution, optimizing sensing duration and transmission duration will be first performed separately. Then, a joint optimization iterative algorithm is proposed to search the optimal pair of sensing and transmission durations. Analytical and simulation results show that there exists a unique duration pair where the EEC is maximized, and that the EEC of the proposed joint optimization algorithm outperforms that of existed algorithms. Furthermore, the simulation results also reveal that the performance of the proposed low complexity iterative algorithm is comparable with that of the exhaustive search scheme.
文摘车辆的快速移动、拓扑动态变化,给车联网VANETs(Vehicular ad hoc Networks)的数据传输提出了挑战。分簇是有效解决VANETs数据传输问题之一。利用分簇技术将车辆划分不同的簇,每个簇产生1个簇头,簇头负责簇间通信,有利于提高数据传输效率。为此,提出基于模糊逻辑的簇头产生FLCHS(Fuzzy Logic based Cluster Head Selection)算法。利用车辆的速度、密度和链路质量决策簇头,进而优化簇头选择过程。仿真结构表明,与LID算法相比,提出的FLCHS算法的簇头寿命提高了近20%,数据传输率提高了近45%。
