针对认知无线Ad Hoc网络(Cognitive Radio Ad Hoc Networks,CRAHNs)下垫式(Underlay)频谱接入模型,次用户节点对主用户干扰功率过高,以及次用户节点能量过早耗尽的问题,提出了基于粒子群优化算法的联合功率控制的路由与频谱分配算法PRSA...针对认知无线Ad Hoc网络(Cognitive Radio Ad Hoc Networks,CRAHNs)下垫式(Underlay)频谱接入模型,次用户节点对主用户干扰功率过高,以及次用户节点能量过早耗尽的问题,提出了基于粒子群优化算法的联合功率控制的路由与频谱分配算法PRSA,以最小化次用户对主用户的干扰功率与延长网络生存时间为目标,包括粒子编码与粒子初始化、适应度函数、粒子飞行。设计了包含信道与发射功率等级二元组的邻接矩阵粒子编码结构,以及重新定义了粒子的3种运算规则。仿真结果表明,PRSA能在最小化对主用户的干扰功率的同时,延长网络生存时间。展开更多
认知无线Ad Hoc网络(Cognitive Radio Ad Hoc Networks,CRAHNs)中某一链路的SINR低于门限值时,将导致端到端路径中断,针对该问题,以最小化路径的中断概率为目标,研究次用户节点总发射功率受限,以及次用户对主用户干扰功率受限的情况下,...认知无线Ad Hoc网络(Cognitive Radio Ad Hoc Networks,CRAHNs)中某一链路的SINR低于门限值时,将导致端到端路径中断,针对该问题,以最小化路径的中断概率为目标,研究次用户节点总发射功率受限,以及次用户对主用户干扰功率受限的情况下,联合功率控制的路由与频谱分配策略.联合功率控制的路由与频谱分配问题非常复杂,是NP问题,为了有效求解该问题,提出基于遗传算法的联合功率控制的路由与频谱分配算法JPCRA.通过大量的仿真发现,我们提出的JPCRA算法能达到预定目标,构造的路径不仅具有较低的中断概率,而且有效地降低了对主用户节点的干扰功率.展开更多
针对目前经典的本地协作多信道MAC协议(LCM-MAC)缺乏频谱感知和带宽动态分配问题,提出一种认知无线电自组织网络(cognitive radio Ad hoc networks,CRAHNs)带宽动态分配多信道MAC(CR-LMAC)协议。通过引入频谱感知机制和新的带宽分配策...针对目前经典的本地协作多信道MAC协议(LCM-MAC)缺乏频谱感知和带宽动态分配问题,提出一种认知无线电自组织网络(cognitive radio Ad hoc networks,CRAHNs)带宽动态分配多信道MAC(CR-LMAC)协议。通过引入频谱感知机制和新的带宽分配策略模型,改进LCM-MAC协议,使其具备空闲信道感知和动态分配带宽的自适应能力。仿真结果表明,改进后的协议性能优于LCM-MAC,在网络总吞吐量和端到端时延等方面有较大提高和改善。展开更多
For the realization of green communications in cognitive radio ad hoc networks(CRAHNs), selfadaptive and efficient power allocation for secondary users(SUs) is essential. With the distributed and timevarying network t...For the realization of green communications in cognitive radio ad hoc networks(CRAHNs), selfadaptive and efficient power allocation for secondary users(SUs) is essential. With the distributed and timevarying network topology, it needs to consider how to optimize the throughput and power consuming, avoid the interference to primary users(PUs) and other SUs, and pay attention to the convergence and fairness of the algorithm. In this study, this problem is modeled as a constraint optimization problem. Each SU would adjust its power and corresponding strategy with the goal of maximizing its throughput. By studying the interactions between SUs in power allocation and strategy selection, we introduce best-response dynamics game theory and prove the existence of Nash equilibrium(NE) point for performance analysis. We further design a fully distributed algorithm to make the SUs formulate their strategy based on their utility functions, the strategy and number of neighbors in local area. Compared with the water-filling(WF) algorithm, the proposed scheme can significantly increase convergent speed and average throughput, and decrease the power consuming of SUs.展开更多
文摘针对认知无线Ad Hoc网络(Cognitive Radio Ad Hoc Networks,CRAHNs)下垫式(Underlay)频谱接入模型,次用户节点对主用户干扰功率过高,以及次用户节点能量过早耗尽的问题,提出了基于粒子群优化算法的联合功率控制的路由与频谱分配算法PRSA,以最小化次用户对主用户的干扰功率与延长网络生存时间为目标,包括粒子编码与粒子初始化、适应度函数、粒子飞行。设计了包含信道与发射功率等级二元组的邻接矩阵粒子编码结构,以及重新定义了粒子的3种运算规则。仿真结果表明,PRSA能在最小化对主用户的干扰功率的同时,延长网络生存时间。
文摘认知无线Ad Hoc网络(Cognitive Radio Ad Hoc Networks,CRAHNs)中某一链路的SINR低于门限值时,将导致端到端路径中断,针对该问题,以最小化路径的中断概率为目标,研究次用户节点总发射功率受限,以及次用户对主用户干扰功率受限的情况下,联合功率控制的路由与频谱分配策略.联合功率控制的路由与频谱分配问题非常复杂,是NP问题,为了有效求解该问题,提出基于遗传算法的联合功率控制的路由与频谱分配算法JPCRA.通过大量的仿真发现,我们提出的JPCRA算法能达到预定目标,构造的路径不仅具有较低的中断概率,而且有效地降低了对主用户节点的干扰功率.
文摘针对目前经典的本地协作多信道MAC协议(LCM-MAC)缺乏频谱感知和带宽动态分配问题,提出一种认知无线电自组织网络(cognitive radio Ad hoc networks,CRAHNs)带宽动态分配多信道MAC(CR-LMAC)协议。通过引入频谱感知机制和新的带宽分配策略模型,改进LCM-MAC协议,使其具备空闲信道感知和动态分配带宽的自适应能力。仿真结果表明,改进后的协议性能优于LCM-MAC,在网络总吞吐量和端到端时延等方面有较大提高和改善。
基金the National Natural Science Foundation of China(No.61271182)the Specialized Research Fund for the Doctoral Program of Higher Education(No.20120005120010)
文摘For the realization of green communications in cognitive radio ad hoc networks(CRAHNs), selfadaptive and efficient power allocation for secondary users(SUs) is essential. With the distributed and timevarying network topology, it needs to consider how to optimize the throughput and power consuming, avoid the interference to primary users(PUs) and other SUs, and pay attention to the convergence and fairness of the algorithm. In this study, this problem is modeled as a constraint optimization problem. Each SU would adjust its power and corresponding strategy with the goal of maximizing its throughput. By studying the interactions between SUs in power allocation and strategy selection, we introduce best-response dynamics game theory and prove the existence of Nash equilibrium(NE) point for performance analysis. We further design a fully distributed algorithm to make the SUs formulate their strategy based on their utility functions, the strategy and number of neighbors in local area. Compared with the water-filling(WF) algorithm, the proposed scheme can significantly increase convergent speed and average throughput, and decrease the power consuming of SUs.
