软件学报
軟件學報
연건학보
JOURNAL OF SOFTWARE
2013年
6期
1310-1323
,共14页
杨春刚%盛敏%李建东%李红艳
楊春剛%盛敏%李建東%李紅豔
양춘강%성민%리건동%리홍염
认知Wi-Fi 2.0无线网络%功率控制%博弈论%斯坦科尔伯格均衡
認知Wi-Fi 2.0無線網絡%功率控製%博弈論%斯坦科爾伯格均衡
인지Wi-Fi 2.0무선망락%공솔공제%박혁론%사탄과이백격균형
cognitive Wi-Fi 2.0 network%power control%game theory%Stackelberg equilibrium
具有认知性、自主性和适变性等特点的认知Wi-Fi 2.0无线网络技术,作为提高无线网络容量的重要技术不断引起学术界、标准组织和工业界的关注.针对现有功率控制技术不能刻画多个认知节点存在分层决策的现象,提出一种认知Wi-Fi 2.0无线网络中多用户动态分层功率控制算法.基于提出的斯坦科尔伯格(Stackelberg)容量最大化博弈模型,为认知Wi-Fi 2.0无线网络中感知信息不对称的多用户分别设计了分布式功率控制方法,实现领导者用户和跟随者用户的多阶段动态交互在保证个体效用的同时实现网络整体性能.该算法根据当前认知Wi-Fi 2.0无线网络中多个认知节点接入频谱顺序的不同,确定领导者用户和跟随者用户;然后,对于领导者和跟随者分别采用不同的功率控制策略,并多次交互实现多用户分层算法的动态交互收敛.蒙特卡洛仿真验证了算法的有效性.
具有認知性、自主性和適變性等特點的認知Wi-Fi 2.0無線網絡技術,作為提高無線網絡容量的重要技術不斷引起學術界、標準組織和工業界的關註.針對現有功率控製技術不能刻畫多箇認知節點存在分層決策的現象,提齣一種認知Wi-Fi 2.0無線網絡中多用戶動態分層功率控製算法.基于提齣的斯坦科爾伯格(Stackelberg)容量最大化博弈模型,為認知Wi-Fi 2.0無線網絡中感知信息不對稱的多用戶分彆設計瞭分佈式功率控製方法,實現領導者用戶和跟隨者用戶的多階段動態交互在保證箇體效用的同時實現網絡整體性能.該算法根據噹前認知Wi-Fi 2.0無線網絡中多箇認知節點接入頻譜順序的不同,確定領導者用戶和跟隨者用戶;然後,對于領導者和跟隨者分彆採用不同的功率控製策略,併多次交互實現多用戶分層算法的動態交互收斂.矇特卡洛倣真驗證瞭算法的有效性.
구유인지성、자주성화괄변성등특점적인지Wi-Fi 2.0무선망락기술,작위제고무선망락용량적중요기술불단인기학술계、표준조직화공업계적관주.침대현유공솔공제기술불능각화다개인지절점존재분층결책적현상,제출일충인지Wi-Fi 2.0무선망락중다용호동태분층공솔공제산법.기우제출적사탄과이백격(Stackelberg)용량최대화박혁모형,위인지Wi-Fi 2.0무선망락중감지신식불대칭적다용호분별설계료분포식공솔공제방법,실현령도자용호화근수자용호적다계단동태교호재보증개체효용적동시실현망락정체성능.해산법근거당전인지Wi-Fi 2.0무선망락중다개인지절점접입빈보순서적불동,학정령도자용호화근수자용호;연후,대우령도자화근수자분별채용불동적공솔공제책략,병다차교호실현다용호분층산법적동태교호수렴.몽특잡락방진험증료산법적유효성.
Cognitive Wi-Fi 2.0 wireless networks with the typical characteristics of cognition, reconfirmation and self-organizing abilities as the novel open spectrum sharing technology, that are used to improve the network performance, have promisingly captured a great attention from the wireless community. In this paper, to capture the hierarchical decision-making properties of the power control, the study proposes a dynamic hierarchical power control for the cognitive Wi-Fi 2.0 wireless networks. The spectrum sharing issue is formulated as the Stackelberg game with the more foresighted cognitive users as the leaders and short-sighted users as follower, and the paper derives the closed-form power policy, respectively. Meanwhile, the study concludes that this policy can achieve the optimal performance in the weak interference environment after analysis. Simulations results show that the proposed algorithm converges after limited iterations, which also effectively guarantees the optimal trade-off between the individual performance and the network overall performance.