Dynamic Hierarchical Power Control in Multi-User Cognitive Wi-Fi 2.0 Wireless Networks

Abstract

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.;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.