基于合作博弈的认知卫星网络信道分配与上行功率控制算法

Channel Allocation and Power Control Algorithm for Cognitive Satellite Networks Based on Cooperative Game Theory

随着通信业务需求的不断增长,频谱资源的有限性使得卫星通信网络和地面网络都面临着严重的频谱危机。认知无线电技术的出现,使得卫星网络与地面网络共用频率资源以提升网络效用成为可能。文中对认知接入分配给地面网络作为主用户的同一频谱资源的认知卫星网络的功率控制和信道分配问题进行了研究。根据卫星网络和地面网络的特性构建了合理的系统模型,并利用中断概率门限表征了信道估计误差对系统容量的影响。为了保护主基站的通信性能,在考虑信道估计误差、信道资源约束、认知卫星用户最大发射功率和微波基站干扰约束的条件下,根据议价博弈理论设计了优化函数。其次,根据凸优化理论推导了最优发射功率和信道分配的闭式解,并在此基础上设计了一种对偶迭代算法来求解该优化问题。最后,根据卫星网络的特性设置了合理的网络参数,并根据参数利用Matlab仿真平台对提出的算法进行了仿真实验。仿真结果表明:所提方法在不同到达速率的条件下均具备良好的收敛性;信道估计误差会降低网络的总容量;所提方法在波束数多于15个时,相比比例公平性算法容量提升超过50 bps/Hz,相比最大容量法公平性能提升超过一倍,因此,相较于这两种方法,该方法能在系统容量和用户间公平性之间获得较好的折中。

With continuous increasing of communication service requirements,satellite networks and terrestrial networks are both facing a serious spectrum crisis because of the limitation of spectrum resource.Cognitive radio technology makes it possible to rea-lize the resource sharing for network utility improvement between satellite networks and terrestrial networks.This paper investigated the power control and channel allocation problem for cognitive satellite networks,where satellite users cognitively access the same spectrum resource allocated to terrestrial networks as primary users.A reasonable system model is constructed based on the characteristics of satellite networks and terrestrial networks,and the outage probability threshold is used to represent the effect on system capacity of channel estimation error.To protect the communication performance of primary base station,the optimization function is designed based on bargaining game theory by taking into account with channel estimation errors,constrain of channel resource,maximum transmit power of cognitive satellite users and interference constrains of primary base stations.In this paper,the closed from solutions of optimal transmit power and channel allocation for the problem are derived based on convex optimization theory,and a dual iteration algorithm is designed to find the solutions.Finally,the system parameters are set based on characteristics of satellite networks,and several simulations are obtained for the proposed algorithm with Matlab simulation platform based on the parameters.The simulation results show that the proposed algorithm has a proper convergence performance under different arrival rates.It also shows that the channel estimation error can decrease the capacity performance of the network.Compared with existing methods,the proposed algorithm can improve the capacity performance with more than 50bps/Hz than the proportional fairness method when the number of beams is more than 15,and the fairness performance is more than double of the capacity maximizing method under the same condition.Therefore,the proposed algorithm can find a reasonable trade-off between system capacity and fairness among users.