摘要：A weighted selection combining （WSC） scheme is proposed to improve prediction accuracy for cooperative spectrum prediction in cognitive radio networks by exploiting spatial diversity. First, a genetic algorithm-based neural network （GANN） is designed to perform spectrum prediction in consideration of both the characteristics of the primary users （PU） and the effect of fading. Then, a fusion selection method based on the iterative self-organizing data analysis （ISODATA） algorithm is designed to select the best local predictors for combination. Additionally, a reliability-based weighted combination rule is proposed to make an accurate decision based on local prediction results considering the diversity of the predictors. Finally, a Gaussian approximation approach is employed to study the performance of the proposed WSC scheme, and the expressions of the global prediction precision and throughput enhancement are derived. Simulation results reveal that the proposed WSC scheme outperforms the other cooperative spectrum prediction schemes in terms of prediction accuracy, and can achieve significant throughput gain for cognitive radio networks.

摘要：针对巨型星座单星任务的时变性以及由此产生的负载过重、单节点脆弱性以及网络控制平面的高可靠性需求,研究面向多层多域巨型星座的卫星网络拓扑控制,提出了一种基于北斗网格位置码的多层多域拓扑描述模型。首先给出了域、层、片、元相关概念及其定义,以实现对卫星节点和星间链路的拓扑特征的统一表征,刻画卫星节点的连通状态以及整个星座的网络拓扑结构;然后设计了一套以在轨控制器为核心、以地面网络控制为辅助的拓扑控制架构,用于提供常态化运行服务保障;最后通过仿真平台对巨型星座子域划分和统一表征进行了验证分析。仿真结果表明,所提拓扑描述模型能够提高巨型星座卫星网络拓扑控制过程的实时性与准确率。

摘要：低轨卫星通信网络可以提供全球覆盖的低延迟服务,但是低轨卫星网络拓扑的频繁变化给路由设计带来了挑战。针对低轨卫星通信网络拓扑快速变化的问题,提出一种基于星间链路状态的路由算法,在卫星的实际坐标和相对位置关系的基础上,建立了逻辑拓扑结构,并计算路由跳数、传输方向和优先级,进而确定路由路径。针对链路故障问题,实时检测链路状态,并利用链路状态信息进行路由修正。在NS3仿真软件中进行仿真验证,结果表明:与传统星间路由算法相比,该算法实施简单,并能有效降低链路故障的影响,使丢包率降低20%,传输时延约为200 ms。