无人机网络中基于位置预测的最优中继选择

为了解决无人机（UAV, Unmanned Aerial Vehicle）协作通信网络在完成任务时由于高机动性而会影响链路状态的问题，提出了一种基于UAV位置预测的信道中继选择算法。根据卡尔曼算法预测出UAV下一时刻的位置，提前判断链路优劣性，使更换UAV中继节点的时机更为精准。通过UAV源节点到UAV中继节点以及UAV中继节点到UAV目的节点的瞬时信道状态信息（CSI, Channel State Information）选出备选UAV中继节点集合。最优的备选UAV中继节点由贪婪算法计算而得。仿真结果证明了此方法的有效的性，链路中断的概率比随机选择算法降低了10%，且链路更加稳定。

Optimal Relay Selection Based on Location Prediction for UAV Networks

In order to solve the problem that the UAV (unmanned aerial vehicle) cooperative communication network will affect the link state due to its high mobility when completing the task, a channel relay selection algorithm based on UAV position prediction is proposed. According to the Kalman algorithm, the next time position of UAV is predicted, and the link quality is judged in advance, so that the time of replacing UAV relay node is more accurate. Through the CSI (channel state information) from the UAV source node to the UAV relay node and from the UAV relay node to the UAV destination node, an alternative set of UAV relay nodes is selected. The optimal candidate UAV relay nodes are calculated by greedy algorithm. The simulation results show that this method is effective and the probability of link interruption is 10% lower than that of random selection algorithm, and the link is more stable.