认知无线电系统多接入用户信息新鲜度研究

为了解决物联网信道资源有限的问题以及提高物联网系统的信息时效性，考虑了包括一个主用户(primary user, PU)和两个次用户(secondary user, SU)节点的多接入认知无线电(CR)物联网系统模型。在PU工作状态和SU数据队列稳定的约束下，分别分析了第一个SU节点在先来先服务(first come first served, FCFS)、后来先服务(last come last served, LCLS)以及包丢弃队列下的平均信息年龄(age of information, AoI),推导了在阈值策略下第二个SU节点的平均AoI。然后，提出了使第一个SU平均AoI最小化，并且第二个SU的平均AoI低于给定阈值的优化问题。优化问题的约束条件是凸的，但所得到的目标函数是非凸的，故引入了一种次优技术，利用双层凸优化算法得到最优解。仿真结果给出了所考虑优化算法在不同系统参数下的性能，该算法在不同系统参数和多天线影响下的性能表现良好。后续工作可以考虑扩展到两个以上次用户的CR物联网系统。

Research on information freshness of multiple access users in cognitive radio system

In order to solve the problem of limited channel resources of the Internet of Things(IoT) and improve the information timeliness of the IoT system, this paper considered a multi-access cognitive radio(CR) IoT system model including one primary user(PU) and two secondary user(SU) nodes. Under the constraint of PU working state and SU data queue stability, the paper analyzed the average age of information(AoI) of the first secondary user node in the first come first served(FCFS), last come last served(LCLS) and the packet dropping queue, and derived the average AoI of the second SU node in the threshold strategy. Then, the paper proposed an optimization problem to minimize the average AoI of the first user and lower the average AoI of the second user below the given threshold. The constraint condition of the problem was convex, but the objective function was non-convex, so the paper introduced a suboptimal technique and obtained the optimal solution by double convex optimization algorithm. Simulation results show the performance of the proposed algorithm under different system parameters, and the algorithm performs well under the influence of different system parameters and multiple antennas. Subsequent work can consider extending CR IoT system to more than two SUs.