Age of information (AoI) has been proposed as a more suitable metric for characterizing the freshness of information than traditional metrics like delay and throughput. However, the calculation of AoI requires complex analysis and strict end-to-end synchronization. Most existential AoI-related works have assumed that the statistical characterizations of the arrival process and the service process are known. In fact, due to the randomness of the sources and the channel noises, these processes are often unavailable in reality. To this end, we propose a method to estimate the average AoI on a point-to-point wireless Rayleigh channel, which uses the available finite order statistical moments of the arrival process. Based on this method, we explicitly present the upper and lower bounds on the average AoI of the system. Our results show that 1) with the increase of the traffic intensity, the absolute error of the estimated average AoI bounds is first increasing and then decreasing, while the average AoI is monotonically increasing; 2) the average AoI can be effectively approximated by using the first two order moment estimation bounds, especially when traffic intensity is small or approaches unity; 3) tighter bounds can be obtained by using more moments.

翻译：信息年龄（AoI）已被提出作为一种比延迟和吞吐量等传统指标更适用于表征信息新鲜度的度量。然而，AoI的计算需要复杂的分析和严格的端到端同步。现有的大多数与AoI相关的研究都假设到达过程和服务过程的统计特征是已知的。实际上，由于信源的随机性和信道噪声，这些过程在现实中往往是不可知的。为此，我们提出了一种在点对点无线瑞利信道上估计平均AoI的方法，该方法利用到达过程可用的有限阶统计矩。基于此方法，我们明确给出了系统平均AoI的上下界。我们的结果表明：1）随着业务强度的增加，估计的平均AoI边界的绝对误差先增大后减小，而平均AoI单调递增；2）使用前两阶矩估计边界可有效逼近平均AoI，尤其是在业务强度较小或趋近于1时；3）使用更多阶矩可得到更紧的边界。