LAUSR

The information freshness, quantified by the emerging idea of Age of Information (AoI), has recently received widespread attentions from both academia and industry. However, most prior works on AoI considered a single source-destination pair and provided the performance analysis merely through queueing-theoretic models, which do not lend themselves to the analysis of large-scale wireless networks. This paper focuses on the AoI analysis in a large-scale setting using random spatial models in stochastic geometry. Specifically, we first adopt rateless coding for packet delivery to improve the transmission reliability while reducing the transmission delay. Then, to quantify the enhancement of the information freshness by rateless coding, we derive the average peak age of information (PAoI) in Poisson bipolar and cellular networks, which characterizes the maximum value of AoI immediately before an update packet is received accounting for the spatial variation of network nodes and temporal dynamics of service packets. With these results, we further give the conditions that make the average PAoI to be finite in each type of the network. Numerical results show the significant benefits of rateless codes relative to the commonly used fixed-rate codes in terms of the PAoI and the feasible region of system parameters such as the traffic arrival rate, transmit probability, etc., in Poisson bipolar and cellular networks.