2020/05/30 by Praful D. Mankar, Mankar, Praful D., Mohamed A. Abd-Elmagid +3
Computer Science · Engineering · #Advanced MIMO Systems Optimization #Age of Information Optimization #FOS: Computer and information sciences #FOS: Electrical engineering #Information Theory (cs.IT) #IoT Networks and Protocols #Signal Processing (eess.SP) #electronic engineering #information engineering
paper · pdf · doi:10.48550/arxiv.2006.00290
openalex publication_date 2020/05/30 · openalex created_date 2022/07/26 · openalex updated_date 2026/07/28
This paper considers a large-scale wireless network consisting of\nsource-destination (SD) pairs, where the sources send time-sensitive\ninformation, termed status updates, to their corresponding destinations in a\ntime-slotted fashion. We employ Age of information (AoI) for quantifying the\nfreshness of the status updates measured at the destination nodes for two\ndifferent queuing disciplines, namely Type I and II queues. Type I queue is\nassumed to transmit the status updates in a first-come-first-served (FCFS)\nfashion with no storage facility. However, Type I queue may not necessarily\nminimize AoI because a new update will not be allowed to enter a server until\nthe current update has been successfully transmitted. To overcome this\nshortcoming, we consider Type II queue in which the most recent status update\navailable at a given transmission slot is transmitted in order to minimize the\nAoI. As the update delivery rate for a given link is a function of the\ninterference field seen from the receiver, the temporal mean AoI can be treated\nas a random variable over space. Our goal in this paper is to characterize the\nspatial distribution of the mean AoI observed by the SD pairs by modeling them\nas a Poisson bipolar process. Towards this objective, we first derive accurate\nbounds on the moments of success probability while efficiently capturing the\ninterference-induced coupling in the activities of the SD pairs. Using this\nresult, we then derive tight bounds on the moments as well as the spatial\ndistribution of peak AoI. Our numerical results verify our analytical findings\nand demonstrate the impact of various system design parameters on the mean peak\nAoI.\n