Analysis of the Polling Model of a Node in the Integrated Access and Backhaul System
Abstract
In this paper, a polling model of node service of Integrated Access and Backhaul (IAB) network is constructed to analyze the probabilistic-time characteristics (PTC) of the system, which will enable the estimation of packet transmission delays in the network. The polling-based queueing system is assumed to be Markovian. One of the queues is designed to store packets from parent nodes in the IAB network, and the second queue is designed to store packets from child nodes and user equipments associated with a given node. Cyclic polling of queues allows to consider the main feature of IAB in 5G networks – half-duplex mode of packet transmission. Using the apparatus of Markov processes, formulas for calculating the queueing delay and the time spent in the system of the request in the system, which corresponds to the delay of packet transmission in the node, are obtained. The results of the numerical analysis allow us to give an upper bound estimate for the device switching duration at which the 5G NR delay constraints are fulfilled for networks with a single relay node.
This work is licensed under a Creative Commons Attribution 4.0 International License.
Publication policy of the journal is based on traditional ethical principles of the Russian scientific periodicals and is built in terms of ethical norms of editors and publishers work stated in Code of Conduct and Best Practice Guidelines for Journal Editors and Code of Conduct for Journal Publishers, developed by the Committee on Publication Ethics (COPE). In the course of publishing editorial board of the journal is led by international rules for copyright protection, statutory regulations of the Russian Federation as well as international standards of publishing.
Authors publishing articles in this journal agree to the following: They retain copyright and grant the journal right of first publication of the work, which is automatically licensed under the Creative Commons Attribution License (CC BY license). Users can use, reuse and build upon the material published in this journal provided that such uses are fully attributed.
