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Delay-Aware Link Scheduling in IAB Networks with Dynamic User Demands

The result's identifiers

  • Result code in IS VaVaI

    <a href="https://www.isvavai.cz/riv?ss=detail&h=RIV%2F00216305%3A26220%2F24%3APU151735" target="_blank" >RIV/00216305:26220/24:PU151735 - isvavai.cz</a>

  • Result on the web

    <a href="https://ieeexplore.ieee.org/document/10568354/" target="_blank" >https://ieeexplore.ieee.org/document/10568354/</a>

  • DOI - Digital Object Identifier

    <a href="http://dx.doi.org/10.1109/TVT.2024.3409179" target="_blank" >10.1109/TVT.2024.3409179</a>

Alternative languages

  • Result language

    angličtina

  • Original language name

    Delay-Aware Link Scheduling in IAB Networks with Dynamic User Demands

  • Original language description

    Integrated Access and Backhaul (IAB) is a costefficient network densification technology for improving the coverage and capacity of the millimeter-wave (mmWave) cellular networks. In IAB systems, user traffic is forwarded to/from the wired base station by one or more relay stations, known as IAB nodes. Due to the multi-hop relaying, these systems may be subject to large packet delays and poor performance when the load is unevenly distributed among nodes. Addressing this limitation via delay-aware access and backhaul link scheduling in IAB networks is challenging due to potentially large network scale, complex topology, half-duplex, and interference constraints. In this paper, the topical link scheduling problem is formulated as a Markov decision problem (MDP) for a single-donor IAB system with a general topology that allows for users with different delay requirements and traffic dynamics. The proposed link scheduling strategy jointly optimizes (i) user traffic routing and (ii) multiplexing of access and backhaul links under half-duplex constraints and non-negligible interference that may arise in dense IAB systems even with high beam directionality. To address the complexity of our formulated MDP, we consider several approximation methods, namely, Q-learning, Monte Carlo Tree Search (MCTS), and genetic algorithms (GAs). Then, we propose a customized version of the GA, which provides the preferred optimality-complexity trade-off and offers a 15% packet delay reduction as compared to the state-of-the-art backpressure algorithm.

  • Czech name

  • Czech description

Classification

  • Type

    J<sub>imp</sub> - Article in a specialist periodical, which is included in the Web of Science database

  • CEP classification

  • OECD FORD branch

    20203 - Telecommunications

Result continuities

  • Project

  • Continuities

    S - Specificky vyzkum na vysokych skolach

Others

  • Publication year

    2024

  • Confidentiality

    S - Úplné a pravdivé údaje o projektu nepodléhají ochraně podle zvláštních právních předpisů

Data specific for result type

  • Name of the periodical

    IEEE TRANSACTIONS ON VEHICULAR TECHNOLOGY

  • ISSN

    0018-9545

  • e-ISSN

    1939-9359

  • Volume of the periodical

    73

  • Issue of the periodical within the volume

    10

  • Country of publishing house

    US - UNITED STATES

  • Number of pages

    17

  • Pages from-to

    15125-15139

  • UT code for WoS article

    001336949600023

  • EID of the result in the Scopus database

    2-s2.0-85196761584