Delay reduction and interference mitigation by resource management for IAB networks

To overcome the increasing demand for high-throughput data services, the 3rd Generation Partnership Project (3GPP) has proposed Integrated Access and Backhaul (IAB) in Release 16 as a scalable and cost-effective alternative to traditional fiber backhaul for 5 G systems. A key feature of IAB is the shared use of the same spectrum band for both access and backhaul communications, which introduces challenges related to interference, delays, capacity sharing, and additional complexity due to the half-duplex constraint. In this paper, we provide an overview of the 3GPP guidelines for IAB resource management and introduce a semi-centralized, heuristic-based resource management policy aimed at jointly enhancing end-to-end delay and minimizing interference in IAB networks, in compliance with 3GPP standards. We conduct a comparative study of our proposed policy against several policies, including the baseline proposed by 3GPP. The evaluation is performed through discrete-event simulations under two types of traffic and varying network loads. The simulation results underline that our semi-centralized resource management policy effectively controls interference, leading to improved network Key Performance indicators (KPIs) like system throughput and end-to-end delay. Specifically, our solution achieves up to an 11% increase in system throughput and a 30% reduction in end-to-end delay compared to the baseline for constant traffic, while for variable traffic, it results in a 16% increase in system throughput and a 26% reduction in end-to-end delay.

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Publication Details

Journal
Discover Applied Sciences
Published
2024-11-20
DOI
https://doi.org/10.1007/s42452-024-06342-x
Citations
2
Primary Topic
Advanced Wireless Network Optimization
Type
article
Field-Weighted Citation Impact
0.42
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article

Delay reduction and interference mitigation by resource management for IAB networks

Patrick Savelli, Chourouk Ghodhbane, Cédric Gueguen, Xavier Lagrange
2 citations
Discover Applied Sciences
Advanced Wireless Network Optimization
0.42
article

Delay reduction and interference mitigation by resource management for IAB networks

Patrick Savelli, Chourouk Ghodhbane, Cédric Gueguen, Xavier Lagrange
article en
2 citations

Abstract

To overcome the increasing demand for high-throughput data services, the 3rd Generation Partnership Project (3GPP) has proposed Integrated Access and Backhaul (IAB) in Release 16 as a scalable and cost-effective alternative to traditional fiber backhaul for 5 G systems. A key feature of IAB is the shared use of the same spectrum band for both access and backhaul communications, which introduces challenges related to interference, delays, capacity sharing, and additional complexity due to the half-duplex constraint. In this paper, we provide an overview of the 3GPP guidelines for IAB resource management and introduce a semi-centralized, heuristic-based resource management policy aimed at jointly enhancing end-to-end delay and minimizing interference in IAB networks, in compliance with 3GPP standards. We conduct a comparative study of our proposed policy against several policies, including the baseline proposed by 3GPP. The evaluation is performed through discrete-event simulations under two types of traffic and varying network loads. The simulation results underline that our semi-centralized resource management policy effectively controls interference, leading to improved network Key Performance indicators (KPIs) like system throughput and end-to-end delay. Specifically, our solution achieves up to an 11% increase in system throughput and a 30% reduction in end-to-end delay compared to the baseline for constant traffic, while for variable traffic, it results in a 16% increase in system throughput and a 26% reduction in end-to-end delay.

Discover Applied SciencesVol. 6(12)
Centre National de la Recherche Scientifique (FR), Institut de Recherche en Informatique et Systèmes Aléatoires (FR), IMT Atlantique (FR), Institut de Recherche Technologique B-com (FR), Université de Rennes (FR)
Openalex Percentile: Top 36%
Advanced Wireless Network Optimization
0.42
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