On Topology Optimization and Routing in Integrated Access and Backhaul Networks: A Genetic Algorithm-based Approach

Charitha Madapatha, Behrooz Makki, Ajmal Muhammad, Erik Dahlman, Mohamed-Slim Alouini, Tommy Svensson

Research output: Contribution to journalArticlepeer-review

16 Scopus citations


In this paper, we study the problem of topology optimization and routing in integrated access and backhaul (IAB) networks, as one of the promising techniques for evolving 5G networks. We study the problem from different perspectives. We develop efficient genetic algorithm-based schemes for both IAB node placement and non-IAB backhaul link distribution, and evaluate the effect of routing on bypassing temporal blockages. Here, concentrating on millimeter wave-based communications, we study the service coverage probability, defined as the probability of the event that the user equipments’ (UEs) minimum rate requirements are satisfied. Moreover, we study the effect of different parameters such as the antenna gain, blockage, and tree foliage on the system performance. Finally, we summarize the recent Rel-16 as well as the upcoming Rel-17 3GPP discussions on routing in IAB networks, and discuss the main challenges for enabling mesh-based IAB networks. As we show, with a proper network topology, IAB is an attractive approach to enable the network densification required by 5G and beyond.
Original languageEnglish (US)
Pages (from-to)1-1
Number of pages1
JournalIEEE Open Journal of the Communications Society
StatePublished - 2021

Bibliographical note

KAUST Repository Item: Exported on 2021-09-29
Acknowledgements: This work was supported in part by VINNOVA (Swedish Government Agency for Innovation Systems) within the VINN Excellence Center ChaseOn and in part by the European Commission through the H2020 project Hexa-X (Grant Agreement no. 101015956). The work of C. Madapatha in this publication is part of his research work at Chalmers University of Technology.


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