User-Mobility-Aware Optimization of Fiber Placement in Hybrid Fiber–IAB Networks Piotr Lechowicz 1, * , Charitha Madapatha 1 , Carlos Natalino Tommy Svensson 1 , Paolo Monti 1
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1 Department of Electrical Engineering, Chalmers University of Technology, Gothenburg, Sweden
arXiv:2606.18016v1 [cs.NI] 16 Jun 2026
Abstract: Metaheuristic optimization of hybrid fiber–IAB networks demonstrates that integrating user dynamics into topology design enables more adaptive and cost-efficient backhaul architectures, contributing to the development of scalable and flexible 6G network infrastructures. This is the authors’ version of this publication. The final published version is available at https://doi.org/10.1364/OFC.2026.W1H.7. 1. Introduction 6G networks necessitate the design of dynamic and resilient access topologies that integrate multiple confluent backhaul technologies to provide ubiquitous coverage with high data rates and ultra-reliable connectivity [1]. To meet these demanding requirements, mobile networks will increasingly rely on the densification of wireless Base Stations (BSs) achieved by deploying multiple low-power Small Base Stations (SBSs) closer to end users, leveraging millimeter-wave and sub-terahertz transmission spectra to increase frequency reuse. However, such densification poses significant challenges for the x-haul transport network, since providing fiber-optic connectivity to every SBS remains both economically and logistically prohibitive. From the mobile network perspective, existing solutions to mitigate these constraints are mainly based on the concept of Integrated Access and Backhaul (IAB). Using in-band IAB, an SBS connects to a Macro Base Station (MBS) (i.e., IAB donor) using the same frequency resources that are normally assigned to serve end users. The donor provides wireless backhaul connectivity to one or more IAB child nodes, enabling multi-hop connections through the access spectrum. While this approach requires no additional infrastructure, increased reliance on IAB reduces the spectrum available for access, degrading user coverage and quality of service. Previous studies have shown that the performance of IAB-based networks can be significantly improved by selectively adding fiber connections between certain base stations and their donors. Even without connecting all base stations via fiber, properly choosing a subset of SBSs for fiber backhaul can already enhance user coverage [2], i.e., the percentage of users whose achievable data rate exceeds a predefined threshold. However, such design decisions are typically made assuming static user distributions, whereas in practical mobile scenarios, user movement over time affects where backhaul capacity is most beneficial. Motivated by this observation, a relevant question arises on what will be the best hybrid design combining IAB and fiber to maximize user coverage under a fixed number of fiber-connected SBSs, while considering the dynamics introduced by user mobility. Related optimization problems have been explored Genetic Algorithm (GA) [3], Deep Reinforcement Learning (DRL) [4], and joint resource placement methods [5], but most assume static user distributions yielding topologies that degrade under realistic user mobility, an aspect that must be explicitly addressed in hybrid fiber-IAB design. This work addresses this gap by introducing user-mobility-aware metaheuristic optimization strategy for the design of hybrid fiber-IAB topologies. The proposed method explicitly integrates user mobility into the optimization process, identifying which SBSs should be fiber-connected under a fixed deployment budget to maximize end-user coverage over time. Performance evaluation in a 3GPP urban-macro scenario with random waypoint mobility shows that the proposed mobility-aware metaheuristic achieves 22.8% higher user coverage compared to greedy baselines and a 5.1% improvement over mobility-unaware metaheuristic designs, confirming that explicitly accounting for user movement yields more efficient hybrid fiber-IAB configurations. Importantly, these benefits are achieved without increasing infrastructure cost, underscoring the cost-efficiency and practical relevance of mobility-aware optimization for future 6G backhaul design. 2. Problem Description and Proposed Solutions We consider an urban macro environment with a fixed coverage area where MBSs and SBSs are deployed as hybrid IAB systems to serve a set of User Equipments (UEs) [2]. Fig. 1 shows an example of such a system.
Value
Area Size MBS count SBS count (N) Fiber SBS count (k) Users per drop Number of drops Time steps Carrier frequency Bandwidth Beamwidth Coverage threshold (η) Backhaul split (β )
1km × 1km 5 80 40 100 10 600 28 GHz 1 GHz 60° 100 Mbps 0.5
Table 1: Simulation parameters.