Assessing the Benefits of Ground Vehicles as Moving Urban Base Stations

2025-07-21

AI Summary

In user-centric 6G networks, mobile base stations (e.g., vehicle-mounted small cells) promise enhanced flexibility and resource efficiency, yet their cost-benefit trade-offs remain poorly quantified. Method: This paper proposes a unified stochastic geometric framework jointly modeling dynamic vehicular base station deployment, wireless backhaul constraints, resource scheduling, and user mobility—while guaranteeing end-to-end QoS requirements. It integrates stochastic geometry analysis, backhaul-aware resource allocation, and an efficient stochastic heuristic optimization algorithm. Contribution/Results: The proposed dynamic “follow-the-user” strategy reduces base station deployment density by up to 40% compared to static deployment, while meeting per-user latency and throughput targets. These results provide theoretical foundations and quantitative evidence for economically viable mobile infrastructure deployment in 6G networks.

Technology Category

• Planning, Routing, and Scheduling: Optimization of Spatio-temporal Systems
• Reasoning under Uncertainty: Stochastic Optimization
• Search and Optimization: Sampling/Simulation-based Search

Application Category

• Systems and Infrastructure for Web, Mobile and WoT: Virtualization and resource management in Web systems and infrastructures
• Graph Algorithms and Modeling for the Web: Efficient manipulation of static and dynamic Web-related graphs
• Economics, Online Markets and Human Computation: Incentives in network design for Web infrastructures and ecosystems

Abstract

In the evolution towards 6G user-centric networking, the moving network (MN) paradigm can play an important role. In a MN, some small cell base stations (BS) are installed on top of vehicles, and enable a more dynamic, flexible and sustainable, network operation. By "following" the users movements and adapting dynamically to their requests, the MN paradigm enables a more efficient utilization of network resources, mitigating the need for dense small cell BS deployments at the cost of an increase in resource utilization due to wireless backhauling. This aspect is at least partly compensated by the shorter distance between users and BS, which allows for lower power and Line-of-Sight communications. While the MN paradigm has been investigated for some time, to date, it is still unclear in which conditions the advantages of MN outweigh the additional resource costs. In this paper, we propose a stochastic geometry framework for the characterization of the potential benefits of the MN paradigm as part of an HetNet in urban settings. Our approach allows the estimation of user-perceived performance, accounting for wireless backhaul connectivity as well as base station resource scheduling. We formulate an optimization problem for determining the resource-optimal network configurations and BS scheduling which minimize the overall amount of deployed BSs in a QoS-aware manner, and the minimum vehicular flow between different urban districts required to support them, and we propose an efficient stochastic heuristic to solve it. Our numerical assessment suggests that the MN paradigm, coupled with appropriate dynamic network management strategies, significantly reduces the amount of deployed network infrastructure while guaranteeing the target QoS perceived by users.

Problem

• Evaluates benefits of vehicle-mounted base stations in 6G networks
• Determines optimal conditions for moving network advantages over costs
• Minimizes deployed infrastructure while maintaining user QoS requirements

Innovation

• Vehicles host small cell base stations
• Dynamic network management optimizes resources
• Stochastic geometry evaluates MN benefits