Assessing the Benefits of Ground Vehicles as Moving Urban Base Stations

TL;DR

This paper introduces a stochastic geometry framework to evaluate the benefits of using moving ground vehicles as dynamic base stations in urban 6G networks, showing potential for infrastructure reduction while maintaining QoS.

Contribution

It develops a novel stochastic geometry model and optimization approach to quantify when moving base stations outperform static deployments in urban HetNets.

Findings

Significant reduction in deployed infrastructure with proper management.

Dynamic base stations can meet QoS requirements effectively.

Framework accounts for wireless backhaul and resource scheduling.

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.